Chetan Bansal
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
47
Venues
24
Active years
2009–2026
Best venue rank
A*
Where they publish
- A*ICSE7 papers
- A*ACL4 papers
- AISSRE4 papers
- BCLOUD3 papers
- A*KDD3 papers
- ACIKM3 papers
- A*ASPLOS2 papers
- A*ICLR2 papers
- A*ISCA2 papers
- A*WWW2 papers
- AESEM2 papers
- A*SIGMETRICS1 paper
- A*ICML1 paper
- ANAACL1 paper
- ASC1 paper
- ADSN1 paper
- AUSENIX1 paper
- AMSR1 paper
- BFMCAD1 paper
- NationalNSDI1 paper
- A*SIGIR1 paper
- BIFM1 paper
- UnrankedSEC1 paper
- CISCAS1 paper
Papers
47 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | Learning Optimal Message Representations for Agentic Communication. | Shashwat Gupta, Anson Bastos, Mayukh Das, Supriyo Ghosh, Nagarajan Natarajan, Chetan Bansal, Saravan Rajmohan |
| 2026 | ACL | SynthAgent: Adapting Web Agents with Synthetic Supervision. | Zhaoyang Wang, Yiming Liang, Xuchao Zhang, Qianhui Wu, Siwei Han, Anson Bastos, Rujia Wang, Chetan Bansal, Baolin Peng, Jianfeng Gao, Saravan Rajmohan, Huaxiu Yao |
| 2026 | SIGMETRICS | SageServe: Optimizing LLM Serving on Cloud Data Centers with Forecast Aware Auto-Scaling. | Shashwat Jaiswal, Kunal Jain, Yogesh Simmhan, Anjaly Parayil, Ankur Mallick, Rujia Wang, Rene St. Amant, Chetan Bansal, Victor Rhle, Anoop Kulkarni, Steve Kofsky, Saravan Rajmohan |
| 2025 | ACL | CARMO: Dynamic Criteria Generation for Context Aware Reward Modelling. | Taneesh Gupta, Shivam Shandilya, Xuchao Zhang, Rahul Madhavan, Supriyo Ghosh, Chetan Bansal, Huaxiu Yao, Saravan Rajmohan |
| 2025 | ACL | Synergistic Weak-Strong Collaboration by Aligning Preferences. | Yizhu Jiao, Xuchao Zhang, Zhaoyang Wang, Yubo Ma, Zhun Deng, Rujia Wang, Chetan Bansal, Saravan Rajmohan, Jiawei Han, Huaxiu Yao |
| 2025 | ASPLOS | Coach: Exploiting Temporal Patterns for All-Resource Oversubscription in Cloud Platforms. | Benjamin Reidys, Pantea Zardoshti, igo Goiri, Celine Irvene, Daniel S. Berger, Haoran Ma, Kapil Arya, Eli Cortez, Taylor Stark, Eugene Bak, Mehmet Iyigun, Stanko Novakovic, Lisa Hsu, Karel Trueba, Abhisek Pan, Chetan Bansal, Saravan Rajmohan, Jian Huang, Ricardo Bianchini |
| 2025 | CLOUD | ModServe: Modality- and Stage-Aware Resource Disaggregation for Scalable Multimodal Model Serving. | Haoran Qiu, Anish Biswas, Zihan Zhao, Jayashree Mohan, Alind Khare, Esha Choukse, igo Goiri, Zeyu Zhang, Haiying Shen, Chetan Bansal, Ramachandran Ramjee, Rodrigo Fonseca |
| 2025 | ICLR | CREAM: Consistency Regularized Self-Rewarding Language Models. | Zhaoyang Wang, Weilei He, Zhiyuan Liang, Xuchao Zhang, Chetan Bansal, Ying Wei, Weitong Zhang, Huaxiu Yao |
| 2025 | ICLR | Anyprefer: An Agentic Framework for Preference Data Synthesis. | Yiyang Zhou, Zhaoyang Wang, Tianle Wang, Shangyu Xing, Peng Xia, Bo Li, Kaiyuan Zheng, Zijian Zhang, Zhaorun Chen, Wenhao Zheng, Xuchao Zhang, Chetan Bansal, Weitong Zhang, Ying Wei, Mohit Bansal, Huaxiu Yao |
| 2025 | ICML | AMPO: Active Multi Preference Optimization for Self-play Preference Selection. | Taneesh Gupta, Rahul Madhavan, Xuchao Zhang, Chetan Bansal, Saravan Rajmohan |
| 2025 | ICSE | Automated Service Design with Cerulean (Project Showcase). | Vaastav Anand, Alok Gautam Kumbhare, Celine Irvene, Chetan Bansal, Gagan Somashekar, Jonathan Mace, Pedro Henrique B. Las-Casas, Ricardo Bianchini, Rodrigo Fonseca |
| 2025 | ISSRE | An Empirical Study of Production Incidents in Generative AI Cloud Services. | Haoran Yan, Yinfang Chen, Minghua Ma, Ming Wen, Shan Lu, Shenglin Zhang, Tianyin Xu, Rujia Wang, Chetan Bansal, Saravan Rajmohan, Qingwei Lin, Chaoyun Zhang, Dongmei Zhang |
| 2025 | KDD | Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection. | Jun Liu, Chaoyun Zhang, Jiaxu Qian, Minghua Ma, Si Qin, Chetan Bansal, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang |
| 2025 | NAACL | Verifiable Format Control for Large Language Model Generations. | Zhaoyang Wang, Jinqi Jiang, Huichi Zhou, Wenhao Zheng, Xuchao Zhang, Chetan Bansal, Huaxiu Yao |
| 2025 | SC | Workload Intelligence: Workload-Aware IaaS abstraction for Cloud Efficiency. | Lexiang Huang, Anjaly Parayil, Jue Zhang, Xiaoting Qin, Chetan Bansal, Jovan Stojkovic, Pantea Zardoshti, Pulkit A. Misra, Eli Cortez, Raphael Ghelman, igo Goiri, Saravan Rajmohan, Jim Kleewein, Rodrigo Fonseca, Timothy Zhu, Ricardo Bianchini |
| 2024 | CIKM | 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, Dongmei Zhang, Qi Zhang |
| 2024 | CLOUD | Building AI Agents for Autonomous Clouds: Challenges and Design Principles. | Manish Shetty, Yinfang Chen, Gagan Somashekar, Minghua Ma, Yogesh Simmhan, Xuchao Zhang, Jonathan Mace, Dax Vandevoorde, Pedro Henrique B. Las-Casas, Shachee Mishra Gupta, Suman Nath, Chetan Bansal, Saravan Rajmohan |
| 2024 | ISCA | SmartOClock: Workload- and Risk-Aware Overclocking in the Cloud. | Jovan Stojkovic, Pulkit A. Misra, igo 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 |
| 2024 | ISCA | 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 |
| 2024 | ICSE | Intelligent Monitoring Framework for Cloud Services: A Data-Driven Approach. | Pooja Srinivas, Fiza Husain, Anjaly Parayil, Ayush Choure, Chetan Bansal, Saravan Rajmohan |
| 2024 | ISSRE | Can We Trust Auto-Mitigation? Improving Cloud Failure Prediction with Uncertain Positive Learning. | Haozhe Li, Minghua Ma, Yudong Liu, Pu Zhao, Shuo Li, Ze Li, Murali Chintalapati, Yingnong Dang, Chetan Bansal, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang |
| 2024 | ISSRE | Early Bird: Ensuring Reliability of Cloud Systems Through Early Failure Prediction. | Yudong Liu, Minghua Ma, Pu Zhao, Tianci Li, Bo Qiao, Shuo Li, Ze Li, Murali Chintalapati, Yingnong Dang, Chetan Bansal, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang |
| 2024 | ISSRE | Large Language Models Can Provide Accurate and Interpretable Incident Triage. | Zexin Wang, Jianhui Li, Minghua Ma, Ze Li, Yu Kang, Chaoyun Zhang, Chetan Bansal, Murali Chintalapati, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang, Changhua Pei, Gaogang Xie |
| 2024 | KDD | Pre-trained KPI Anomaly Detection Model Through Disentangled Transformer. | Zhaoyang Yu, Changhua Pei, Xin Wang, Minghua Ma, Chetan Bansal, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang, Xidao Wen, Jianhui Li, Gaogang Xie, Dan Pei |
| 2024 | WWW | Dependency Aware Incident Linking in Large Cloud Systems. | Supriyo Ghosh, Karish Grover, Jimmy Wong, Chetan Bansal, Rakesh Namineni, Mohit Verma, Saravan Rajmohan |
| 2023 | ASPLOS | 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, igo Goiri, Eli Cortez, Terry Yang, Victor Rhle, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang |
| 2023 | DSN | How Different are the Cloud Workloads? Characterizing Large-Scale Private and Public Cloud Workloads. | Xiaoting Qin, Minghua Ma, Yuheng Zhao, Jue Zhang, Chao Du, Yudong Liu, Anjaly Parayil, Chetan Bansal, Saravan Rajmohan, igo Goiri, Eli Cortez, Si Qin, Qingwei Lin, Dongmei Zhang |
| 2023 | ICSE | Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models. | Toufique Ahmed, Supriyo Ghosh, Chetan Bansal, Thomas Zimmermann, Xuchao Zhang, Saravan Rajmohan |
| 2023 | USENIX | AutoARTS: Taxonomy, Insights and Tools for Root Cause Labelling of Incidents in Microsoft Azure. | Pradeep Dogga, Chetan Bansal, Richard Costleigh, Gopinath Jayagopal, Suman Nath, Xuchao Zhang |
| 2022 | CLOUD | How to fight production incidents?: an empirical study on a large-scale cloud service. | Supriyo Ghosh, Manish Shetty, Chetan Bansal, Suman Nath |
| 2022 | ESEM | Characterizing the Usage of CI Tools in ML Projects. | Dhia Elhaq Rzig, Foyzul Hassan, Chetan Bansal, Nachiappan Nagappan |
| 2022 | ICSE | DeepAnalyze: Learning to Localize Crashes at Scale. | Manish Shetty, Chetan Bansal, Suman Nath, Sean Bowles, Henry Wang, Ozgur Arman, Siamak Ahari |
| 2022 | WWW | 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, Iigo Goiri, Eli Cortez, Senthil Baladhandayutham, Victor Rhle, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang |
| 2021 | ICSE | Neural Knowledge Extraction From Cloud Service Incidents. | Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan, Thomas Zimmermann |
| 2021 | KDD | Micro-climate Prediction - Multi Scale Encoder-decoder based Deep Learning Framework. | Peeyush Kumar, Ranveer Chandra, Chetan Bansal, Shivkumar Kalyanaraman, Tanuja Ganu, Michael Grant |
| 2021 | MSR | Search4Code: Code Search Intent Classification Using Weak Supervision. | Nikitha Rao, Chetan Bansal, Joe Guan |
| 2020 | CIKM | Product Insights: Analyzing Product Intents in Web Search. | Nikitha Rao, Chetan Bansal, Subhabrata Mukherjee, Chandra Shekhar Maddila |
| 2020 | ESEM | An Empirical Study of Software Exceptions in the Field using Search Logs. | Foyzul Hassan, Chetan Bansal, Nachiappan Nagappan, Thomas Zimmermann, Ahmed Hassan Awadallah |
| 2020 | FMCAD | Angelic Checking within Static Driver Verifier: Towards high-precision defects without (modeling) cost. | Shuvendu K. Lahiri, Akash Lal, Sridhar Gopinath, Alexander Nutz, Vladimir Levin, Rahul Kumar, Nate Deisinger, Jakob Lichtenberg, Chetan Bansal |
| 2020 | ICSE | DeCaf: diagnosing and triaging performance issues in large-scale cloud services. | Chetan Bansal, Sundararajan Renganathan, Ashima Asudani, Olivier Midy, Mathru Janakiraman |
| 2020 | NSDI | Rex: Preventing Bugs and Misconfiguration in Large Services Using Correlated Change Analysis. | Sonu Mehta, Ranjita Bhagwan, Rahul Kumar, Chetan Bansal, Chandra Shekhar Maddila, Balasubramanyan Ashok, Sumit Asthana, Christian Bird, Aditya Kumar |
| 2020 | SIGIR | Studying Ransomware Attacks Using Web Search Logs. | Chetan Bansal, Pantazis Deligiannis, Chandra Shekhar Maddila, Nikitha Rao |
| 2019 | ICSE | Building sankie: an AI platform for DevOps. | Rahul Kumar, Chetan Bansal, Chandra Shekhar Maddila, Nitin Sharma, Shawn Martelock, Ravi Bhargava |
| 2016 | CIKM | Hashtag Recommendation for Enterprise Applications. | Dhruv Mahajan, Vishwajit Kolathur, Chetan Bansal, Suresh Parthasarathy, Sundararajan Sellamanickam, S. Sathiya Keerthi, Johannes Gehrke |
| 2016 | IFM | CloudSDV Enabling Static Driver Verifier Using Microsoft Azure. | Rahul Kumar, Thomas Ball, Jakob Lichtenberg, Nate Deisinger, Apoorv Upreti, Chetan Bansal |
| 2015 | SEC | Cache Timing Attacks Revisited: Efficient and Repeatable Browser History, OS and Network Sniffing. | Chetan Bansal, Sren Preibusch, Natasa Milic-Frayling |
| 2009 | ISCAS | Binaural Intensity Comparison in the Echolocating Bat using Synaptic Conductance. | Timothy K. Horiuchi, Chetan Bansal, Tarek M. Massoud |