M365 Research

Pioneering advancements in AI and Systems

Papiers de Collaboration

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- Reason-before-Retrieve: One-Stage Reflective Chain-of-Thoughts for Training-Free Zero-Shot Composed Image Retrieval
  
  Yuanmin Tang, Xiaoting Qin, Jue Zhang, Jing Yu, Gaopeng Gou, Gang Xiong, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang, Qi Wu
  
  CVPR’25 | June 2025
  
  Preprint
- AIOpsLab: A Holistic Framework for Evaluating AI Agents for Enabling Autonomous Cloud
  
  Yinfang Chen, Manish Shetty, Gagan Somashekar, Minghua Ma, Yogesh Simmhan, Jonathan Mace, Chetan Bansal, Rujia Wang, Saravan Rajmohan
  
  MLSys ’25 | May 2025
  
  Publication
- ProtoRAIL: A Risk-cognizant Imitation Agent for Adaptive vCPU Oversubscription In The Cloud
  
  Lu Wang, Mayukh Das, Fangkai Yang, Bo Qiao, Hang Dong, Si Qin, Victor Ruehle, Chetan Bansal, Eli Cortez, Íñigo Goiri, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  MLSys’25 | May 2025
  
  Publication
- Towards Cloud Efficiency with Large-scale Workload Characterization
  
  A. Parayil, Jue Zhang, Xiaoting Qin, Íñigo Goiri, Chetan Bansal
  
  ICPE | May 2025
  
  Preprint
- Time Warp: The Gap Between Developers’ Ideal vs Actual Workweeks in an AI-Driven Era
  
  Sukrit Kumar, Drishti Goel, Tom Zimmermann, Brian Houck, B. Ashok, Chetan Bansal
  
  ICSE SEIP ’25 | April 2025
  
  Distinguished Paper Award
  
  Preprint
- Performance Aware LLM Load Balancer for Mixed Workloads
  
  Kunal Jain, A. Parayil, Ankur Mallick, Esha Choukse, Xiaoting Qin, Jue Zhang, Íñigo Goiri, Rujia Wang, Chetan Bansal, Victor Ruehle, Anoop Kulkarni, Steve Kofsky, Saravan Rajmohan
  
  EuroMLSys 2025 | April 2025
  
  Publication Project
- RuAG: Learned-rule-augmented Generation for Large Language Models
  
  Yudi Zhang, Pei Xiao, Lu Wang, Chaoyun Zhang, Meng Fang, Yali Du, Yevgeniy Puzyrev, Randolph Yao, Si Qin, Qingwei Lin 林庆维, Mykola Pechenizkiy, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  ICLR’25 | April 2025
  
  Publication
- Serving Models, Fast and Slow:Optimizing Heterogeneous LLM Inferencing Workloads at Scale
  
  Kunal Jain, A. Parayil, Ankur Mallick, Rujia Wang, Renee St. Amant, Chetan Bansal, Victor Ruehle, Saravan Rajmohan, Shashwat Jaiswal, Yogesh Simmhan, Anoop Kulkarni, Steve Kofsky
  
  ArXiv | February 2025
  
  Publication
- The Canary’s Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
  
  Matthieu Meeus, Lukas Wutschitz, Santiago Zanella-Béguelin, Reza Shokri, Shruti Tople
  
  February 2025
  
  DOI Preprint Project
- MEETING DELEGATE: Benchmarking LLMs on Attending Meetings on Our Behalf
  
  Lingxiang Hu, Shurun Yuan, Xiaoting Qin, Jue Zhang, Qingwei Lin 林庆维, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  February 2025
  
  Publication
- Towards Efficient Large Multimodal Model Serving
  
  Haoran Qiu, Anish Biswas, Zihan Zhao, Jayashree Mohan, Alind Khare, Esha Choukse, Íñigo Goiri, Zeyu Zhang, Haiying Shen, Chetan Bansal, Ramachandran Ramjee, Rodrigo Fonseca
  
  February 2025
  
  Preprint Project Project
- Triangle: Empowering Incident Triage with Multi-Agent
  
  Zhaoyang Yu, Aoyang Fang, Minghua Ma, Chaoyun Zhang, Ze Li, Murali Chintalapati, Xuchao Zhang, Rujia Wang, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, et.al
  
  ASE’25 | November 2025
  
  Publication
- Enabling Autonomic Microservice Management through Self-Learning Agents
  
  Fenglin Yu, Fangkai Yang, Xiaoting Qin, Zhiyang Zhang, Jue Zhang, Qingwei Lin 林庆维, Hongyu Zhang, Yingnong Dang, Saravan Rajmohan, Dongmei Zhang, Qi Zhang
  
  January 2025
  
  Preprint
- TurboAttention: Efficient Attention Approximation For High Throughputs LLMs
  
  Hao Kang, Srikant Bharadwaj, James Hensman, Tushar Krishna, Victor Ruehle, Saravan Rajmohan
  
  ArXiv | December 2024, Vol abs/2412.08585
  
  DOI Publication Publication
- Ensuring Fair LLM Serving Amid Diverse Applications
  
  Kunal Jain, Ankur Mallick, A. Parayil, Renee St. Amant, Rujia Wang, Victor Ruehle, Chetan Bansal, Saravan Rajmohan, Redwan Ibne Seraj Khan, Haiying Shen, Anoop Kulkarni, Steve Kofsky, Pankhuri Choudhary, Yue Cheng
  
  ArXiv | November 2024
  
  Publication
- Building AI Agents for Autonomous Clouds: Challenges and Design Principles
  
  Manisha M Shetty, Yinfang Chen, Gagan Somashekar, Minghua Ma, Yogesh L. Simmhan, Xuchao Zhang, Jonathan Mace, Pedro Las-Casas, Shachee Mishra Gupta, Suman Nath, Chetan Bansal, Saravan Rajmohan
  
  2024 Symposium on Cloud Computing | November 2024
  
  Publication
- AutoRAG-HP: Automatic Online Hyper-Parameter Tuning for Retrieval-Augmented Generation
  
  Jia Fu, Xiaoting Qin, Fangkai Yang, Lu Wang, Jue Zhang, Qingwei Lin 林庆维, Yubo Chen, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  EMNLP’24 | November 2024
  
  Preprint
- Hybrid-RACA: Hybrid Retrieval-Augmented Composition Assistance for Real-time Text Prediction
  
  Menglin Xia, Xuchao Zhang, Camille Couturier, Guoqing Zheng, Saravan Rajmohan, Victor Ruehle
  
  EMNLP 2024 Industry Track | November 2024
  
  Preprint
- Sharingan: Extract user action sequence from desktop recordings
  
  Yanting Chen, Yi Ren, Xiaoting Qin, Jue Zhang, Kehong Yuan, Lu Han, Qingwei Lin 林庆维, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  November 2024
  
  Preprint
- Can We Trust Auto-Mitigation? Improving Cloud Failure Prediction with Uncertain Positive Learning
  
  Haozhe Li, Minghua Ma, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  2024 International Symposium on Software Reliability Engineering | October 2024
  
  Publication
- COIN: Chance-Constrained Imitation Learning for Safe and Adaptive Resource Oversubscription under Uncertainty
  
  Lu Wang, Mayukh Das, Fangkai Yang, Chao Du, Bo Qiao, Hang Dong, Chetan Bansal, Si Qin, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang, Qi Zhang
  
  CIKM’24 | October 2024
  
  PDF
- Early Bird: Ensuring Reliability of Cloud Systems Through Early Failure Prediction
  
  Yudong Liu, Minghua Ma, Pu Zhao, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  2024 International Symposium on Software Reliability Engineering | October 2024
  
  Publication
- FLASH: A Workflow Automation Agent for Diagnosing Recurring Incidents
  
  Xuchao Zhang, Tanish Mittal, Chetan Bansal, Rujia Wang, Minghua Ma, Zhixin Ren, Hao Huang, Saravan Rajmohan
  
  October 2024
  
  Publication Project
- Navigating the Unknown: A Chat-Based Collaborative Interface for Personalized Exploratory Tasks
  
  Yingzhe Peng, Xiaoting Qin, Zhiyang Zhang, Jue Zhang, Qingwei Lin 林庆维, Xu Yang, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  IUI’25 | October 2024
  
  Publication
- AI Delegates with a Dual Focus: Ensuring Privacy and Strategic Self-Disclosure
  
  Xi Chen, Zhiyang Zhang, Fangkai Yang, Xiaoting Qin, Chao Du, Xi Cheng, Hangxin Liu, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang, Qi Zhang
  
  September 2024
  
  Preprint
- Intelligent Router for LLM Workloads: Improving Performance Through Workload-Aware Scheduling
  
  A. Parayil, Ankur Mallick, Esha Choukse, Xiaoting Qin, Jue Zhang, Íñigo Goiri, Rujia Wang, Chetan Bansal, Victor Ruehle, Saravan Rajmohan, Kunal Jain, Anoop Kulkarni, Steve Kofsky
  
  ArXiv | August 2024, Vol abs/2408.13510
  
  Preprint
- Large Language Models Can Provide Accurate and Interpretable Incident Triage
  
  Zexin Wang, Minghua Ma, Ze Li, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  2024 International Symposium on Software Reliability Engineering | August 2024
  
  Publication
- Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4
  
  Xuchao Zhang, Supriyo GHOSH, Chetan Bansal, Rujia Wang, Minghua Ma, Yu Kang, Saravan Rajmohan
  
  Foundations of Software Engineering (FSE) | July 2024
  
  Publication
- X-lifecycle Learning for Cloud Incident Management using LLMs
  
  Drishti Goel, Fiza Husain, Aditya Singh, Supriyo GHOSH, A. Parayil, Chetan Bansal, Xuchao Zhang, Saravan Rajmohan
  
  Foundations of Software Engineering (FSE) | July 2024
  
  Publication
- MonitorAssistant: Simplifying Cloud Service Monitoring via Large Language Models
  
  Zhaoyang Yu, Minghua Ma, Chaoyun Zhang, Si Qin, Yu Kang, Chetan Bansal, Saravan Rajmohan, Yingnong Dang, Changhua Pei, Dan Pei, Qingwei Lin 林庆维, Dongmei Zhang
  
  Foundations of Software Engineering (FSE) | July 2024
  
  DOI Publication
- Exploring LLM-based Agents for Root Cause Analysis
  
  Devjeet Roy, Xuchao Zhang, Rashi Bhave, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, Saravan Rajmohan
  
  FSE ’24: 32nd ACM International Conference on the Foundations of Software Engineering | July 2024
  
  Publication Project
- MonitorAssistant: Simplifying Cloud Service Monitoring via Large Language Models
  
  Zhaoyang Yu, Minghua Ma, Chaoyun Zhang, Si Qin, Yu Kang, Chetan Bansal, Saravan Rajmohan, Yingnong Dang, Changhua Pei, Dan Pei, Qingwei Lin 林庆维, Dongmei Zhang
  
  ESEC/FSE’24 Industry Track | July 2024
  
  Publication Publication
- The Vision of Autonomic Computing: Can LLMs Make It a Reality?
  
  Zhiyang Zhang, Fangkai Yang, Xiaoting Qin, Jue Zhang, Qingwei Lin 林庆维, Gong Cheng, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  July 2024
  
  Preprint
- CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models
  
  Peng Xia, Ze Chen, Juanxi Tian, Yangrui Gong, Ruibo Hou, Yue Xu, Zhenbang Wu, Zhiyuan Fan, Yiyang Zhou, Kangyu Zhu, Wenhao Zheng, Zhaoyang Wang, Xiao Wang, Xuchao Zhang, Chetan Bansal, Marc Niethammer, Junzhou Huang, Hongtu Zhu, Yun Li, Jimeng Sun, Zongyuan Ge, Gang Li, James Zou, Huaxiu Yao
  
  NeurIPS 2024 | June 2024
  
  DOI Publication Publication
- Designing Cloud Servers for Lower Carbon
  
  Jaylen Wang, Daniel S. Berger, Fiodar Kazhamiaka, Celine Irvene, Chaojie Zhang, Esha Choukse, Kali Frost, Rodrigo Fonseca, Brijesh Warrier, Chetan Bansal, Jonathan Stern, Ricardo Bianchini, Akshitha Sriraman
  
  ISCA | June 2024
  
  Publication
- SmartOClock: Workload- and Risk-Aware Overclocking in the Cloud
  
  Jovan Stojkovic, Pulkit Misra, Íñigo Goiri, Sam Whitlock, Esha Choukse, Mayukh Das, Chetan Bansal, Jason Lee, Zoey Sun, Haoran Qiu, Reed Zimmermann, Savyasachi Samal, Brijesh Warrier, Ashish Raniwala, Ricardo Bianchini
  
  ISCA | June 2024
  
  Publication
- LeanAttention: Hardware-Aware Scalable Attention Mechanism for the Decode-Phase of Transformers
  
  Rya Sanovar, Srikant Bharadwaj, Renee St. Amant, Victor Ruehle, Saravan Rajmohan
  
  May 2024
  
  Publication
- Dependency Aware Incident Linking in Large Cloud Systems
  
  Supriyo GHOSH, Karish Grover, Jimmy Wong, Chetan Bansal, Rakesh Namineni, Mohit Verma, Saravan Rajmohan
  
  The Web Conference (WWW) | May 2024
  
  Publication
- Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
  
  Xinyu Tang, Richard Shin, Huseyin Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Robert Sim
  
  ICLR 2024 | May 2024
  
  Publication Publication Github Projet
- Intelligent Overclocking for Improved Cloud Efficiency
  
  Aditya Soni, Mayukh Das, Pulkit Misra, Chetan Bansal
  
  AIOps ’24 workshop @ ASPLOS [5th International Workshop on Cloud Intelligence / AIOps] | April 2024
  
  Preprint
- Automatic Root Cause Analysis via Large Language Models for Cloud Incidents
  
  Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xue‐Chao Gao, Hao Fan, Ming Wen, Jun Zeng, Supriyo GHOSH, Xuchao Zhang, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang
  
  EuroSys’24 | April 2024
  
  Publication
- Intelligent Monitoring Framework for Cloud Services: A Data-Driven Approach
  
  Pooja Srinivas, Fiza Husain, A. Parayil, Ayush Choure, Chetan Bansal, Saravan Rajmohan
  
  46th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP’24) | April 2024
  
  Preprint
- OPPerTune: Post-Deployment Configuration Tuning of Services Made Easy
  
  Gagan Somashekar, Karan Tandon, Anush Kini, Chieh-Chun Chang, Petr Husak, Ranjita Bhagwan, Mayukh Das, Anshul Gandhi, Nagarajan Natarajan
  
  NSDI 2024 | April 2024
  
  Publication Publication Github Project Project
- Workload Intelligence: Punching Holes Through the Cloud Abstraction
  
  Lexiang Huang, A. Parayil, Jue Zhang, Xiaoting Qin, Chetan Bansal, Jovan Stojkovic, Pantea Zardoshti, Pulkit Misra, Eli Cortez, Raphael Ghelman, Íñigo Goiri, Saravan Rajmohan, Jim Kleewein, Rodrigo Fonseca, Timothy Zhu, Ricardo Bianchini
  
  ArXiv | April 2024, Vol abs/2404.19143
  
  Preprint
- Workload Intelligence: Punching Holes Through the Cloud Abstraction
  
  Lexiang Huang, A. Parayil, Jue Zhang, Xiaoting Qin, Chetan Bansal, Jovan Stojkovic, Pantea Zardoshti, Pulkit Misra, Eli Cortez, Raphael Ghelman, Íñigo Goiri, Saravan Rajmohan, Jim Kleewein, Rodrigo Fonseca, Timothy Zhu, Ricardo Bianchini
  
  April 2024
  
  Preprint
- Predict; Don’t React for Enabling Efficient Fine-Grain DVFS in GPUs
  
  Srikant Bharadwaj, Shomit Das, K. Mazumdar, Bradford M. Beckmann, Stephen Kosonocky
  
  Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems | March 2024
  
  Publication DOI Publication
- LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
  
  Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, Menglin Xia, Xufang Luo, Jue Zhang, Qingwei Lin 林庆维, Victor Ruehle, Yuqing Yang, Chin-Yew Lin, H. Vicky Zhao, Lili Qiu, Dongmei Zhang
  
  The 62nd Annual Meeting of the Association for Computational Linguistics (Findings of ACL 2024) | March 2024
  
  Preprint Project
- Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing
  
  Dujian Ding, Ankur Mallick, Chi Wang, Robert Sim, Subhabrata Mukherjee, Victor Ruehle, Laks V. S. Lakshmanan, Ahmed Awadallah
  
  ICLR 2024 | February 2024
  
  Publication
- Revisiting VAE for Unsupervised Time Series Anomaly Detection: A Frequency Perspective
  
  Zexin Wang, Changhua Pei, Minghua Ma, Xin Wang, Zhihan Li, Dan Pei, Saravan Rajmohan, Dongmei Zhang, Qingwei Lin 林庆维, Haiming Zhang, Jianhui Li, Gaogang Xie
  
  TheWebConf’24 | February 2024
  
  DOI Publication
- Advancing differential privacy: where we are now and future directions for real-world deployment
  
  Rachel Cummings, Damien Desfontaines, David Evans, Roxana Geambasu, Yangsibo Huang, Matthew Jagielski, Peter Kairouz, Gautam Kamath, Sewoong Oh, Olga Ohrimenko, Nicolas Papernot, Ryan Rogers, Milan Shen, Shuang Song, Weijie Su, Andreas Terzis, Abhradeep Thakurta, Sergei Vassilvitskii, Yu-Xiang Wang, Li Xiong, Da Yu, Sergey Yekhanin, Huanyu Zhang, Wanrong Zhang
  
  Harvard Data Science Review | January 2024, Vol 6(1)
  
  Publication Project
- NASerEx: Optimizing Early Exits via AutoML for Scalable Efficient Inference in Big Image Streams
  
  Aakash Kapoor, Rajath Elias Soans, Soham Dixit, Pradeep NS, Brijraj Singh, Mayukh Das
  
  IEEE Big Data 2023 | December 2023
  
  Special session on Machine Learning on Big Data (MLBD)
  
  Publication
- Training Private and Efficient Language Models with Synthetic Data from LLMs
  
  Da Yu, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Janardhan (Jana) Kulkarni, Zinan Lin, Chulin Xie, Huishuai Zhang, Wanrong Zhang
  
  NeurIPS 2023 SoLaR Workshop | December 2023
  
  Publication Project
- Detection Is Better Than Cure: A Cloud Incidents Perspective
  
  A. Parayil, Supriyo GHOSH, Yu Kang, Minghua Ma, Chetan Bansal, Suman Nath, Jonathan Mace, Vaibhav Ganatra
  
  ESEC/FSE 2023: Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering | November 2023
  
  Publication
- Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation
  
  Ruomeng Ding, Chaoyun Zhang, Lu Wang, Yong Xu, Minghua Ma, Wei Zhang, Si Qin, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  ArXiv | November 2023, Vol abs/2311.04254
  
  DOI Publication Publication
- Sweeping Heterogeneity with Smart MoPs: Mixture of Prompts for LLM Task Adaptation
  
  Chen Dun, Mirian Hipolito Garcia, Guoqing Zheng, Ahmed Awadallah, Anastasios Kyrillidis, Robert Sim
  
  ArXiv | October 2023, Vol abs/2310.02842
  
  DOI Publication Publication Publication
- PACE-LM: Prompting and Augmentation for Calibrated Confidence Estimation with GPT-4 in Cloud Incident Root Cause Analysis
  
  Dylan Zhang, Xuchao Zhang, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, Saravan Rajmohan
  
  September 2023
  
  Publication
- Secure Floating-Point Training
  
  Deevashwer Rathee, Anwesh Bhattacharya, Divya Gupta, Rahul Sharma, Dawn Song
  
  Usenix Security Symposium 2023 | August 2023
  
  Publication Project
- Project Florida: Federated Learning Made Easy
  
  Daniel Madrigal, Andre Manoel, Jialei Chen, Nalin Singal, Robert Sim
  
  | July 2023
  
  Published by Microsoft
  
  Publication Project
- Bayesian Estimation of Differential Privacy
  
  Santiago Zanella-Béguelin, Lukas Wutschitz, Shruti Tople, Ahmed Salem, Victor Ruehle, Andrew Paverd, Mohammad Naseri, Boris Köpf, Daniel Jones
  
  2023 International Conference on Machine Learning | July 2023
  
  Editor(s): Barbara Engelhardt, Emma Brunskill, Kyunghyun Cho
  
  Publication Project
- How Different are the Cloud Workloads? Characterizing Large-Scale Private and Public Cloud Workloads
  
  Xiaoting Qin, Minghua Ma, Yueng Zhao, Jue Zhang, Chao Du, Yudong Liu, A. Parayil, Chetan Bansal, Saravan Rajmohan, Íñigo Goiri, Eli Cortez, Si Qin, Qingwei Lin 林庆维, Dongmei Zhang
  
  DSN’23 | June 2023
  
  Publication
- Analyzing Leakage of Personally Identifiable Information in Language Models
  
  Nils Lukas, Ahmed Salem, Robert Sim, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin
  
  2023 IEEE Symposium on Security and Privacy | May 2023
  
  Publication PDF DOI Project
- Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
  
  Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan (Jana) Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian
  
  International Conference on Learning Representations (ICLR) 2023 | May 2023
  
  Publication Projet
- Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models
  
  Toufique Ahmed, Supriyo GHOSH, Chetan Bansal, Tom Zimmermann, Xuchao Zhang, Saravan Rajmohan
  
  ICSE 2023 | May 2023
  
  Publication
- SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning
  
  Ahmed Salem, Giovanni Cherubin, David Evans, Boris Köpf, Andrew Paverd, Anshuman Suri, Shruti Tople, Santiago Zanella-Béguelin
  
  2023 IEEE Symposium on Security and Privacy | May 2023
  
  Publication PDF DOI Project
- Snape: Reliable and Low-Cost Computing with Mixture of Spot and On-Demand VMs
  
  Fangkai Yang, Lu Wang, Zhenyu Xu, Jue Zhang, Liqun Li, Bo Qiao, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Terry Yang, Victor Ruehle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  ASPLOS’23 | March 2023
  
  Publication
- Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler
  
  Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Rouqi Shen, Kevin Tian
  
  COLT 2023 | February 2023
  
  Publication Project
- Differentially Private Model Compression
  
  Fatemehsadat Mireshghallah, Arturs Backurs, Huseyin Inan, Lukas Wutschitz, Janardhan (Jana) Kulkarni
  
  NeurIPS 2022 | November 2022
  
  Publication Project
- When does differentially private learning not suffer in high dimensions?
  
  Xuechen Li, Daogao Liu, Tatsunori Hashimoto, Huseyin Inan, Janardhan (Jana) Kulkarni, Yin Tat Lee, Abhradeep Guha Thakurta
  
  NeurIPS’22 | November 2022
  
  Publication Projet
- AutoTSG: Learning and Synthesis for Incident Troubleshooting
  
  Manish Shetty, Chetan Bansal, Sai Pramod Upadhyayula, Arjun Radhakrishna, Anurag Gupta
  
  ESEC/FSE 2022 | November 2022
  
  Publication Publication Publication
- Membership Inference Attacks and Generalization: A Causal Perspective
  
  Teodora Baluta, Shiqi Shen, S. Hitarth, Shruti Tople, Prateek Saxena
  
  Computer and Communications Security (CCS) | November 2022
  
  Publication Projet
- How to Fight Production Incidents? An Empirical Study on a Large-scale Cloud Service
  
  Supriyo GHOSH, Manish Shetty, Chetan Bansal, Suman Nath
  
  SoCC 2022 | November 2022
  
  Best Paper Award
  
  Publication PDF Project
- Multi-task Hierarchical Classification for Disk Failure Prediction in Online Service Systems
  
  Yudong Liu, Hailan Yang, Pu Zhao, Minghua Ma, Chengwu Wen, Hongyu Zhang, Chuan Luo, Qingwei Lin 林庆维, Chang Yi, Jiaojian Wang, Chenjian Zhang, Paul Wang, Yingnong Dang, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD 2022 | August 2022
  
  DOI Publication Project Project
- AutoCoMet: Smart Neural Architecture Search via Co-Regulated Shaping Reinforcement
  
  Mayukh Das, Brijraj Singh, Harsh Kanti Chheda, Pawan Sharma, Pradeep NS
  
  ICPR | August 2022
  
  Publication
- Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning
  
  Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, Dimitrios Dimitriadis
  
  IJCAI-ECAI’22 | August 2022
  
  Publication Projet
- NENYA: Cascade Reinforcement Learning for Cost-Aware Failure Mitigation at Microsoft 365
  
  Lu Wang, Pu Zhao, Chao Du, Chuan Luo, Mengna Su, Fangkai Yang, Yudong Liu, Qingwei Lin 林庆维, Min Wang, Yingnong Dang, Hongyu Zhang, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD 2022 | August 2022
  
  Publication Project Project
- SIMC: ML Inference Secure Against Malicious Clients at Semi-Honest Cost
  
  Nishanth Chandran, Divya Gupta, Sai Lakshmi Bhavana Obbattu, Akash Shah
  
  USENIX Security | August 2022
  
  USENIX Security 2022
  
  Publication Project
- Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach
  
  Jie Yan, Yunlei Lu, Liting Chen, Si Qin, Yixin Fang, Qingwei Lin 林庆维, Thomas Moscibroda, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD’22 | August 2022
  
  Publication Project Project
- dp-transformers: Training transformer models with differential privacy
  
  Huseyin Inan, Andre Manoel, Lukas Wutschitz
  
  July 2022
  
  Publication Project
- UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis
  
  Fatemehsadat Mireshghallah, Vaishnavi Shrivastava, Milad Shokouhi, Taylor Berg-Kirkpatrick, Robert Sim, Dimitrios Dimitriadis
  
  2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL’22) | July 2022
  
  Publication Project
- Private Convex Optimization in General Norms
  
  Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Rouqi Shen, Kevin Tian
  
  SODA 2023 | July 2022
  
  Publication Projet
- Circuit-PSI with Linear Complexity via Relaxed Batch OPPRF
  
  Nishanth Chandran, Divya Gupta, Akash Shah
  
  22nd Privacy Enhancing Technologies Symposium (PETS 2022) | June 2022
  
  Publication Project
- Personalized Federated Learning with Adaptive Batchnorm for Healthcare
  
  Wang Lu, Jindong Wang, Yiqiang Chen, Xin Qin, Renjun Xu, Dimitrios Dimitriadis, Tao Qin
  
  IEEE Transactions on Big Data | May 2022
  
  Preprint Publication Projet
- DeepAnalyze: Learning to Localize Crashes at Scale
  
  Manish Shetty, Chetan Bansal, Suman Nath, Sean Bowles, Henry Wang, Ozgur Arman, Siamak Ahari
  
  ICSE 2022 | May 2022
  
  Publication Project
- SECFLOAT: Accurate Floating-Point meets Secure 2-Party Computation
  
  Deevashwer Rathee, Anwesh Bhattacharya, Rahul Sharma, Divya Gupta, Nishanth Chandran, Aseem Rastogi
  
  43rd IEEE Symposium on Security and Privacy (IEEE S&P 2022) | May 2022
  
  Publication Project
- Differentially private fine-tuning of language models
  
  Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Gautam Kamath, Janardhan (Jana) Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang
  
  ICLR 2022 | April 2022
  
  Publication Projet
- SoftNER: Mining knowledge graphs from Cloud Incidents
  
  Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan
  
  Empirical Software Engineering | April 2022, Vol 27(4)
  
  Publication
- Spot Virtual Machine Eviction Prediction in Microsoft Cloud
  
  Fangkai Yang, Bowen Pang, Jue Zhang, Bo Qiao, Lu Wang, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Senthil Baladhandayutham, Victor Rühle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  WWW’22 Companion | April 2022
  
  Publication
- FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations
  
  Dimitrios Dimitriadis, Mirian Hipolito Garcia, Daniel Madrigal, Andre Manoel, Robert Sim
  
  March 2022
  
  Preprint Github Project
- Private Convex Optimization via Exponential Mechanism
  
  Sivakanth Gopi, Yin Tat Lee, Daogao Liu
  
  COLT 2022 | March 2022
  
  Publication Project
- HALO: Hierarchy-aware Fault Localization for Cloud Systems
  
  Xu Zhang, Chao Du, Yifan Li, Yong Xu, Hongyu Zhang, Si Qin, Ze Li, Qingwei Lin 林庆维, Yingnong Dang, Andrew Zhou, Saravanakumar Rajmohan, Dongmei Zhang
  
  SigKDD’21 Applied Data Science Track | October 2021
  
  Publication PDF Projet Projet
- How Long Will it Take to Mitigate this Incident for Online Service Systems?
  
  Weijing Wang, Junjie Chen, Lin Yang, Hongyu Zhang, Pu Zhao, Bo Qiao, Yu Kang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Feng Gao, Zhangwei Xu, Yingnong Dang, Dongmei Zhang
  
  ISSRE’21 | September 2021
  
  Best Research Paper
  
  Publication Projet Projet
- Intelligent container reallocation at Microsoft 365
  
  Bo Qiao, Fangkai Yang, Chuan Luo, Yanan Wang, Johnny Li, Qingwei Lin 林庆维, Hongyu Zhang, Mohit Datta, Andrew Zhou, Thomas Moscibroda, Saravanakumar Rajmohan, Dongmei Zhang
  
  2021 Foundations of Software Engineering | August 2021
  
  DOI Projet Projet
- Fighting the Fog of War: Automated Incident Detection for Cloud Systems
  
  Liqun Li, Xu Zhang, Xin Zhao, Hongyu Zhang, Yu Kang, Pu Zhao, Bo Qiao, Shilin He, Pochian Lee, Jeffrey Sun, Feng Gao, Li Yang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Zhangwei Xu, Dongmei Zhang
  
  2021 USENIX Annual Technical Conference (USENIX ATC’21) | August 2021
  
  Publication Project Project
- Neural Knowledge Extraction From Cloud Service Incidents
  
  Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan, Tom Zimmermann
  
  43rd International Conference on Software Engineering (ICSE ’21) – SEIP Track | May 2021
- Correlation-Aware Heuristic Search for Intelligent Virtual Machine Provisioning in Cloud Systems
  
  Chuan Luo, Bo Qiao, Wenqian Xing, Xin Chen, Pu Zhao, Chao Du, Randolph Yao, Hongyu Zhang, Wei Wu, Shaowei Cai, Saravanakumar Rajmohan, Qingwei Lin 林庆维
  
  AAAI’21 | March 2021
  
  Publication Projet Projet Projet
- PULNS: Positive-Unlabeled Learning with Effective Negative Sample Selector
  
  Chuan Luo, …, Qingwei Lin 林庆维
  
  AAAI’21 | March 2021
  
  Publication Projet
- NTAM: Neighborhood-Temporal Attention Model for Disk Failure Prediction in Cloud Platforms
  
  Chuan Luo, Pu Zhao, …, Qingwei Lin 林庆维, …
  
  WWW (TheWebConf) 2021 | February 2021
  
  Publication Project Project Project
- DeCaf: Diagnosing and Triaging Performance Issues in Large-Scale Cloud Services
  
  Chetan Bansal, Sundararajan Renganathan, Ashima Asudani, Olivier Midy, Mathru Janakiraman
  
  ICSE 2020 | May 2020
  
  PDF Project
- Rex: Preventing Bugs and Misconfiguration in Large Services using Correlated Change Analysis
  
  Sonu Mehta, Ranjita Bhagwan, Rahul Kumar, B. Ashok, Chetan Bansal, Chandra Maddila, Christian Bird, Sumit Asthana, Aditya Kumar
  
  Networked System Design and Implementation (NSDI) | February 2020
  
  Publication Project
- WhoDo: Automating Reviewer Suggestions at Scale
  
  Sumit Asthana, Rahul Kumar, Ranjita Bhagwan, Chetan Bansal, Christian Bird, Chandra Maddila, Sonu Mehta, B. Ashok
  
  ESEC/FSE 2019 | August 2019
  
  Publication Projet
- Predicting Pull Request Completion Time: A Case Study on Large Scale Cloud Services
  
  Chandra Maddila, Chetan Bansal, Nachi Nagappan
  
  ESEC/FSE 2019 | August 2019
  
  Publication Project
- Building sankie: an AI platform for DevOps
  
  Rahul Kumar, Chetan Bansal, Chandra Maddila, Nitin Sharma, Shawn Martelock, Ravi Bhargava
  
  1st International Workshop on Bots in Software Engineering (BotSE ’19) | May 2019
  
  Publication Project
- FastLane: Test Minimization for Rapidly Deployed Large-scale Online Services
  
  Ranjita Bhagwan, Adithya Philip, Rahul Kumar, Chandra Maddila, Nachi Nagappan
  
  International Conference on Software Engineering | May 2019
  
  Publication Project
- EzPC: Programmable, Efficient, and Scalable Secure Two-Party Computation for Machine Learning
  
  Nishanth Chandran, Divya Gupta, Aseem Rastogi, Rahul Sharma, Shardul Tripathi
  
  IEEE European Symposium on Security and Privacy | February 2019
  
  Publication Vidéo Github Projet
- Orca: Differential Bug Localization in Large-Scale Services
  
  Ranjita Bhagwan, Rahul Kumar, Chandra Maddila, Adithya Abraham Philip
  
  13th USENIX Symposium on Operating Systems Design and Implementation | October 2018
  
  Won the Jay Lepreau Best Paper Award
  
  Publication Projet

- RuAG: Learned-rule-augmented Generation for Large Language Models
  
  Yudi Zhang, Pei Xiao, Lu Wang, Chaoyun Zhang, Meng Fang, Yali Du, Yevgeniy Puzyrev, Randolph Yao, Si Qin, Qingwei Lin 林庆维, Mykola Pechenizkiy, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  ICLR’25 | April 2025
  
  Publication
- Can We Trust Auto-Mitigation? Improving Cloud Failure Prediction with Uncertain Positive Learning
  
  Haozhe Li, Minghua Ma, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  2024 International Symposium on Software Reliability Engineering | October 2024
  
  Publication
- Early Bird: Ensuring Reliability of Cloud Systems Through Early Failure Prediction
  
  Yudong Liu, Minghua Ma, Pu Zhao, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  2024 International Symposium on Software Reliability Engineering | October 2024
  
  Publication
- Exploring LLM-based Agents for Root Cause Analysis
  
  Devjeet Roy, Xuchao Zhang, Rashi Bhave, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, Saravan Rajmohan
  
  FSE ’24: 32nd ACM International Conference on the Foundations of Software Engineering | July 2024
  
  Publication Project
- Automatic Root Cause Analysis via Large Language Models for Cloud Incidents
  
  Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xue‐Chao Gao, Hao Fan, Ming Wen, Jun Zeng, Supriyo GHOSH, Xuchao Zhang, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang
  
  EuroSys’24 | April 2024
  
  Publication
- OPPerTune: Post-Deployment Configuration Tuning of Services Made Easy
  
  Gagan Somashekar, Karan Tandon, Anush Kini, Chieh-Chun Chang, Petr Husak, Ranjita Bhagwan, Mayukh Das, Anshul Gandhi, Nagarajan Natarajan
  
  NSDI 2024 | April 2024
  
  Publication Publication Github Project Project
- Revisiting VAE for Unsupervised Time Series Anomaly Detection: A Frequency Perspective
  
  Zexin Wang, Changhua Pei, Minghua Ma, Xin Wang, Zhihan Li, Dan Pei, Saravan Rajmohan, Dongmei Zhang, Qingwei Lin 林庆维, Haiming Zhang, Jianhui Li, Gaogang Xie
  
  TheWebConf’24 | February 2024
  
  DOI Publication
- NASerEx: Optimizing Early Exits via AutoML for Scalable Efficient Inference in Big Image Streams
  
  Aakash Kapoor, Rajath Elias Soans, Soham Dixit, Pradeep NS, Brijraj Singh, Mayukh Das
  
  IEEE Big Data 2023 | December 2023
  
  Special session on Machine Learning on Big Data (MLBD)
  
  Publication
- Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler
  
  Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Rouqi Shen, Kevin Tian
  
  COLT 2023 | February 2023
  
  Publication Project
- Differentially Private Model Compression
  
  Fatemehsadat Mireshghallah, Arturs Backurs, Huseyin Inan, Lukas Wutschitz, Janardhan (Jana) Kulkarni
  
  NeurIPS 2022 | November 2022
  
  Publication Project
- When does differentially private learning not suffer in high dimensions?
  
  Xuechen Li, Daogao Liu, Tatsunori Hashimoto, Huseyin Inan, Janardhan (Jana) Kulkarni, Yin Tat Lee, Abhradeep Guha Thakurta
  
  NeurIPS’22 | November 2022
  
  Publication Projet
- Multi-task Hierarchical Classification for Disk Failure Prediction in Online Service Systems
  
  Yudong Liu, Hailan Yang, Pu Zhao, Minghua Ma, Chengwu Wen, Hongyu Zhang, Chuan Luo, Qingwei Lin 林庆维, Chang Yi, Jiaojian Wang, Chenjian Zhang, Paul Wang, Yingnong Dang, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD 2022 | August 2022
  
  DOI Publication Project Project
- Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach
  
  Jie Yan, Yunlei Lu, Liting Chen, Si Qin, Yixin Fang, Qingwei Lin 林庆维, Thomas Moscibroda, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD’22 | August 2022
  
  Publication Project Project
- NENYA: Cascade Reinforcement Learning for Cost-Aware Failure Mitigation at Microsoft 365
  
  Lu Wang, Pu Zhao, Chao Du, Chuan Luo, Mengna Su, Fangkai Yang, Yudong Liu, Qingwei Lin 林庆维, Min Wang, Yingnong Dang, Hongyu Zhang, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD 2022 | August 2022
  
  Publication Project Project
- Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning
  
  Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, Dimitrios Dimitriadis
  
  IJCAI-ECAI’22 | August 2022
  
  Publication Projet
- Private Convex Optimization in General Norms
  
  Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Rouqi Shen, Kevin Tian
  
  SODA 2023 | July 2022
  
  Publication Projet
- Spot Virtual Machine Eviction Prediction in Microsoft Cloud
  
  Fangkai Yang, Bowen Pang, Jue Zhang, Bo Qiao, Lu Wang, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Senthil Baladhandayutham, Victor Rühle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  WWW’22 Companion | April 2022
  
  Publication
- Differentially private fine-tuning of language models
  
  Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Gautam Kamath, Janardhan (Jana) Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang
  
  ICLR 2022 | April 2022
  
  Publication Projet
- Private Convex Optimization via Exponential Mechanism
  
  Sivakanth Gopi, Yin Tat Lee, Daogao Liu
  
  COLT 2022 | March 2022
  
  Publication Project
- HALO: Hierarchy-aware Fault Localization for Cloud Systems
  
  Xu Zhang, Chao Du, Yifan Li, Yong Xu, Hongyu Zhang, Si Qin, Ze Li, Qingwei Lin 林庆维, Yingnong Dang, Andrew Zhou, Saravanakumar Rajmohan, Dongmei Zhang
  
  SigKDD’21 Applied Data Science Track | October 2021
  
  Publication PDF Projet Projet
- How Long Will it Take to Mitigate this Incident for Online Service Systems?
  
  Weijing Wang, Junjie Chen, Lin Yang, Hongyu Zhang, Pu Zhao, Bo Qiao, Yu Kang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Feng Gao, Zhangwei Xu, Yingnong Dang, Dongmei Zhang
  
  ISSRE’21 | September 2021
  
  Best Research Paper
  
  Publication Projet Projet
- Fighting the Fog of War: Automated Incident Detection for Cloud Systems
  
  Liqun Li, Xu Zhang, Xin Zhao, Hongyu Zhang, Yu Kang, Pu Zhao, Bo Qiao, Shilin He, Pochian Lee, Jeffrey Sun, Feng Gao, Li Yang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Zhangwei Xu, Dongmei Zhang
  
  2021 USENIX Annual Technical Conference (USENIX ATC’21) | August 2021
  
  Publication Project Project
- Correlation-Aware Heuristic Search for Intelligent Virtual Machine Provisioning in Cloud Systems
  
  Chuan Luo, Bo Qiao, Wenqian Xing, Xin Chen, Pu Zhao, Chao Du, Randolph Yao, Hongyu Zhang, Wei Wu, Shaowei Cai, Saravanakumar Rajmohan, Qingwei Lin 林庆维
  
  AAAI’21 | March 2021
  
  Publication Projet Projet Projet
- PULNS: Positive-Unlabeled Learning with Effective Negative Sample Selector
  
  Chuan Luo, …, Qingwei Lin 林庆维
  
  AAAI’21 | March 2021
  
  Publication Projet
- NTAM: Neighborhood-Temporal Attention Model for Disk Failure Prediction in Cloud Platforms
  
  Chuan Luo, Pu Zhao, …, Qingwei Lin 林庆维, …
  
  WWW (TheWebConf) 2021 | February 2021
  
  Publication Project Project Project
- Reason-before-Retrieve: One-Stage Reflective Chain-of-Thoughts for Training-Free Zero-Shot Composed Image Retrieval
  
  Yuanmin Tang, Xiaoting Qin, Jue Zhang, Jing Yu, Gaopeng Gou, Gang Xiong, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang, Qi Wu
  
  CVPR’25 | June 2025
  
  Preprint
- ProtoRAIL: A Risk-cognizant Imitation Agent for Adaptive vCPU Oversubscription In The Cloud
  
  Lu Wang, Mayukh Das, Fangkai Yang, Bo Qiao, Hang Dong, Si Qin, Victor Ruehle, Chetan Bansal, Eli Cortez, Íñigo Goiri, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  MLSys’25 | May 2025
  
  Publication
- AIOpsLab: A Holistic Framework for Evaluating AI Agents for Enabling Autonomous Cloud
  
  Yinfang Chen, Manish Shetty, Gagan Somashekar, Minghua Ma, Yogesh Simmhan, Jonathan Mace, Chetan Bansal, Rujia Wang, Saravan Rajmohan
  
  MLSys ’25 | May 2025
  
  Publication
- Towards Cloud Efficiency with Large-scale Workload Characterization
  
  A. Parayil, Jue Zhang, Xiaoting Qin, Íñigo Goiri, Chetan Bansal
  
  ICPE | May 2025
  
  Preprint
- RuAG: Learned-rule-augmented Generation for Large Language Models
  
  Yudi Zhang, Pei Xiao, Lu Wang, Chaoyun Zhang, Meng Fang, Yali Du, Yevgeniy Puzyrev, Randolph Yao, Si Qin, Qingwei Lin 林庆维, Mykola Pechenizkiy, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  ICLR’25 | April 2025
  
  Publication
- Performance Aware LLM Load Balancer for Mixed Workloads
  
  Kunal Jain, A. Parayil, Ankur Mallick, Esha Choukse, Xiaoting Qin, Jue Zhang, Íñigo Goiri, Rujia Wang, Chetan Bansal, Victor Ruehle, Anoop Kulkarni, Steve Kofsky, Saravan Rajmohan
  
  EuroMLSys 2025 | April 2025
  
  Publication Project
- Serving Models, Fast and Slow:Optimizing Heterogeneous LLM Inferencing Workloads at Scale
  
  Kunal Jain, A. Parayil, Ankur Mallick, Rujia Wang, Renee St. Amant, Chetan Bansal, Victor Ruehle, Saravan Rajmohan, Shashwat Jaiswal, Yogesh Simmhan, Anoop Kulkarni, Steve Kofsky
  
  ArXiv | February 2025
  
  Publication
- The Canary’s Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
  
  Matthieu Meeus, Lukas Wutschitz, Santiago Zanella-Béguelin, Reza Shokri, Shruti Tople
  
  February 2025
  
  DOI Preprint Project
- MEETING DELEGATE: Benchmarking LLMs on Attending Meetings on Our Behalf
  
  Lingxiang Hu, Shurun Yuan, Xiaoting Qin, Jue Zhang, Qingwei Lin 林庆维, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  February 2025
  
  Publication
- Towards Efficient Large Multimodal Model Serving
  
  Haoran Qiu, Anish Biswas, Zihan Zhao, Jayashree Mohan, Alind Khare, Esha Choukse, Íñigo Goiri, Zeyu Zhang, Haiying Shen, Chetan Bansal, Ramachandran Ramjee, Rodrigo Fonseca
  
  February 2025
  
  Preprint Project Project
- Enabling Autonomic Microservice Management through Self-Learning Agents
  
  Fenglin Yu, Fangkai Yang, Xiaoting Qin, Zhiyang Zhang, Jue Zhang, Qingwei Lin 林庆维, Hongyu Zhang, Yingnong Dang, Saravan Rajmohan, Dongmei Zhang, Qi Zhang
  
  January 2025
  
  Preprint
- TurboAttention: Efficient Attention Approximation For High Throughputs LLMs
  
  Hao Kang, Srikant Bharadwaj, James Hensman, Tushar Krishna, Victor Ruehle, Saravan Rajmohan
  
  ArXiv | December 2024, Vol abs/2412.08585
  
  DOI Publication Publication
- Ensuring Fair LLM Serving Amid Diverse Applications
  
  Kunal Jain, Ankur Mallick, A. Parayil, Renee St. Amant, Rujia Wang, Victor Ruehle, Chetan Bansal, Saravan Rajmohan, Redwan Ibne Seraj Khan, Haiying Shen, Anoop Kulkarni, Steve Kofsky, Pankhuri Choudhary, Yue Cheng
  
  ArXiv | November 2024
  
  Publication
- Building AI Agents for Autonomous Clouds: Challenges and Design Principles
  
  Manisha M Shetty, Yinfang Chen, Gagan Somashekar, Minghua Ma, Yogesh L. Simmhan, Xuchao Zhang, Jonathan Mace, Pedro Las-Casas, Shachee Mishra Gupta, Suman Nath, Chetan Bansal, Saravan Rajmohan
  
  2024 Symposium on Cloud Computing | November 2024
  
  Publication
- Sharingan: Extract user action sequence from desktop recordings
  
  Yanting Chen, Yi Ren, Xiaoting Qin, Jue Zhang, Kehong Yuan, Lu Han, Qingwei Lin 林庆维, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  November 2024
  
  Preprint
- AutoRAG-HP: Automatic Online Hyper-Parameter Tuning for Retrieval-Augmented Generation
  
  Jia Fu, Xiaoting Qin, Fangkai Yang, Lu Wang, Jue Zhang, Qingwei Lin 林庆维, Yubo Chen, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  EMNLP’24 | November 2024
  
  Preprint
- Hybrid-RACA: Hybrid Retrieval-Augmented Composition Assistance for Real-time Text Prediction
  
  Menglin Xia, Xuchao Zhang, Camille Couturier, Guoqing Zheng, Saravan Rajmohan, Victor Ruehle
  
  EMNLP 2024 Industry Track | November 2024
  
  Preprint
- Navigating the Unknown: A Chat-Based Collaborative Interface for Personalized Exploratory Tasks
  
  Yingzhe Peng, Xiaoting Qin, Zhiyang Zhang, Jue Zhang, Qingwei Lin 林庆维, Xu Yang, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  IUI’25 | October 2024
  
  Publication
- FLASH: A Workflow Automation Agent for Diagnosing Recurring Incidents
  
  Xuchao Zhang, Tanish Mittal, Chetan Bansal, Rujia Wang, Minghua Ma, Zhixin Ren, Hao Huang, Saravan Rajmohan
  
  October 2024
  
  Publication Project
- COIN: Chance-Constrained Imitation Learning for Safe and Adaptive Resource Oversubscription under Uncertainty
  
  Lu Wang, Mayukh Das, Fangkai Yang, Chao Du, Bo Qiao, Hang Dong, Chetan Bansal, Si Qin, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang, Qi Zhang
  
  CIKM’24 | October 2024
  
  PDF
- AI Delegates with a Dual Focus: Ensuring Privacy and Strategic Self-Disclosure
  
  Xi Chen, Zhiyang Zhang, Fangkai Yang, Xiaoting Qin, Chao Du, Xi Cheng, Hangxin Liu, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang, Qi Zhang
  
  September 2024
  
  Preprint
- Intelligent Router for LLM Workloads: Improving Performance Through Workload-Aware Scheduling
  
  A. Parayil, Ankur Mallick, Esha Choukse, Xiaoting Qin, Jue Zhang, Íñigo Goiri, Rujia Wang, Chetan Bansal, Victor Ruehle, Saravan Rajmohan, Kunal Jain, Anoop Kulkarni, Steve Kofsky
  
  ArXiv | August 2024, Vol abs/2408.13510
  
  Preprint
- Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4
  
  Xuchao Zhang, Supriyo GHOSH, Chetan Bansal, Rujia Wang, Minghua Ma, Yu Kang, Saravan Rajmohan
  
  Foundations of Software Engineering (FSE) | July 2024
  
  Publication
- X-lifecycle Learning for Cloud Incident Management using LLMs
  
  Drishti Goel, Fiza Husain, Aditya Singh, Supriyo GHOSH, A. Parayil, Chetan Bansal, Xuchao Zhang, Saravan Rajmohan
  
  Foundations of Software Engineering (FSE) | July 2024
  
  Publication
- MonitorAssistant: Simplifying Cloud Service Monitoring via Large Language Models
  
  Zhaoyang Yu, Minghua Ma, Chaoyun Zhang, Si Qin, Yu Kang, Chetan Bansal, Saravan Rajmohan, Yingnong Dang, Changhua Pei, Dan Pei, Qingwei Lin 林庆维, Dongmei Zhang
  
  Foundations of Software Engineering (FSE) | July 2024
  
  DOI Publication
- MonitorAssistant: Simplifying Cloud Service Monitoring via Large Language Models
  
  Zhaoyang Yu, Minghua Ma, Chaoyun Zhang, Si Qin, Yu Kang, Chetan Bansal, Saravan Rajmohan, Yingnong Dang, Changhua Pei, Dan Pei, Qingwei Lin 林庆维, Dongmei Zhang
  
  ESEC/FSE’24 Industry Track | July 2024
  
  Publication Publication
- Exploring LLM-based Agents for Root Cause Analysis
  
  Devjeet Roy, Xuchao Zhang, Rashi Bhave, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, Saravan Rajmohan
  
  FSE ’24: 32nd ACM International Conference on the Foundations of Software Engineering | July 2024
  
  Publication Project
- The Vision of Autonomic Computing: Can LLMs Make It a Reality?
  
  Zhiyang Zhang, Fangkai Yang, Xiaoting Qin, Jue Zhang, Qingwei Lin 林庆维, Gong Cheng, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  July 2024
  
  Preprint
- CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models
  
  Peng Xia, Ze Chen, Juanxi Tian, Yangrui Gong, Ruibo Hou, Yue Xu, Zhenbang Wu, Zhiyuan Fan, Yiyang Zhou, Kangyu Zhu, Wenhao Zheng, Zhaoyang Wang, Xiao Wang, Xuchao Zhang, Chetan Bansal, Marc Niethammer, Junzhou Huang, Hongtu Zhu, Yun Li, Jimeng Sun, Zongyuan Ge, Gang Li, James Zou, Huaxiu Yao
  
  NeurIPS 2024 | June 2024
  
  DOI Publication Publication
- LeanAttention: Hardware-Aware Scalable Attention Mechanism for the Decode-Phase of Transformers
  
  Rya Sanovar, Srikant Bharadwaj, Renee St. Amant, Victor Ruehle, Saravan Rajmohan
  
  May 2024
  
  Publication
- Dependency Aware Incident Linking in Large Cloud Systems
  
  Supriyo GHOSH, Karish Grover, Jimmy Wong, Chetan Bansal, Rakesh Namineni, Mohit Verma, Saravan Rajmohan
  
  The Web Conference (WWW) | May 2024
  
  Publication
- Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
  
  Xinyu Tang, Richard Shin, Huseyin Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Robert Sim
  
  ICLR 2024 | May 2024
  
  Publication Publication Github Projet
- Intelligent Overclocking for Improved Cloud Efficiency
  
  Aditya Soni, Mayukh Das, Pulkit Misra, Chetan Bansal
  
  AIOps ’24 workshop @ ASPLOS [5th International Workshop on Cloud Intelligence / AIOps] | April 2024
  
  Preprint
- Automatic Root Cause Analysis via Large Language Models for Cloud Incidents
  
  Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xue‐Chao Gao, Hao Fan, Ming Wen, Jun Zeng, Supriyo GHOSH, Xuchao Zhang, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang
  
  EuroSys’24 | April 2024
  
  Publication
- Intelligent Monitoring Framework for Cloud Services: A Data-Driven Approach
  
  Pooja Srinivas, Fiza Husain, A. Parayil, Ayush Choure, Chetan Bansal, Saravan Rajmohan
  
  46th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP’24) | April 2024
  
  Preprint
- Workload Intelligence: Punching Holes Through the Cloud Abstraction
  
  Lexiang Huang, A. Parayil, Jue Zhang, Xiaoting Qin, Chetan Bansal, Jovan Stojkovic, Pantea Zardoshti, Pulkit Misra, Eli Cortez, Raphael Ghelman, Íñigo Goiri, Saravan Rajmohan, Jim Kleewein, Rodrigo Fonseca, Timothy Zhu, Ricardo Bianchini
  
  April 2024
  
  Preprint
- LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
  
  Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, Menglin Xia, Xufang Luo, Jue Zhang, Qingwei Lin 林庆维, Victor Ruehle, Yuqing Yang, Chin-Yew Lin, H. Vicky Zhao, Lili Qiu, Dongmei Zhang
  
  The 62nd Annual Meeting of the Association for Computational Linguistics (Findings of ACL 2024) | March 2024
  
  Preprint Project
- Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing
  
  Dujian Ding, Ankur Mallick, Chi Wang, Robert Sim, Subhabrata Mukherjee, Victor Ruehle, Laks V. S. Lakshmanan, Ahmed Awadallah
  
  ICLR 2024 | February 2024
  
  Publication
- NASerEx: Optimizing Early Exits via AutoML for Scalable Efficient Inference in Big Image Streams
  
  Aakash Kapoor, Rajath Elias Soans, Soham Dixit, Pradeep NS, Brijraj Singh, Mayukh Das
  
  IEEE Big Data 2023 | December 2023
  
  Special session on Machine Learning on Big Data (MLBD)
  
  Publication
- Training Private and Efficient Language Models with Synthetic Data from LLMs
  
  Da Yu, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Janardhan (Jana) Kulkarni, Zinan Lin, Chulin Xie, Huishuai Zhang, Wanrong Zhang
  
  NeurIPS 2023 SoLaR Workshop | December 2023
  
  Publication Project
- Detection Is Better Than Cure: A Cloud Incidents Perspective
  
  A. Parayil, Supriyo GHOSH, Yu Kang, Minghua Ma, Chetan Bansal, Suman Nath, Jonathan Mace, Vaibhav Ganatra
  
  ESEC/FSE 2023: Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering | November 2023
  
  Publication
- Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation
  
  Ruomeng Ding, Chaoyun Zhang, Lu Wang, Yong Xu, Minghua Ma, Wei Zhang, Si Qin, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  ArXiv | November 2023, Vol abs/2311.04254
  
  DOI Publication Publication
- Sweeping Heterogeneity with Smart MoPs: Mixture of Prompts for LLM Task Adaptation
  
  Chen Dun, Mirian Hipolito Garcia, Guoqing Zheng, Ahmed Awadallah, Anastasios Kyrillidis, Robert Sim
  
  ArXiv | October 2023, Vol abs/2310.02842
  
  DOI Publication Publication Publication
- PACE-LM: Prompting and Augmentation for Calibrated Confidence Estimation with GPT-4 in Cloud Incident Root Cause Analysis
  
  Dylan Zhang, Xuchao Zhang, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, Saravan Rajmohan
  
  September 2023
  
  Publication
- Project Florida: Federated Learning Made Easy
  
  Daniel Madrigal, Andre Manoel, Jialei Chen, Nalin Singal, Robert Sim
  
  | July 2023
  
  Published by Microsoft
  
  Publication Project
- Bayesian Estimation of Differential Privacy
  
  Santiago Zanella-Béguelin, Lukas Wutschitz, Shruti Tople, Ahmed Salem, Victor Ruehle, Andrew Paverd, Mohammad Naseri, Boris Köpf, Daniel Jones
  
  2023 International Conference on Machine Learning | July 2023
  
  Editor(s): Barbara Engelhardt, Emma Brunskill, Kyunghyun Cho
  
  Publication Project
- Analyzing Leakage of Personally Identifiable Information in Language Models
  
  Nils Lukas, Ahmed Salem, Robert Sim, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin
  
  2023 IEEE Symposium on Security and Privacy | May 2023
  
  Publication PDF DOI Project
- SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning
  
  Ahmed Salem, Giovanni Cherubin, David Evans, Boris Köpf, Andrew Paverd, Anshuman Suri, Shruti Tople, Santiago Zanella-Béguelin
  
  2023 IEEE Symposium on Security and Privacy | May 2023
  
  Publication PDF DOI Project
- Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
  
  Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan (Jana) Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian
  
  International Conference on Learning Representations (ICLR) 2023 | May 2023
  
  Publication Projet
- Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models
  
  Toufique Ahmed, Supriyo GHOSH, Chetan Bansal, Tom Zimmermann, Xuchao Zhang, Saravan Rajmohan
  
  ICSE 2023 | May 2023
  
  Publication
- Differentially Private Model Compression
  
  Fatemehsadat Mireshghallah, Arturs Backurs, Huseyin Inan, Lukas Wutschitz, Janardhan (Jana) Kulkarni
  
  NeurIPS 2022 | November 2022
  
  Publication Project
- AutoTSG: Learning and Synthesis for Incident Troubleshooting
  
  Manish Shetty, Chetan Bansal, Sai Pramod Upadhyayula, Arjun Radhakrishna, Anurag Gupta
  
  ESEC/FSE 2022 | November 2022
  
  Publication Publication Publication
- Membership Inference Attacks and Generalization: A Causal Perspective
  
  Teodora Baluta, Shiqi Shen, S. Hitarth, Shruti Tople, Prateek Saxena
  
  Computer and Communications Security (CCS) | November 2022
  
  Publication Projet
- Multi-task Hierarchical Classification for Disk Failure Prediction in Online Service Systems
  
  Yudong Liu, Hailan Yang, Pu Zhao, Minghua Ma, Chengwu Wen, Hongyu Zhang, Chuan Luo, Qingwei Lin 林庆维, Chang Yi, Jiaojian Wang, Chenjian Zhang, Paul Wang, Yingnong Dang, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD 2022 | August 2022
  
  DOI Publication Project Project
- AutoCoMet: Smart Neural Architecture Search via Co-Regulated Shaping Reinforcement
  
  Mayukh Das, Brijraj Singh, Harsh Kanti Chheda, Pawan Sharma, Pradeep NS
  
  ICPR | August 2022
  
  Publication
- NENYA: Cascade Reinforcement Learning for Cost-Aware Failure Mitigation at Microsoft 365
  
  Lu Wang, Pu Zhao, Chao Du, Chuan Luo, Mengna Su, Fangkai Yang, Yudong Liu, Qingwei Lin 林庆维, Min Wang, Yingnong Dang, Hongyu Zhang, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD 2022 | August 2022
  
  Publication Project Project
- Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning
  
  Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, Dimitrios Dimitriadis
  
  IJCAI-ECAI’22 | August 2022
  
  Publication Projet
- dp-transformers: Training transformer models with differential privacy
  
  Huseyin Inan, Andre Manoel, Lukas Wutschitz
  
  July 2022
  
  Publication Project
- UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis
  
  Fatemehsadat Mireshghallah, Vaishnavi Shrivastava, Milad Shokouhi, Taylor Berg-Kirkpatrick, Robert Sim, Dimitrios Dimitriadis
  
  2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL’22) | July 2022
  
  Publication Project
- Personalized Federated Learning with Adaptive Batchnorm for Healthcare
  
  Wang Lu, Jindong Wang, Yiqiang Chen, Xin Qin, Renjun Xu, Dimitrios Dimitriadis, Tao Qin
  
  IEEE Transactions on Big Data | May 2022
  
  Preprint Publication Projet
- DeepAnalyze: Learning to Localize Crashes at Scale
  
  Manish Shetty, Chetan Bansal, Suman Nath, Sean Bowles, Henry Wang, Ozgur Arman, Siamak Ahari
  
  ICSE 2022 | May 2022
  
  Publication Project
- Spot Virtual Machine Eviction Prediction in Microsoft Cloud
  
  Fangkai Yang, Bowen Pang, Jue Zhang, Bo Qiao, Lu Wang, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Senthil Baladhandayutham, Victor Rühle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  WWW’22 Companion | April 2022
  
  Publication
- SoftNER: Mining knowledge graphs from Cloud Incidents
  
  Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan
  
  Empirical Software Engineering | April 2022, Vol 27(4)
  
  Publication
- FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations
  
  Dimitrios Dimitriadis, Mirian Hipolito Garcia, Daniel Madrigal, Andre Manoel, Robert Sim
  
  March 2022
  
  Preprint Github Project
- HALO: Hierarchy-aware Fault Localization for Cloud Systems
  
  Xu Zhang, Chao Du, Yifan Li, Yong Xu, Hongyu Zhang, Si Qin, Ze Li, Qingwei Lin 林庆维, Yingnong Dang, Andrew Zhou, Saravanakumar Rajmohan, Dongmei Zhang
  
  SigKDD’21 Applied Data Science Track | October 2021
  
  Publication PDF Projet Projet
- How Long Will it Take to Mitigate this Incident for Online Service Systems?
  
  Weijing Wang, Junjie Chen, Lin Yang, Hongyu Zhang, Pu Zhao, Bo Qiao, Yu Kang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Feng Gao, Zhangwei Xu, Yingnong Dang, Dongmei Zhang
  
  ISSRE’21 | September 2021
  
  Best Research Paper
  
  Publication Projet Projet
- Intelligent container reallocation at Microsoft 365
  
  Bo Qiao, Fangkai Yang, Chuan Luo, Yanan Wang, Johnny Li, Qingwei Lin 林庆维, Hongyu Zhang, Mohit Datta, Andrew Zhou, Thomas Moscibroda, Saravanakumar Rajmohan, Dongmei Zhang
  
  2021 Foundations of Software Engineering | August 2021
  
  DOI Projet Projet
- Fighting the Fog of War: Automated Incident Detection for Cloud Systems
  
  Liqun Li, Xu Zhang, Xin Zhao, Hongyu Zhang, Yu Kang, Pu Zhao, Bo Qiao, Shilin He, Pochian Lee, Jeffrey Sun, Feng Gao, Li Yang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Zhangwei Xu, Dongmei Zhang
  
  2021 USENIX Annual Technical Conference (USENIX ATC’21) | August 2021
  
  Publication Project Project
- Neural Knowledge Extraction From Cloud Service Incidents
  
  Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan, Tom Zimmermann
  
  43rd International Conference on Software Engineering (ICSE ’21) – SEIP Track | May 2021
- Correlation-Aware Heuristic Search for Intelligent Virtual Machine Provisioning in Cloud Systems
  
  Chuan Luo, Bo Qiao, Wenqian Xing, Xin Chen, Pu Zhao, Chao Du, Randolph Yao, Hongyu Zhang, Wei Wu, Shaowei Cai, Saravanakumar Rajmohan, Qingwei Lin 林庆维
  
  AAAI’21 | March 2021
  
  Publication Projet Projet Projet
- PULNS: Positive-Unlabeled Learning with Effective Negative Sample Selector
  
  Chuan Luo, …, Qingwei Lin 林庆维
  
  AAAI’21 | March 2021
  
  Publication Projet
- NTAM: Neighborhood-Temporal Attention Model for Disk Failure Prediction in Cloud Platforms
  
  Chuan Luo, Pu Zhao, …, Qingwei Lin 林庆维, …
  
  WWW (TheWebConf) 2021 | February 2021
  
  Publication Project Project Project
- Predicting Pull Request Completion Time: A Case Study on Large Scale Cloud Services
  
  Chandra Maddila, Chetan Bansal, Nachi Nagappan
  
  ESEC/FSE 2019 | August 2019
  
  Publication Project
- Triangle: Empowering Incident Triage with Multi-Agent
  
  Zhaoyang Yu, Aoyang Fang, Minghua Ma, Chaoyun Zhang, Ze Li, Murali Chintalapati, Xuchao Zhang, Rujia Wang, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, et.al
  
  ASE’25 | November 2025
  
  Publication
- ProtoRAIL: A Risk-cognizant Imitation Agent for Adaptive vCPU Oversubscription In The Cloud
  
  Lu Wang, Mayukh Das, Fangkai Yang, Bo Qiao, Hang Dong, Si Qin, Victor Ruehle, Chetan Bansal, Eli Cortez, Íñigo Goiri, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  MLSys’25 | May 2025
  
  Publication
- AIOpsLab: A Holistic Framework for Evaluating AI Agents for Enabling Autonomous Cloud
  
  Yinfang Chen, Manish Shetty, Gagan Somashekar, Minghua Ma, Yogesh Simmhan, Jonathan Mace, Chetan Bansal, Rujia Wang, Saravan Rajmohan
  
  MLSys ’25 | May 2025
  
  Publication
- Towards Cloud Efficiency with Large-scale Workload Characterization
  
  A. Parayil, Jue Zhang, Xiaoting Qin, Íñigo Goiri, Chetan Bansal
  
  ICPE | May 2025
  
  Preprint
- Serving Models, Fast and Slow:Optimizing Heterogeneous LLM Inferencing Workloads at Scale
  
  Kunal Jain, A. Parayil, Ankur Mallick, Rujia Wang, Renee St. Amant, Chetan Bansal, Victor Ruehle, Saravan Rajmohan, Shashwat Jaiswal, Yogesh Simmhan, Anoop Kulkarni, Steve Kofsky
  
  ArXiv | February 2025
  
  Publication
- Towards Efficient Large Multimodal Model Serving
  
  Haoran Qiu, Anish Biswas, Zihan Zhao, Jayashree Mohan, Alind Khare, Esha Choukse, Íñigo Goiri, Zeyu Zhang, Haiying Shen, Chetan Bansal, Ramachandran Ramjee, Rodrigo Fonseca
  
  February 2025
  
  Preprint Project Project
- Ensuring Fair LLM Serving Amid Diverse Applications
  
  Kunal Jain, Ankur Mallick, A. Parayil, Renee St. Amant, Rujia Wang, Victor Ruehle, Chetan Bansal, Saravan Rajmohan, Redwan Ibne Seraj Khan, Haiying Shen, Anoop Kulkarni, Steve Kofsky, Pankhuri Choudhary, Yue Cheng
  
  ArXiv | November 2024
  
  Publication
- Building AI Agents for Autonomous Clouds: Challenges and Design Principles
  
  Manisha M Shetty, Yinfang Chen, Gagan Somashekar, Minghua Ma, Yogesh L. Simmhan, Xuchao Zhang, Jonathan Mace, Pedro Las-Casas, Shachee Mishra Gupta, Suman Nath, Chetan Bansal, Saravan Rajmohan
  
  2024 Symposium on Cloud Computing | November 2024
  
  Publication
- COIN: Chance-Constrained Imitation Learning for Safe and Adaptive Resource Oversubscription under Uncertainty
  
  Lu Wang, Mayukh Das, Fangkai Yang, Chao Du, Bo Qiao, Hang Dong, Chetan Bansal, Si Qin, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang, Qi Zhang
  
  CIKM’24 | October 2024
  
  PDF
- Intelligent Router for LLM Workloads: Improving Performance Through Workload-Aware Scheduling
  
  A. Parayil, Ankur Mallick, Esha Choukse, Xiaoting Qin, Jue Zhang, Íñigo Goiri, Rujia Wang, Chetan Bansal, Victor Ruehle, Saravan Rajmohan, Kunal Jain, Anoop Kulkarni, Steve Kofsky
  
  ArXiv | August 2024, Vol abs/2408.13510
  
  Preprint
- Large Language Models Can Provide Accurate and Interpretable Incident Triage
  
  Zexin Wang, Minghua Ma, Ze Li, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  2024 International Symposium on Software Reliability Engineering | August 2024
  
  Publication
- Designing Cloud Servers for Lower Carbon
  
  Jaylen Wang, Daniel S. Berger, Fiodar Kazhamiaka, Celine Irvene, Chaojie Zhang, Esha Choukse, Kali Frost, Rodrigo Fonseca, Brijesh Warrier, Chetan Bansal, Jonathan Stern, Ricardo Bianchini, Akshitha Sriraman
  
  ISCA | June 2024
  
  Publication
- SmartOClock: Workload- and Risk-Aware Overclocking in the Cloud
  
  Jovan Stojkovic, Pulkit Misra, Íñigo Goiri, Sam Whitlock, Esha Choukse, Mayukh Das, Chetan Bansal, Jason Lee, Zoey Sun, Haoran Qiu, Reed Zimmermann, Savyasachi Samal, Brijesh Warrier, Ashish Raniwala, Ricardo Bianchini
  
  ISCA | June 2024
  
  Publication
- LeanAttention: Hardware-Aware Scalable Attention Mechanism for the Decode-Phase of Transformers
  
  Rya Sanovar, Srikant Bharadwaj, Renee St. Amant, Victor Ruehle, Saravan Rajmohan
  
  May 2024
  
  Publication
- Intelligent Overclocking for Improved Cloud Efficiency
  
  Aditya Soni, Mayukh Das, Pulkit Misra, Chetan Bansal
  
  AIOps ’24 workshop @ ASPLOS [5th International Workshop on Cloud Intelligence / AIOps] | April 2024
  
  Preprint
- Automatic Root Cause Analysis via Large Language Models for Cloud Incidents
  
  Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xue‐Chao Gao, Hao Fan, Ming Wen, Jun Zeng, Supriyo GHOSH, Xuchao Zhang, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang
  
  EuroSys’24 | April 2024
  
  Publication
- Intelligent Monitoring Framework for Cloud Services: A Data-Driven Approach
  
  Pooja Srinivas, Fiza Husain, A. Parayil, Ayush Choure, Chetan Bansal, Saravan Rajmohan
  
  46th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP’24) | April 2024
  
  Preprint
- Workload Intelligence: Punching Holes Through the Cloud Abstraction
  
  Lexiang Huang, A. Parayil, Jue Zhang, Xiaoting Qin, Chetan Bansal, Jovan Stojkovic, Pantea Zardoshti, Pulkit Misra, Eli Cortez, Raphael Ghelman, Íñigo Goiri, Saravan Rajmohan, Jim Kleewein, Rodrigo Fonseca, Timothy Zhu, Ricardo Bianchini
  
  ArXiv | April 2024, Vol abs/2404.19143
  
  Preprint
- OPPerTune: Post-Deployment Configuration Tuning of Services Made Easy
  
  Gagan Somashekar, Karan Tandon, Anush Kini, Chieh-Chun Chang, Petr Husak, Ranjita Bhagwan, Mayukh Das, Anshul Gandhi, Nagarajan Natarajan
  
  NSDI 2024 | April 2024
  
  Publication Publication Github Project Project
- NASerEx: Optimizing Early Exits via AutoML for Scalable Efficient Inference in Big Image Streams
  
  Aakash Kapoor, Rajath Elias Soans, Soham Dixit, Pradeep NS, Brijraj Singh, Mayukh Das
  
  IEEE Big Data 2023 | December 2023
  
  Special session on Machine Learning on Big Data (MLBD)
  
  Publication
- Detection Is Better Than Cure: A Cloud Incidents Perspective
  
  A. Parayil, Supriyo GHOSH, Yu Kang, Minghua Ma, Chetan Bansal, Suman Nath, Jonathan Mace, Vaibhav Ganatra
  
  ESEC/FSE 2023: Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering | November 2023
  
  Publication
- PACE-LM: Prompting and Augmentation for Calibrated Confidence Estimation with GPT-4 in Cloud Incident Root Cause Analysis
  
  Dylan Zhang, Xuchao Zhang, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, Saravan Rajmohan
  
  September 2023
  
  Publication
- How Different are the Cloud Workloads? Characterizing Large-Scale Private and Public Cloud Workloads
  
  Xiaoting Qin, Minghua Ma, Yueng Zhao, Jue Zhang, Chao Du, Yudong Liu, A. Parayil, Chetan Bansal, Saravan Rajmohan, Íñigo Goiri, Eli Cortez, Si Qin, Qingwei Lin 林庆维, Dongmei Zhang
  
  DSN’23 | June 2023
  
  Publication
- Snape: Reliable and Low-Cost Computing with Mixture of Spot and On-Demand VMs
  
  Fangkai Yang, Lu Wang, Zhenyu Xu, Jue Zhang, Liqun Li, Bo Qiao, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Terry Yang, Victor Ruehle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  ASPLOS’23 | March 2023
  
  Publication
- AutoTSG: Learning and Synthesis for Incident Troubleshooting
  
  Manish Shetty, Chetan Bansal, Sai Pramod Upadhyayula, Arjun Radhakrishna, Anurag Gupta
  
  ESEC/FSE 2022 | November 2022
  
  Publication Publication Publication
- How to Fight Production Incidents? An Empirical Study on a Large-scale Cloud Service
  
  Supriyo GHOSH, Manish Shetty, Chetan Bansal, Suman Nath
  
  SoCC 2022 | November 2022
  
  Best Paper Award
  
  Publication PDF Project
- Multi-task Hierarchical Classification for Disk Failure Prediction in Online Service Systems
  
  Yudong Liu, Hailan Yang, Pu Zhao, Minghua Ma, Chengwu Wen, Hongyu Zhang, Chuan Luo, Qingwei Lin 林庆维, Chang Yi, Jiaojian Wang, Chenjian Zhang, Paul Wang, Yingnong Dang, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD 2022 | August 2022
  
  DOI Publication Project Project
- Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach
  
  Jie Yan, Yunlei Lu, Liting Chen, Si Qin, Yixin Fang, Qingwei Lin 林庆维, Thomas Moscibroda, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD’22 | August 2022
  
  Publication Project Project
- NENYA: Cascade Reinforcement Learning for Cost-Aware Failure Mitigation at Microsoft 365
  
  Lu Wang, Pu Zhao, Chao Du, Chuan Luo, Mengna Su, Fangkai Yang, Yudong Liu, Qingwei Lin 林庆维, Min Wang, Yingnong Dang, Hongyu Zhang, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD 2022 | August 2022
  
  Publication Project Project
- DeepAnalyze: Learning to Localize Crashes at Scale
  
  Manish Shetty, Chetan Bansal, Suman Nath, Sean Bowles, Henry Wang, Ozgur Arman, Siamak Ahari
  
  ICSE 2022 | May 2022
  
  Publication Project
- Spot Virtual Machine Eviction Prediction in Microsoft Cloud
  
  Fangkai Yang, Bowen Pang, Jue Zhang, Bo Qiao, Lu Wang, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Senthil Baladhandayutham, Victor Rühle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  WWW’22 Companion | April 2022
  
  Publication
- HALO: Hierarchy-aware Fault Localization for Cloud Systems
  
  Xu Zhang, Chao Du, Yifan Li, Yong Xu, Hongyu Zhang, Si Qin, Ze Li, Qingwei Lin 林庆维, Yingnong Dang, Andrew Zhou, Saravanakumar Rajmohan, Dongmei Zhang
  
  SigKDD’21 Applied Data Science Track | October 2021
  
  Publication PDF Projet Projet
- How Long Will it Take to Mitigate this Incident for Online Service Systems?
  
  Weijing Wang, Junjie Chen, Lin Yang, Hongyu Zhang, Pu Zhao, Bo Qiao, Yu Kang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Feng Gao, Zhangwei Xu, Yingnong Dang, Dongmei Zhang
  
  ISSRE’21 | September 2021
  
  Best Research Paper
  
  Publication Projet Projet
- Intelligent container reallocation at Microsoft 365
  
  Bo Qiao, Fangkai Yang, Chuan Luo, Yanan Wang, Johnny Li, Qingwei Lin 林庆维, Hongyu Zhang, Mohit Datta, Andrew Zhou, Thomas Moscibroda, Saravanakumar Rajmohan, Dongmei Zhang
  
  2021 Foundations of Software Engineering | August 2021
  
  DOI Projet Projet
- Fighting the Fog of War: Automated Incident Detection for Cloud Systems
  
  Liqun Li, Xu Zhang, Xin Zhao, Hongyu Zhang, Yu Kang, Pu Zhao, Bo Qiao, Shilin He, Pochian Lee, Jeffrey Sun, Feng Gao, Li Yang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Zhangwei Xu, Dongmei Zhang
  
  2021 USENIX Annual Technical Conference (USENIX ATC’21) | August 2021
  
  Publication Project Project
- DeCaf: Diagnosing and Triaging Performance Issues in Large-Scale Cloud Services
  
  Chetan Bansal, Sundararajan Renganathan, Ashima Asudani, Olivier Midy, Mathru Janakiraman
  
  ICSE 2020 | May 2020
  
  PDF Project
- Rex: Preventing Bugs and Misconfiguration in Large Services using Correlated Change Analysis
  
  Sonu Mehta, Ranjita Bhagwan, Rahul Kumar, B. Ashok, Chetan Bansal, Chandra Maddila, Christian Bird, Sumit Asthana, Aditya Kumar
  
  Networked System Design and Implementation (NSDI) | February 2020
  
  Publication Project
- Building sankie: an AI platform for DevOps
  
  Rahul Kumar, Chetan Bansal, Chandra Maddila, Nitin Sharma, Shawn Martelock, Ravi Bhargava
  
  1st International Workshop on Bots in Software Engineering (BotSE ’19) | May 2019
  
  Publication Project
- FastLane: Test Minimization for Rapidly Deployed Large-scale Online Services
  
  Ranjita Bhagwan, Adithya Philip, Rahul Kumar, Chandra Maddila, Nachi Nagappan
  
  International Conference on Software Engineering | May 2019
  
  Publication Project
- Orca: Differential Bug Localization in Large-Scale Services
  
  Ranjita Bhagwan, Rahul Kumar, Chandra Maddila, Adithya Abraham Philip
  
  13th USENIX Symposium on Operating Systems Design and Implementation | October 2018
  
  Won the Jay Lepreau Best Paper Award
  
  Publication Projet
- Reason-before-Retrieve: One-Stage Reflective Chain-of-Thoughts for Training-Free Zero-Shot Composed Image Retrieval
  
  Yuanmin Tang, Xiaoting Qin, Jue Zhang, Jing Yu, Gaopeng Gou, Gang Xiong, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang, Qi Wu
  
  CVPR’25 | June 2025
  
  Preprint
- The Canary’s Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
  
  Matthieu Meeus, Lukas Wutschitz, Santiago Zanella-Béguelin, Reza Shokri, Shruti Tople
  
  February 2025
  
  DOI Preprint Project
- Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
  
  Xinyu Tang, Richard Shin, Huseyin Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Robert Sim
  
  ICLR 2024 | May 2024
  
  Publication Publication Github Projet
- Advancing differential privacy: where we are now and future directions for real-world deployment
  
  Rachel Cummings, Damien Desfontaines, David Evans, Roxana Geambasu, Yangsibo Huang, Matthew Jagielski, Peter Kairouz, Gautam Kamath, Sewoong Oh, Olga Ohrimenko, Nicolas Papernot, Ryan Rogers, Milan Shen, Shuang Song, Weijie Su, Andreas Terzis, Abhradeep Thakurta, Sergei Vassilvitskii, Yu-Xiang Wang, Li Xiong, Da Yu, Sergey Yekhanin, Huanyu Zhang, Wanrong Zhang
  
  Harvard Data Science Review | January 2024, Vol 6(1)
  
  Publication Project
- Secure Floating-Point Training
  
  Deevashwer Rathee, Anwesh Bhattacharya, Divya Gupta, Rahul Sharma, Dawn Song
  
  Usenix Security Symposium 2023 | August 2023
  
  Publication Project
- Bayesian Estimation of Differential Privacy
  
  Santiago Zanella-Béguelin, Lukas Wutschitz, Shruti Tople, Ahmed Salem, Victor Ruehle, Andrew Paverd, Mohammad Naseri, Boris Köpf, Daniel Jones
  
  2023 International Conference on Machine Learning | July 2023
  
  Editor(s): Barbara Engelhardt, Emma Brunskill, Kyunghyun Cho
  
  Publication Project
- Analyzing Leakage of Personally Identifiable Information in Language Models
  
  Nils Lukas, Ahmed Salem, Robert Sim, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin
  
  2023 IEEE Symposium on Security and Privacy | May 2023
  
  Publication PDF DOI Project
- SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning
  
  Ahmed Salem, Giovanni Cherubin, David Evans, Boris Köpf, Andrew Paverd, Anshuman Suri, Shruti Tople, Santiago Zanella-Béguelin
  
  2023 IEEE Symposium on Security and Privacy | May 2023
  
  Publication PDF DOI Project
- Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
  
  Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan (Jana) Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian
  
  International Conference on Learning Representations (ICLR) 2023 | May 2023
  
  Publication Projet
- Membership Inference Attacks and Generalization: A Causal Perspective
  
  Teodora Baluta, Shiqi Shen, S. Hitarth, Shruti Tople, Prateek Saxena
  
  Computer and Communications Security (CCS) | November 2022
  
  Publication Projet
- SIMC: ML Inference Secure Against Malicious Clients at Semi-Honest Cost
  
  Nishanth Chandran, Divya Gupta, Sai Lakshmi Bhavana Obbattu, Akash Shah
  
  USENIX Security | August 2022
  
  USENIX Security 2022
  
  Publication Project
- dp-transformers: Training transformer models with differential privacy
  
  Huseyin Inan, Andre Manoel, Lukas Wutschitz
  
  July 2022
  
  Publication Project
- Private Convex Optimization in General Norms
  
  Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Rouqi Shen, Kevin Tian
  
  SODA 2023 | July 2022
  
  Publication Projet
- Circuit-PSI with Linear Complexity via Relaxed Batch OPPRF
  
  Nishanth Chandran, Divya Gupta, Akash Shah
  
  22nd Privacy Enhancing Technologies Symposium (PETS 2022) | June 2022
  
  Publication Project
- SECFLOAT: Accurate Floating-Point meets Secure 2-Party Computation
  
  Deevashwer Rathee, Anwesh Bhattacharya, Rahul Sharma, Divya Gupta, Nishanth Chandran, Aseem Rastogi
  
  43rd IEEE Symposium on Security and Privacy (IEEE S&P 2022) | May 2022
  
  Publication Project
- FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations
  
  Dimitrios Dimitriadis, Mirian Hipolito Garcia, Daniel Madrigal, Andre Manoel, Robert Sim
  
  March 2022
  
  Preprint Github Project
- Private Convex Optimization via Exponential Mechanism
  
  Sivakanth Gopi, Yin Tat Lee, Daogao Liu
  
  COLT 2022 | March 2022
  
  Publication Project
- EzPC: Programmable, Efficient, and Scalable Secure Two-Party Computation for Machine Learning
  
  Nishanth Chandran, Divya Gupta, Aseem Rastogi, Rahul Sharma, Shardul Tripathi
  
  IEEE European Symposium on Security and Privacy | February 2019
  
  Publication Vidéo Github Projet
- Triangle: Empowering Incident Triage with Multi-Agent
  
  Zhaoyang Yu, Aoyang Fang, Minghua Ma, Chaoyun Zhang, Ze Li, Murali Chintalapati, Xuchao Zhang, Rujia Wang, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, et.al
  
  ASE’25 | November 2025
  
  Publication
- AIOpsLab: A Holistic Framework for Evaluating AI Agents for Enabling Autonomous Cloud
  
  Yinfang Chen, Manish Shetty, Gagan Somashekar, Minghua Ma, Yogesh Simmhan, Jonathan Mace, Chetan Bansal, Rujia Wang, Saravan Rajmohan
  
  MLSys ’25 | May 2025
  
  Publication
- Automatic Root Cause Analysis via Large Language Models for Cloud Incidents
  
  Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xue‐Chao Gao, Hao Fan, Ming Wen, Jun Zeng, Supriyo GHOSH, Xuchao Zhang, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang
  
  EuroSys’24 | April 2024
  
  Publication
- Multi-task Hierarchical Classification for Disk Failure Prediction in Online Service Systems
  
  Yudong Liu, Hailan Yang, Pu Zhao, Minghua Ma, Chengwu Wen, Hongyu Zhang, Chuan Luo, Qingwei Lin 林庆维, Chang Yi, Jiaojian Wang, Chenjian Zhang, Paul Wang, Yingnong Dang, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD 2022 | August 2022
  
  DOI Publication Project Project
- Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach
  
  Jie Yan, Yunlei Lu, Liting Chen, Si Qin, Yixin Fang, Qingwei Lin 林庆维, Thomas Moscibroda, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD’22 | August 2022
  
  Publication Project Project
- NENYA: Cascade Reinforcement Learning for Cost-Aware Failure Mitigation at Microsoft 365
  
  Lu Wang, Pu Zhao, Chao Du, Chuan Luo, Mengna Su, Fangkai Yang, Yudong Liu, Qingwei Lin 林庆维, Min Wang, Yingnong Dang, Hongyu Zhang, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD 2022 | August 2022
  
  Publication Project Project
- Spot Virtual Machine Eviction Prediction in Microsoft Cloud
  
  Fangkai Yang, Bowen Pang, Jue Zhang, Bo Qiao, Lu Wang, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Senthil Baladhandayutham, Victor Rühle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  WWW’22 Companion | April 2022
  
  Publication
- HALO: Hierarchy-aware Fault Localization for Cloud Systems
  
  Xu Zhang, Chao Du, Yifan Li, Yong Xu, Hongyu Zhang, Si Qin, Ze Li, Qingwei Lin 林庆维, Yingnong Dang, Andrew Zhou, Saravanakumar Rajmohan, Dongmei Zhang
  
  SigKDD’21 Applied Data Science Track | October 2021
  
  Publication PDF Projet Projet
- How Long Will it Take to Mitigate this Incident for Online Service Systems?
  
  Weijing Wang, Junjie Chen, Lin Yang, Hongyu Zhang, Pu Zhao, Bo Qiao, Yu Kang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Feng Gao, Zhangwei Xu, Yingnong Dang, Dongmei Zhang
  
  ISSRE’21 | September 2021
  
  Best Research Paper
  
  Publication Projet Projet
- Fighting the Fog of War: Automated Incident Detection for Cloud Systems
  
  Liqun Li, Xu Zhang, Xin Zhao, Hongyu Zhang, Yu Kang, Pu Zhao, Bo Qiao, Shilin He, Pochian Lee, Jeffrey Sun, Feng Gao, Li Yang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Zhangwei Xu, Dongmei Zhang
  
  2021 USENIX Annual Technical Conference (USENIX ATC’21) | August 2021
  
  Publication Project Project
- Correlation-Aware Heuristic Search for Intelligent Virtual Machine Provisioning in Cloud Systems
  
  Chuan Luo, Bo Qiao, Wenqian Xing, Xin Chen, Pu Zhao, Chao Du, Randolph Yao, Hongyu Zhang, Wei Wu, Shaowei Cai, Saravanakumar Rajmohan, Qingwei Lin 林庆维
  
  AAAI’21 | March 2021
  
  Publication Projet Projet Projet
- PULNS: Positive-Unlabeled Learning with Effective Negative Sample Selector
  
  Chuan Luo, …, Qingwei Lin 林庆维
  
  AAAI’21 | March 2021
  
  Publication Projet
- NTAM: Neighborhood-Temporal Attention Model for Disk Failure Prediction in Cloud Platforms
  
  Chuan Luo, Pu Zhao, …, Qingwei Lin 林庆维, …
  
  WWW (TheWebConf) 2021 | February 2021
  
  Publication Project Project Project
- Time Warp: The Gap Between Developers’ Ideal vs Actual Workweeks in an AI-Driven Era
  
  Sukrit Kumar, Drishti Goel, Tom Zimmermann, Brian Houck, B. Ashok, Chetan Bansal
  
  ICSE SEIP ’25 | April 2025
  
  Distinguished Paper Award
  
  Preprint
- Building AI Agents for Autonomous Clouds: Challenges and Design Principles
  
  Manisha M Shetty, Yinfang Chen, Gagan Somashekar, Minghua Ma, Yogesh L. Simmhan, Xuchao Zhang, Jonathan Mace, Pedro Las-Casas, Shachee Mishra Gupta, Suman Nath, Chetan Bansal, Saravan Rajmohan
  
  2024 Symposium on Cloud Computing | November 2024
  
  Publication
- FLASH: A Workflow Automation Agent for Diagnosing Recurring Incidents
  
  Xuchao Zhang, Tanish Mittal, Chetan Bansal, Rujia Wang, Minghua Ma, Zhixin Ren, Hao Huang, Saravan Rajmohan
  
  October 2024
  
  Publication Project
- Automatic Root Cause Analysis via Large Language Models for Cloud Incidents
  
  Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xue‐Chao Gao, Hao Fan, Ming Wen, Jun Zeng, Supriyo GHOSH, Xuchao Zhang, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang
  
  EuroSys’24 | April 2024
  
  Publication
- Intelligent Monitoring Framework for Cloud Services: A Data-Driven Approach
  
  Pooja Srinivas, Fiza Husain, A. Parayil, Ayush Choure, Chetan Bansal, Saravan Rajmohan
  
  46th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP’24) | April 2024
  
  Preprint
- Detection Is Better Than Cure: A Cloud Incidents Perspective
  
  A. Parayil, Supriyo GHOSH, Yu Kang, Minghua Ma, Chetan Bansal, Suman Nath, Jonathan Mace, Vaibhav Ganatra
  
  ESEC/FSE 2023: Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering | November 2023
  
  Publication
- Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models
  
  Toufique Ahmed, Supriyo GHOSH, Chetan Bansal, Tom Zimmermann, Xuchao Zhang, Saravan Rajmohan
  
  ICSE 2023 | May 2023
  
  Publication
- AutoTSG: Learning and Synthesis for Incident Troubleshooting
  
  Manish Shetty, Chetan Bansal, Sai Pramod Upadhyayula, Arjun Radhakrishna, Anurag Gupta
  
  ESEC/FSE 2022 | November 2022
  
  Publication Publication Publication
- How to Fight Production Incidents? An Empirical Study on a Large-scale Cloud Service
  
  Supriyo GHOSH, Manish Shetty, Chetan Bansal, Suman Nath
  
  SoCC 2022 | November 2022
  
  Best Paper Award
  
  Publication PDF Project
- Multi-task Hierarchical Classification for Disk Failure Prediction in Online Service Systems
  
  Yudong Liu, Hailan Yang, Pu Zhao, Minghua Ma, Chengwu Wen, Hongyu Zhang, Chuan Luo, Qingwei Lin 林庆维, Chang Yi, Jiaojian Wang, Chenjian Zhang, Paul Wang, Yingnong Dang, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD 2022 | August 2022
  
  DOI Publication Project Project
- NENYA: Cascade Reinforcement Learning for Cost-Aware Failure Mitigation at Microsoft 365
  
  Lu Wang, Pu Zhao, Chao Du, Chuan Luo, Mengna Su, Fangkai Yang, Yudong Liu, Qingwei Lin 林庆维, Min Wang, Yingnong Dang, Hongyu Zhang, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD 2022 | August 2022
  
  Publication Project Project
- DeepAnalyze: Learning to Localize Crashes at Scale
  
  Manish Shetty, Chetan Bansal, Suman Nath, Sean Bowles, Henry Wang, Ozgur Arman, Siamak Ahari
  
  ICSE 2022 | May 2022
  
  Publication Project
- Spot Virtual Machine Eviction Prediction in Microsoft Cloud
  
  Fangkai Yang, Bowen Pang, Jue Zhang, Bo Qiao, Lu Wang, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Senthil Baladhandayutham, Victor Rühle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  WWW’22 Companion | April 2022
  
  Publication
- SoftNER: Mining knowledge graphs from Cloud Incidents
  
  Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan
  
  Empirical Software Engineering | April 2022, Vol 27(4)
  
  Publication
- How Long Will it Take to Mitigate this Incident for Online Service Systems?
  
  Weijing Wang, Junjie Chen, Lin Yang, Hongyu Zhang, Pu Zhao, Bo Qiao, Yu Kang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Feng Gao, Zhangwei Xu, Yingnong Dang, Dongmei Zhang
  
  ISSRE’21 | September 2021
  
  Best Research Paper
  
  Publication Projet Projet
- Fighting the Fog of War: Automated Incident Detection for Cloud Systems
  
  Liqun Li, Xu Zhang, Xin Zhao, Hongyu Zhang, Yu Kang, Pu Zhao, Bo Qiao, Shilin He, Pochian Lee, Jeffrey Sun, Feng Gao, Li Yang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Zhangwei Xu, Dongmei Zhang
  
  2021 USENIX Annual Technical Conference (USENIX ATC’21) | August 2021
  
  Publication Project Project
- Neural Knowledge Extraction From Cloud Service Incidents
  
  Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan, Tom Zimmermann
  
  43rd International Conference on Software Engineering (ICSE ’21) – SEIP Track | May 2021
- DeCaf: Diagnosing and Triaging Performance Issues in Large-Scale Cloud Services
  
  Chetan Bansal, Sundararajan Renganathan, Ashima Asudani, Olivier Midy, Mathru Janakiraman
  
  ICSE 2020 | May 2020
  
  PDF Project
- Rex: Preventing Bugs and Misconfiguration in Large Services using Correlated Change Analysis
  
  Sonu Mehta, Ranjita Bhagwan, Rahul Kumar, B. Ashok, Chetan Bansal, Chandra Maddila, Christian Bird, Sumit Asthana, Aditya Kumar
  
  Networked System Design and Implementation (NSDI) | February 2020
  
  Publication Project
- WhoDo: Automating Reviewer Suggestions at Scale
  
  Sumit Asthana, Rahul Kumar, Ranjita Bhagwan, Chetan Bansal, Christian Bird, Chandra Maddila, Sonu Mehta, B. Ashok
  
  ESEC/FSE 2019 | August 2019
  
  Publication Projet
- Predicting Pull Request Completion Time: A Case Study on Large Scale Cloud Services
  
  Chandra Maddila, Chetan Bansal, Nachi Nagappan
  
  ESEC/FSE 2019 | August 2019
  
  Publication Project
- Building sankie: an AI platform for DevOps
  
  Rahul Kumar, Chetan Bansal, Chandra Maddila, Nitin Sharma, Shawn Martelock, Ravi Bhargava
  
  1st International Workshop on Bots in Software Engineering (BotSE ’19) | May 2019
  
  Publication Project
- FastLane: Test Minimization for Rapidly Deployed Large-scale Online Services
  
  Ranjita Bhagwan, Adithya Philip, Rahul Kumar, Chandra Maddila, Nachi Nagappan
  
  International Conference on Software Engineering | May 2019
  
  Publication Project
- EzPC: Programmable, Efficient, and Scalable Secure Two-Party Computation for Machine Learning
  
  Nishanth Chandran, Divya Gupta, Aseem Rastogi, Rahul Sharma, Shardul Tripathi
  
  IEEE European Symposium on Security and Privacy | February 2019
  
  Publication Vidéo Github Projet
- AI Delegates with a Dual Focus: Ensuring Privacy and Strategic Self-Disclosure
  
  Xi Chen, Zhiyang Zhang, Fangkai Yang, Xiaoting Qin, Chao Du, Xi Cheng, Hangxin Liu, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang, Qi Zhang
  
  September 2024
  
  Preprint
- CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models
  
  Peng Xia, Ze Chen, Juanxi Tian, Yangrui Gong, Ruibo Hou, Yue Xu, Zhenbang Wu, Zhiyuan Fan, Yiyang Zhou, Kangyu Zhu, Wenhao Zheng, Zhaoyang Wang, Xiao Wang, Xuchao Zhang, Chetan Bansal, Marc Niethammer, Junzhou Huang, Hongtu Zhu, Yun Li, Jimeng Sun, Zongyuan Ge, Gang Li, James Zou, Huaxiu Yao
  
  NeurIPS 2024 | June 2024
  
  DOI Publication Publication
- LeanAttention: Hardware-Aware Scalable Attention Mechanism for the Decode-Phase of Transformers
  
  Rya Sanovar, Srikant Bharadwaj, Renee St. Amant, Victor Ruehle, Saravan Rajmohan
  
  May 2024
  
  Publication
- Predict; Don’t React for Enabling Efficient Fine-Grain DVFS in GPUs
  
  Srikant Bharadwaj, Shomit Das, K. Mazumdar, Bradford M. Beckmann, Stephen Kosonocky
  
  Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems | March 2024
  
  Publication DOI Publication
- LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
  
  Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, Menglin Xia, Xufang Luo, Jue Zhang, Qingwei Lin 林庆维, Victor Ruehle, Yuqing Yang, Chin-Yew Lin, H. Vicky Zhao, Lili Qiu, Dongmei Zhang
  
  The 62nd Annual Meeting of the Association for Computational Linguistics (Findings of ACL 2024) | March 2024
  
  Preprint Project
- Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models
  
  Toufique Ahmed, Supriyo GHOSH, Chetan Bansal, Tom Zimmermann, Xuchao Zhang, Saravan Rajmohan
  
  ICSE 2023 | May 2023
  
  Publication
- UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis
  
  Fatemehsadat Mireshghallah, Vaishnavi Shrivastava, Milad Shokouhi, Taylor Berg-Kirkpatrick, Robert Sim, Dimitrios Dimitriadis
  
  2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL’22) | July 2022
  
  Publication Project
- Advancing differential privacy: where we are now and future directions for real-world deployment
  
  Rachel Cummings, Damien Desfontaines, David Evans, Roxana Geambasu, Yangsibo Huang, Matthew Jagielski, Peter Kairouz, Gautam Kamath, Sewoong Oh, Olga Ohrimenko, Nicolas Papernot, Ryan Rogers, Milan Shen, Shuang Song, Weijie Su, Andreas Terzis, Abhradeep Thakurta, Sergei Vassilvitskii, Yu-Xiang Wang, Li Xiong, Da Yu, Sergey Yekhanin, Huanyu Zhang, Wanrong Zhang
  
  Harvard Data Science Review | January 2024, Vol 6(1)
  
  Publication Project
- Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler
  
  Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Rouqi Shen, Kevin Tian
  
  COLT 2023 | February 2023
  
  Publication Project
- Private Convex Optimization in General Norms
  
  Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Rouqi Shen, Kevin Tian
  
  SODA 2023 | July 2022
  
  Publication Projet
- Private Convex Optimization via Exponential Mechanism
  
  Sivakanth Gopi, Yin Tat Lee, Daogao Liu
  
  COLT 2022 | March 2022
  
  Publication Project

- Triangle: Empowering Incident Triage with Multi-Agent
  
  Zhaoyang Yu, Aoyang Fang, Minghua Ma, Chaoyun Zhang, Ze Li, Murali Chintalapati, Xuchao Zhang, Rujia Wang, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, et.al
  
  ASE’25 | November 2025
  
  Publication
- Reason-before-Retrieve: One-Stage Reflective Chain-of-Thoughts for Training-Free Zero-Shot Composed Image Retrieval
  
  Yuanmin Tang, Xiaoting Qin, Jue Zhang, Jing Yu, Gaopeng Gou, Gang Xiong, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang, Qi Wu
  
  CVPR’25 | June 2025
  
  Preprint
- ProtoRAIL: A Risk-cognizant Imitation Agent for Adaptive vCPU Oversubscription In The Cloud
  
  Lu Wang, Mayukh Das, Fangkai Yang, Bo Qiao, Hang Dong, Si Qin, Victor Ruehle, Chetan Bansal, Eli Cortez, Íñigo Goiri, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  MLSys’25 | May 2025
  
  Publication
- AIOpsLab: A Holistic Framework for Evaluating AI Agents for Enabling Autonomous Cloud
  
  Yinfang Chen, Manish Shetty, Gagan Somashekar, Minghua Ma, Yogesh Simmhan, Jonathan Mace, Chetan Bansal, Rujia Wang, Saravan Rajmohan
  
  MLSys ’25 | May 2025
  
  Publication
- Towards Cloud Efficiency with Large-scale Workload Characterization
  
  A. Parayil, Jue Zhang, Xiaoting Qin, Íñigo Goiri, Chetan Bansal
  
  ICPE | May 2025
  
  Preprint
- Time Warp: The Gap Between Developers’ Ideal vs Actual Workweeks in an AI-Driven Era
  
  Sukrit Kumar, Drishti Goel, Tom Zimmermann, Brian Houck, B. Ashok, Chetan Bansal
  
  ICSE SEIP ’25 | April 2025
  
  Distinguished Paper Award
  
  Preprint
- RuAG: Learned-rule-augmented Generation for Large Language Models
  
  Yudi Zhang, Pei Xiao, Lu Wang, Chaoyun Zhang, Meng Fang, Yali Du, Yevgeniy Puzyrev, Randolph Yao, Si Qin, Qingwei Lin 林庆维, Mykola Pechenizkiy, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  ICLR’25 | April 2025
  
  Publication
- Performance Aware LLM Load Balancer for Mixed Workloads
  
  Kunal Jain, A. Parayil, Ankur Mallick, Esha Choukse, Xiaoting Qin, Jue Zhang, Íñigo Goiri, Rujia Wang, Chetan Bansal, Victor Ruehle, Anoop Kulkarni, Steve Kofsky, Saravan Rajmohan
  
  EuroMLSys 2025 | April 2025
  
  Publication Project
- Building AI Agents for Autonomous Clouds: Challenges and Design Principles
  
  Manisha M Shetty, Yinfang Chen, Gagan Somashekar, Minghua Ma, Yogesh L. Simmhan, Xuchao Zhang, Jonathan Mace, Pedro Las-Casas, Shachee Mishra Gupta, Suman Nath, Chetan Bansal, Saravan Rajmohan
  
  2024 Symposium on Cloud Computing | November 2024
  
  Publication
- AutoRAG-HP: Automatic Online Hyper-Parameter Tuning for Retrieval-Augmented Generation
  
  Jia Fu, Xiaoting Qin, Fangkai Yang, Lu Wang, Jue Zhang, Qingwei Lin 林庆维, Yubo Chen, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  EMNLP’24 | November 2024
  
  Preprint
- Hybrid-RACA: Hybrid Retrieval-Augmented Composition Assistance for Real-time Text Prediction
  
  Menglin Xia, Xuchao Zhang, Camille Couturier, Guoqing Zheng, Saravan Rajmohan, Victor Ruehle
  
  EMNLP 2024 Industry Track | November 2024
  
  Preprint
- Navigating the Unknown: A Chat-Based Collaborative Interface for Personalized Exploratory Tasks
  
  Yingzhe Peng, Xiaoting Qin, Zhiyang Zhang, Jue Zhang, Qingwei Lin 林庆维, Xu Yang, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  IUI’25 | October 2024
  
  Publication
- Can We Trust Auto-Mitigation? Improving Cloud Failure Prediction with Uncertain Positive Learning
  
  Haozhe Li, Minghua Ma, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  2024 International Symposium on Software Reliability Engineering | October 2024
  
  Publication
- Early Bird: Ensuring Reliability of Cloud Systems Through Early Failure Prediction
  
  Yudong Liu, Minghua Ma, Pu Zhao, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  2024 International Symposium on Software Reliability Engineering | October 2024
  
  Publication
- COIN: Chance-Constrained Imitation Learning for Safe and Adaptive Resource Oversubscription under Uncertainty
  
  Lu Wang, Mayukh Das, Fangkai Yang, Chao Du, Bo Qiao, Hang Dong, Chetan Bansal, Si Qin, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang, Qi Zhang
  
  CIKM’24 | October 2024
  
  PDF
- Large Language Models Can Provide Accurate and Interpretable Incident Triage
  
  Zexin Wang, Minghua Ma, Ze Li, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  2024 International Symposium on Software Reliability Engineering | August 2024
  
  Publication
- Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4
  
  Xuchao Zhang, Supriyo GHOSH, Chetan Bansal, Rujia Wang, Minghua Ma, Yu Kang, Saravan Rajmohan
  
  Foundations of Software Engineering (FSE) | July 2024
  
  Publication
- X-lifecycle Learning for Cloud Incident Management using LLMs
  
  Drishti Goel, Fiza Husain, Aditya Singh, Supriyo GHOSH, A. Parayil, Chetan Bansal, Xuchao Zhang, Saravan Rajmohan
  
  Foundations of Software Engineering (FSE) | July 2024
  
  Publication
- MonitorAssistant: Simplifying Cloud Service Monitoring via Large Language Models
  
  Zhaoyang Yu, Minghua Ma, Chaoyun Zhang, Si Qin, Yu Kang, Chetan Bansal, Saravan Rajmohan, Yingnong Dang, Changhua Pei, Dan Pei, Qingwei Lin 林庆维, Dongmei Zhang
  
  Foundations of Software Engineering (FSE) | July 2024
  
  DOI Publication
- MonitorAssistant: Simplifying Cloud Service Monitoring via Large Language Models
  
  Zhaoyang Yu, Minghua Ma, Chaoyun Zhang, Si Qin, Yu Kang, Chetan Bansal, Saravan Rajmohan, Yingnong Dang, Changhua Pei, Dan Pei, Qingwei Lin 林庆维, Dongmei Zhang
  
  ESEC/FSE’24 Industry Track | July 2024
  
  Publication Publication
- Exploring LLM-based Agents for Root Cause Analysis
  
  Devjeet Roy, Xuchao Zhang, Rashi Bhave, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, Saravan Rajmohan
  
  FSE ’24: 32nd ACM International Conference on the Foundations of Software Engineering | July 2024
  
  Publication Project
- CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models
  
  Peng Xia, Ze Chen, Juanxi Tian, Yangrui Gong, Ruibo Hou, Yue Xu, Zhenbang Wu, Zhiyuan Fan, Yiyang Zhou, Kangyu Zhu, Wenhao Zheng, Zhaoyang Wang, Xiao Wang, Xuchao Zhang, Chetan Bansal, Marc Niethammer, Junzhou Huang, Hongtu Zhu, Yun Li, Jimeng Sun, Zongyuan Ge, Gang Li, James Zou, Huaxiu Yao
  
  NeurIPS 2024 | June 2024
  
  DOI Publication Publication
- Designing Cloud Servers for Lower Carbon
  
  Jaylen Wang, Daniel S. Berger, Fiodar Kazhamiaka, Celine Irvene, Chaojie Zhang, Esha Choukse, Kali Frost, Rodrigo Fonseca, Brijesh Warrier, Chetan Bansal, Jonathan Stern, Ricardo Bianchini, Akshitha Sriraman
  
  ISCA | June 2024
  
  Publication
- SmartOClock: Workload- and Risk-Aware Overclocking in the Cloud
  
  Jovan Stojkovic, Pulkit Misra, Íñigo Goiri, Sam Whitlock, Esha Choukse, Mayukh Das, Chetan Bansal, Jason Lee, Zoey Sun, Haoran Qiu, Reed Zimmermann, Savyasachi Samal, Brijesh Warrier, Ashish Raniwala, Ricardo Bianchini
  
  ISCA | June 2024
  
  Publication
- Dependency Aware Incident Linking in Large Cloud Systems
  
  Supriyo GHOSH, Karish Grover, Jimmy Wong, Chetan Bansal, Rakesh Namineni, Mohit Verma, Saravan Rajmohan
  
  The Web Conference (WWW) | May 2024
  
  Publication
- Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
  
  Xinyu Tang, Richard Shin, Huseyin Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Robert Sim
  
  ICLR 2024 | May 2024
  
  Publication Publication Github Projet
- Intelligent Overclocking for Improved Cloud Efficiency
  
  Aditya Soni, Mayukh Das, Pulkit Misra, Chetan Bansal
  
  AIOps ’24 workshop @ ASPLOS [5th International Workshop on Cloud Intelligence / AIOps] | April 2024
  
  Preprint
- Automatic Root Cause Analysis via Large Language Models for Cloud Incidents
  
  Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xue‐Chao Gao, Hao Fan, Ming Wen, Jun Zeng, Supriyo GHOSH, Xuchao Zhang, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang
  
  EuroSys’24 | April 2024
  
  Publication
- Intelligent Monitoring Framework for Cloud Services: A Data-Driven Approach
  
  Pooja Srinivas, Fiza Husain, A. Parayil, Ayush Choure, Chetan Bansal, Saravan Rajmohan
  
  46th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP’24) | April 2024
  
  Preprint
- OPPerTune: Post-Deployment Configuration Tuning of Services Made Easy
  
  Gagan Somashekar, Karan Tandon, Anush Kini, Chieh-Chun Chang, Petr Husak, Ranjita Bhagwan, Mayukh Das, Anshul Gandhi, Nagarajan Natarajan
  
  NSDI 2024 | April 2024
  
  Publication Publication Github Project Project
- Predict; Don’t React for Enabling Efficient Fine-Grain DVFS in GPUs
  
  Srikant Bharadwaj, Shomit Das, K. Mazumdar, Bradford M. Beckmann, Stephen Kosonocky
  
  Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems | March 2024
  
  Publication DOI Publication
- LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
  
  Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, Menglin Xia, Xufang Luo, Jue Zhang, Qingwei Lin 林庆维, Victor Ruehle, Yuqing Yang, Chin-Yew Lin, H. Vicky Zhao, Lili Qiu, Dongmei Zhang
  
  The 62nd Annual Meeting of the Association for Computational Linguistics (Findings of ACL 2024) | March 2024
  
  Preprint Project
- Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing
  
  Dujian Ding, Ankur Mallick, Chi Wang, Robert Sim, Subhabrata Mukherjee, Victor Ruehle, Laks V. S. Lakshmanan, Ahmed Awadallah
  
  ICLR 2024 | February 2024
  
  Publication
- Revisiting VAE for Unsupervised Time Series Anomaly Detection: A Frequency Perspective
  
  Zexin Wang, Changhua Pei, Minghua Ma, Xin Wang, Zhihan Li, Dan Pei, Saravan Rajmohan, Dongmei Zhang, Qingwei Lin 林庆维, Haiming Zhang, Jianhui Li, Gaogang Xie
  
  TheWebConf’24 | February 2024
  
  DOI Publication
- NASerEx: Optimizing Early Exits via AutoML for Scalable Efficient Inference in Big Image Streams
  
  Aakash Kapoor, Rajath Elias Soans, Soham Dixit, Pradeep NS, Brijraj Singh, Mayukh Das
  
  IEEE Big Data 2023 | December 2023
  
  Special session on Machine Learning on Big Data (MLBD)
  
  Publication
- Training Private and Efficient Language Models with Synthetic Data from LLMs
  
  Da Yu, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Janardhan (Jana) Kulkarni, Zinan Lin, Chulin Xie, Huishuai Zhang, Wanrong Zhang
  
  NeurIPS 2023 SoLaR Workshop | December 2023
  
  Publication Project
- Detection Is Better Than Cure: A Cloud Incidents Perspective
  
  A. Parayil, Supriyo GHOSH, Yu Kang, Minghua Ma, Chetan Bansal, Suman Nath, Jonathan Mace, Vaibhav Ganatra
  
  ESEC/FSE 2023: Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering | November 2023
  
  Publication
- Secure Floating-Point Training
  
  Deevashwer Rathee, Anwesh Bhattacharya, Divya Gupta, Rahul Sharma, Dawn Song
  
  Usenix Security Symposium 2023 | August 2023
  
  Publication Project
- Bayesian Estimation of Differential Privacy
  
  Santiago Zanella-Béguelin, Lukas Wutschitz, Shruti Tople, Ahmed Salem, Victor Ruehle, Andrew Paverd, Mohammad Naseri, Boris Köpf, Daniel Jones
  
  2023 International Conference on Machine Learning | July 2023
  
  Editor(s): Barbara Engelhardt, Emma Brunskill, Kyunghyun Cho
  
  Publication Project
- How Different are the Cloud Workloads? Characterizing Large-Scale Private and Public Cloud Workloads
  
  Xiaoting Qin, Minghua Ma, Yueng Zhao, Jue Zhang, Chao Du, Yudong Liu, A. Parayil, Chetan Bansal, Saravan Rajmohan, Íñigo Goiri, Eli Cortez, Si Qin, Qingwei Lin 林庆维, Dongmei Zhang
  
  DSN’23 | June 2023
  
  Publication
- Analyzing Leakage of Personally Identifiable Information in Language Models
  
  Nils Lukas, Ahmed Salem, Robert Sim, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin
  
  2023 IEEE Symposium on Security and Privacy | May 2023
  
  Publication PDF DOI Project
- SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning
  
  Ahmed Salem, Giovanni Cherubin, David Evans, Boris Köpf, Andrew Paverd, Anshuman Suri, Shruti Tople, Santiago Zanella-Béguelin
  
  2023 IEEE Symposium on Security and Privacy | May 2023
  
  Publication PDF DOI Project
- Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
  
  Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan (Jana) Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian
  
  International Conference on Learning Representations (ICLR) 2023 | May 2023
  
  Publication Projet
- Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models
  
  Toufique Ahmed, Supriyo GHOSH, Chetan Bansal, Tom Zimmermann, Xuchao Zhang, Saravan Rajmohan
  
  ICSE 2023 | May 2023
  
  Publication
- Snape: Reliable and Low-Cost Computing with Mixture of Spot and On-Demand VMs
  
  Fangkai Yang, Lu Wang, Zhenyu Xu, Jue Zhang, Liqun Li, Bo Qiao, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Terry Yang, Victor Ruehle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  ASPLOS’23 | March 2023
  
  Publication
- Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler
  
  Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Rouqi Shen, Kevin Tian
  
  COLT 2023 | February 2023
  
  Publication Project
- Differentially Private Model Compression
  
  Fatemehsadat Mireshghallah, Arturs Backurs, Huseyin Inan, Lukas Wutschitz, Janardhan (Jana) Kulkarni
  
  NeurIPS 2022 | November 2022
  
  Publication Project
- When does differentially private learning not suffer in high dimensions?
  
  Xuechen Li, Daogao Liu, Tatsunori Hashimoto, Huseyin Inan, Janardhan (Jana) Kulkarni, Yin Tat Lee, Abhradeep Guha Thakurta
  
  NeurIPS’22 | November 2022
  
  Publication Projet
- AutoTSG: Learning and Synthesis for Incident Troubleshooting
  
  Manish Shetty, Chetan Bansal, Sai Pramod Upadhyayula, Arjun Radhakrishna, Anurag Gupta
  
  ESEC/FSE 2022 | November 2022
  
  Publication Publication Publication
- Membership Inference Attacks and Generalization: A Causal Perspective
  
  Teodora Baluta, Shiqi Shen, S. Hitarth, Shruti Tople, Prateek Saxena
  
  Computer and Communications Security (CCS) | November 2022
  
  Publication Projet
- How to Fight Production Incidents? An Empirical Study on a Large-scale Cloud Service
  
  Supriyo GHOSH, Manish Shetty, Chetan Bansal, Suman Nath
  
  SoCC 2022 | November 2022
  
  Best Paper Award
  
  Publication PDF Project
- Multi-task Hierarchical Classification for Disk Failure Prediction in Online Service Systems
  
  Yudong Liu, Hailan Yang, Pu Zhao, Minghua Ma, Chengwu Wen, Hongyu Zhang, Chuan Luo, Qingwei Lin 林庆维, Chang Yi, Jiaojian Wang, Chenjian Zhang, Paul Wang, Yingnong Dang, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD 2022 | August 2022
  
  DOI Publication Project Project
- Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach
  
  Jie Yan, Yunlei Lu, Liting Chen, Si Qin, Yixin Fang, Qingwei Lin 林庆维, Thomas Moscibroda, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD’22 | August 2022
  
  Publication Project Project
- AutoCoMet: Smart Neural Architecture Search via Co-Regulated Shaping Reinforcement
  
  Mayukh Das, Brijraj Singh, Harsh Kanti Chheda, Pawan Sharma, Pradeep NS
  
  ICPR | August 2022
  
  Publication
- NENYA: Cascade Reinforcement Learning for Cost-Aware Failure Mitigation at Microsoft 365
  
  Lu Wang, Pu Zhao, Chao Du, Chuan Luo, Mengna Su, Fangkai Yang, Yudong Liu, Qingwei Lin 林庆维, Min Wang, Yingnong Dang, Hongyu Zhang, Saravan Rajmohan, Dongmei Zhang
  
  SIGKDD 2022 | August 2022
  
  Publication Project Project
- Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning
  
  Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, Dimitrios Dimitriadis
  
  IJCAI-ECAI’22 | August 2022
  
  Publication Projet
- SIMC: ML Inference Secure Against Malicious Clients at Semi-Honest Cost
  
  Nishanth Chandran, Divya Gupta, Sai Lakshmi Bhavana Obbattu, Akash Shah
  
  USENIX Security | August 2022
  
  USENIX Security 2022
  
  Publication Project
- UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis
  
  Fatemehsadat Mireshghallah, Vaishnavi Shrivastava, Milad Shokouhi, Taylor Berg-Kirkpatrick, Robert Sim, Dimitrios Dimitriadis
  
  2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL’22) | July 2022
  
  Publication Project
- Private Convex Optimization in General Norms
  
  Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Rouqi Shen, Kevin Tian
  
  SODA 2023 | July 2022
  
  Publication Projet
- Circuit-PSI with Linear Complexity via Relaxed Batch OPPRF
  
  Nishanth Chandran, Divya Gupta, Akash Shah
  
  22nd Privacy Enhancing Technologies Symposium (PETS 2022) | June 2022
  
  Publication Project
- SECFLOAT: Accurate Floating-Point meets Secure 2-Party Computation
  
  Deevashwer Rathee, Anwesh Bhattacharya, Rahul Sharma, Divya Gupta, Nishanth Chandran, Aseem Rastogi
  
  43rd IEEE Symposium on Security and Privacy (IEEE S&P 2022) | May 2022
  
  Publication Project
- DeepAnalyze: Learning to Localize Crashes at Scale
  
  Manish Shetty, Chetan Bansal, Suman Nath, Sean Bowles, Henry Wang, Ozgur Arman, Siamak Ahari
  
  ICSE 2022 | May 2022
  
  Publication Project
- Spot Virtual Machine Eviction Prediction in Microsoft Cloud
  
  Fangkai Yang, Bowen Pang, Jue Zhang, Bo Qiao, Lu Wang, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Senthil Baladhandayutham, Victor Rühle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  WWW’22 Companion | April 2022
  
  Publication
- Differentially private fine-tuning of language models
  
  Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Gautam Kamath, Janardhan (Jana) Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang
  
  ICLR 2022 | April 2022
  
  Publication Projet
- Private Convex Optimization via Exponential Mechanism
  
  Sivakanth Gopi, Yin Tat Lee, Daogao Liu
  
  COLT 2022 | March 2022
  
  Publication Project
- HALO: Hierarchy-aware Fault Localization for Cloud Systems
  
  Xu Zhang, Chao Du, Yifan Li, Yong Xu, Hongyu Zhang, Si Qin, Ze Li, Qingwei Lin 林庆维, Yingnong Dang, Andrew Zhou, Saravanakumar Rajmohan, Dongmei Zhang
  
  SigKDD’21 Applied Data Science Track | October 2021
  
  Publication PDF Projet Projet
- How Long Will it Take to Mitigate this Incident for Online Service Systems?
  
  Weijing Wang, Junjie Chen, Lin Yang, Hongyu Zhang, Pu Zhao, Bo Qiao, Yu Kang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Feng Gao, Zhangwei Xu, Yingnong Dang, Dongmei Zhang
  
  ISSRE’21 | September 2021
  
  Best Research Paper
  
  Publication Projet Projet
- Intelligent container reallocation at Microsoft 365
  
  Bo Qiao, Fangkai Yang, Chuan Luo, Yanan Wang, Johnny Li, Qingwei Lin 林庆维, Hongyu Zhang, Mohit Datta, Andrew Zhou, Thomas Moscibroda, Saravanakumar Rajmohan, Dongmei Zhang
  
  2021 Foundations of Software Engineering | August 2021
  
  DOI Projet Projet
- Fighting the Fog of War: Automated Incident Detection for Cloud Systems
  
  Liqun Li, Xu Zhang, Xin Zhao, Hongyu Zhang, Yu Kang, Pu Zhao, Bo Qiao, Shilin He, Pochian Lee, Jeffrey Sun, Feng Gao, Li Yang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Zhangwei Xu, Dongmei Zhang
  
  2021 USENIX Annual Technical Conference (USENIX ATC’21) | August 2021
  
  Publication Project Project
- Neural Knowledge Extraction From Cloud Service Incidents
  
  Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan, Tom Zimmermann
  
  43rd International Conference on Software Engineering (ICSE ’21) – SEIP Track | May 2021
- Correlation-Aware Heuristic Search for Intelligent Virtual Machine Provisioning in Cloud Systems
  
  Chuan Luo, Bo Qiao, Wenqian Xing, Xin Chen, Pu Zhao, Chao Du, Randolph Yao, Hongyu Zhang, Wei Wu, Shaowei Cai, Saravanakumar Rajmohan, Qingwei Lin 林庆维
  
  AAAI’21 | March 2021
  
  Publication Projet Projet Projet
- PULNS: Positive-Unlabeled Learning with Effective Negative Sample Selector
  
  Chuan Luo, …, Qingwei Lin 林庆维
  
  AAAI’21 | March 2021
  
  Publication Projet
- NTAM: Neighborhood-Temporal Attention Model for Disk Failure Prediction in Cloud Platforms
  
  Chuan Luo, Pu Zhao, …, Qingwei Lin 林庆维, …
  
  WWW (TheWebConf) 2021 | February 2021
  
  Publication Project Project Project
- DeCaf: Diagnosing and Triaging Performance Issues in Large-Scale Cloud Services
  
  Chetan Bansal, Sundararajan Renganathan, Ashima Asudani, Olivier Midy, Mathru Janakiraman
  
  ICSE 2020 | May 2020
  
  PDF Project
- Rex: Preventing Bugs and Misconfiguration in Large Services using Correlated Change Analysis
  
  Sonu Mehta, Ranjita Bhagwan, Rahul Kumar, B. Ashok, Chetan Bansal, Chandra Maddila, Christian Bird, Sumit Asthana, Aditya Kumar
  
  Networked System Design and Implementation (NSDI) | February 2020
  
  Publication Project
- WhoDo: Automating Reviewer Suggestions at Scale
  
  Sumit Asthana, Rahul Kumar, Ranjita Bhagwan, Chetan Bansal, Christian Bird, Chandra Maddila, Sonu Mehta, B. Ashok
  
  ESEC/FSE 2019 | August 2019
  
  Publication Projet
- Predicting Pull Request Completion Time: A Case Study on Large Scale Cloud Services
  
  Chandra Maddila, Chetan Bansal, Nachi Nagappan
  
  ESEC/FSE 2019 | August 2019
  
  Publication Project
- Building sankie: an AI platform for DevOps
  
  Rahul Kumar, Chetan Bansal, Chandra Maddila, Nitin Sharma, Shawn Martelock, Ravi Bhargava
  
  1st International Workshop on Bots in Software Engineering (BotSE ’19) | May 2019
  
  Publication Project
- FastLane: Test Minimization for Rapidly Deployed Large-scale Online Services
  
  Ranjita Bhagwan, Adithya Philip, Rahul Kumar, Chandra Maddila, Nachi Nagappan
  
  International Conference on Software Engineering | May 2019
  
  Publication Project
- EzPC: Programmable, Efficient, and Scalable Secure Two-Party Computation for Machine Learning
  
  Nishanth Chandran, Divya Gupta, Aseem Rastogi, Rahul Sharma, Shardul Tripathi
  
  IEEE European Symposium on Security and Privacy | February 2019
  
  Publication Vidéo Github Projet
- Orca: Differential Bug Localization in Large-Scale Services
  
  Ranjita Bhagwan, Rahul Kumar, Chandra Maddila, Adithya Abraham Philip
  
  13th USENIX Symposium on Operating Systems Design and Implementation | October 2018
  
  Won the Jay Lepreau Best Paper Award
  
  Publication Projet
- Serving Models, Fast and Slow:Optimizing Heterogeneous LLM Inferencing Workloads at Scale
  
  Kunal Jain, A. Parayil, Ankur Mallick, Rujia Wang, Renee St. Amant, Chetan Bansal, Victor Ruehle, Saravan Rajmohan, Shashwat Jaiswal, Yogesh Simmhan, Anoop Kulkarni, Steve Kofsky
  
  ArXiv | February 2025
  
  Publication
- MEETING DELEGATE: Benchmarking LLMs on Attending Meetings on Our Behalf
  
  Lingxiang Hu, Shurun Yuan, Xiaoting Qin, Jue Zhang, Qingwei Lin 林庆维, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  February 2025
  
  Publication
- Enabling Autonomic Microservice Management through Self-Learning Agents
  
  Fenglin Yu, Fangkai Yang, Xiaoting Qin, Zhiyang Zhang, Jue Zhang, Qingwei Lin 林庆维, Hongyu Zhang, Yingnong Dang, Saravan Rajmohan, Dongmei Zhang, Qi Zhang
  
  January 2025
  
  Preprint
- TurboAttention: Efficient Attention Approximation For High Throughputs LLMs
  
  Hao Kang, Srikant Bharadwaj, James Hensman, Tushar Krishna, Victor Ruehle, Saravan Rajmohan
  
  ArXiv | December 2024, Vol abs/2412.08585
  
  DOI Publication Publication
- Ensuring Fair LLM Serving Amid Diverse Applications
  
  Kunal Jain, Ankur Mallick, A. Parayil, Renee St. Amant, Rujia Wang, Victor Ruehle, Chetan Bansal, Saravan Rajmohan, Redwan Ibne Seraj Khan, Haiying Shen, Anoop Kulkarni, Steve Kofsky, Pankhuri Choudhary, Yue Cheng
  
  ArXiv | November 2024
  
  Publication
- Sharingan: Extract user action sequence from desktop recordings
  
  Yanting Chen, Yi Ren, Xiaoting Qin, Jue Zhang, Kehong Yuan, Lu Han, Qingwei Lin 林庆维, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  November 2024
  
  Preprint
- AI Delegates with a Dual Focus: Ensuring Privacy and Strategic Self-Disclosure
  
  Xi Chen, Zhiyang Zhang, Fangkai Yang, Xiaoting Qin, Chao Du, Xi Cheng, Hangxin Liu, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang, Qi Zhang
  
  September 2024
  
  Preprint
- Intelligent Router for LLM Workloads: Improving Performance Through Workload-Aware Scheduling
  
  A. Parayil, Ankur Mallick, Esha Choukse, Xiaoting Qin, Jue Zhang, Íñigo Goiri, Rujia Wang, Chetan Bansal, Victor Ruehle, Saravan Rajmohan, Kunal Jain, Anoop Kulkarni, Steve Kofsky
  
  ArXiv | August 2024, Vol abs/2408.13510
  
  Preprint
- The Vision of Autonomic Computing: Can LLMs Make It a Reality?
  
  Zhiyang Zhang, Fangkai Yang, Xiaoting Qin, Jue Zhang, Qingwei Lin 林庆维, Gong Cheng, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
  
  July 2024
  
  Preprint
- Workload Intelligence: Punching Holes Through the Cloud Abstraction
  
  Lexiang Huang, A. Parayil, Jue Zhang, Xiaoting Qin, Chetan Bansal, Jovan Stojkovic, Pantea Zardoshti, Pulkit Misra, Eli Cortez, Raphael Ghelman, Íñigo Goiri, Saravan Rajmohan, Jim Kleewein, Rodrigo Fonseca, Timothy Zhu, Ricardo Bianchini
  
  ArXiv | April 2024, Vol abs/2404.19143
  
  Preprint
- Workload Intelligence: Punching Holes Through the Cloud Abstraction
  
  Lexiang Huang, A. Parayil, Jue Zhang, Xiaoting Qin, Chetan Bansal, Jovan Stojkovic, Pantea Zardoshti, Pulkit Misra, Eli Cortez, Raphael Ghelman, Íñigo Goiri, Saravan Rajmohan, Jim Kleewein, Rodrigo Fonseca, Timothy Zhu, Ricardo Bianchini
  
  April 2024
  
  Preprint
- Advancing differential privacy: where we are now and future directions for real-world deployment
  
  Rachel Cummings, Damien Desfontaines, David Evans, Roxana Geambasu, Yangsibo Huang, Matthew Jagielski, Peter Kairouz, Gautam Kamath, Sewoong Oh, Olga Ohrimenko, Nicolas Papernot, Ryan Rogers, Milan Shen, Shuang Song, Weijie Su, Andreas Terzis, Abhradeep Thakurta, Sergei Vassilvitskii, Yu-Xiang Wang, Li Xiong, Da Yu, Sergey Yekhanin, Huanyu Zhang, Wanrong Zhang
  
  Harvard Data Science Review | January 2024, Vol 6(1)
  
  Publication Project
- Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation
  
  Ruomeng Ding, Chaoyun Zhang, Lu Wang, Yong Xu, Minghua Ma, Wei Zhang, Si Qin, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  ArXiv | November 2023, Vol abs/2311.04254
  
  DOI Publication Publication
- Sweeping Heterogeneity with Smart MoPs: Mixture of Prompts for LLM Task Adaptation
  
  Chen Dun, Mirian Hipolito Garcia, Guoqing Zheng, Ahmed Awadallah, Anastasios Kyrillidis, Robert Sim
  
  ArXiv | October 2023, Vol abs/2310.02842
  
  DOI Publication Publication Publication
- Personalized Federated Learning with Adaptive Batchnorm for Healthcare
  
  Wang Lu, Jindong Wang, Yiqiang Chen, Xin Qin, Renjun Xu, Dimitrios Dimitriadis, Tao Qin
  
  IEEE Transactions on Big Data | May 2022
  
  Preprint Publication Projet
- SoftNER: Mining knowledge graphs from Cloud Incidents
  
  Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan
  
  Empirical Software Engineering | April 2022, Vol 27(4)
  
  Publication
- The Canary’s Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
  
  Matthieu Meeus, Lukas Wutschitz, Santiago Zanella-Béguelin, Reza Shokri, Shruti Tople
  
  February 2025
  
  DOI Preprint Project
- Towards Efficient Large Multimodal Model Serving
  
  Haoran Qiu, Anish Biswas, Zihan Zhao, Jayashree Mohan, Alind Khare, Esha Choukse, Íñigo Goiri, Zeyu Zhang, Haiying Shen, Chetan Bansal, Ramachandran Ramjee, Rodrigo Fonseca
  
  February 2025
  
  Preprint Project Project
- FLASH: A Workflow Automation Agent for Diagnosing Recurring Incidents
  
  Xuchao Zhang, Tanish Mittal, Chetan Bansal, Rujia Wang, Minghua Ma, Zhixin Ren, Hao Huang, Saravan Rajmohan
  
  October 2024
  
  Publication Project
- PACE-LM: Prompting and Augmentation for Calibrated Confidence Estimation with GPT-4 in Cloud Incident Root Cause Analysis
  
  Dylan Zhang, Xuchao Zhang, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, Saravan Rajmohan
  
  September 2023
  
  Publication
- dp-transformers: Training transformer models with differential privacy
  
  Huseyin Inan, Andre Manoel, Lukas Wutschitz
  
  July 2022
  
  Publication Project
- LeanAttention: Hardware-Aware Scalable Attention Mechanism for the Decode-Phase of Transformers
  
  Rya Sanovar, Srikant Bharadwaj, Renee St. Amant, Victor Ruehle, Saravan Rajmohan
  
  May 2024
  
  Publication
- FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations
  
  Dimitrios Dimitriadis, Mirian Hipolito Garcia, Daniel Madrigal, Andre Manoel, Robert Sim
  
  March 2022
  
  Preprint Github Project
- Project Florida: Federated Learning Made Easy
  
  Daniel Madrigal, Andre Manoel, Jialei Chen, Nalin Singal, Robert Sim
  
  | July 2023
  
  Published by Microsoft
  
  Publication Project