AIOps 2025 Contributors

Sat 26 April - Sun 4 May 2025 Ottawa, Ontario, Canada

co-located with ICSE 2025

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Results (36)

A Vaastav AnandAnand, Vaastav Automated Service Design with Cerulean (Project Showcase) Towards Using LLMs for Distributed Trace Comparison (Abstract)
B Chetan BansalBansal, Chetan Microsoft ResearchUnited States Automated Service Design with Cerulean (Project Showcase)
Hermann BauerBauer, Hermann University of MichiganUnited States Automated Bug Discovery in Cloud Infrastructure-as-Code Updates with LLM Agents
Zhendong BeiBei, Zhendong HSBCChina Breaking the Cycle of Recurring Failures: Applying Generative AI to Root Cause Analysis in Legacy Banking Systems
Eion BlanchardBlanchard, Eion Microsoft AzureUnited States Orchestrating Cross-Layer Anomaly Detection and Mitigation to Address Gray Failures in Large-Scale Cloud Infrastructure
C Ang ChenChen, Ang University of MichiganUnited States Automated Bug Discovery in Cloud Infrastructure-as-Code Updates with LLM Agents Automated Lifting for Cloud Infrastructure-as-Code Programs
Bichao ChenChen, Bichao HSBCChina Breaking the Cycle of Recurring Failures: Applying Generative AI to Root Cause Analysis in Legacy Banking Systems
Murali ChintalapatiChintalapati, Murali Microsoft AzureUnited States Orchestrating Cross-Layer Anomaly Detection and Mitigation to Address Gray Failures in Large-Scale Cloud Infrastructure
F Rodrigo FonsecaFonseca, Rodrigo Microsoft Research Automated Service Design with Cerulean (Project Showcase) Towards Using LLMs for Distributed Trace Comparison (Abstract)
G Zheng GuoGuo, Zheng University of California, San DiegoUnited States Automated Lifting for Cloud Infrastructure-as-Code Programs
H Wahab Hamou-LhadjHamou-Lhadj, Wahab Concordia University, Montreal, CanadaCanada Keynote2: AIOps in the Era of Large Language Models
Yibo HuangHuang, Yibo University of MichiganUnited States Automated Lifting for Cloud Infrastructure-as-Code Programs
I Celine IrveneIrvene, Celine MicrosoftUnited States Automated Service Design with Cerulean (Project Showcase)
J Siyuan JinJin, Siyuan Hong Kong University of Science and Technology Breaking the Cycle of Recurring Failures: Applying Generative AI to Root Cause Analysis in Legacy Banking Systems
K Antoine KaufmannKaufmann, Antoine MPI-SWSGermany Towards Using LLMs for Distributed Trace Comparison (Abstract)
Alok KumbhareKumbhare, Alok Microsoft Research, n.n.United States Automated Service Design with Cerulean (Project Showcase)
L Pedro Las-CasasLas-Casas, Pedro MicrosoftUnited States Automated Service Design with Cerulean (Project Showcase) Towards Using LLMs for Distributed Trace Comparison (Abstract)
Ze LiLi, Ze Microsoft AzureUnited States Orchestrating Cross-Layer Anomaly Detection and Mitigation to Address Gray Failures in Large-Scale Cloud Infrastructure
Chang LouLou, Chang University of VirginiaUnited States Orchestrating Cross-Layer Anomaly Detection and Mitigation to Address Gray Failures in Large-Scale Cloud Infrastructure
M Minghua MaMa, Minghua MicrosoftUnited States Orchestrating Cross-Layer Anomaly Detection and Mitigation to Address Gray Failures in Large-Scale Cloud Infrastructure
Jonathan MaceMace, Jonathan MicrosoftUnited States Automated Service Design with Cerulean (Project Showcase)
Andriy MiranskyyMiranskyy, Andriy Toronto Metropolitan University (formerly Ryerson University)Canada Invited Talk2: Scaling Intelligence: AIOps for Complex Systems
P Jingjia PengPeng, Jingjia University of MichiganUnited States Automated Bug Discovery in Cloud Infrastructure-as-Code Updates with LLM Agents Automated Lifting for Cloud Infrastructure-as-Code Programs
Q Yiming QiuQiu, Yiming University of MichiganUnited States Automated Bug Discovery in Cloud Infrastructure-as-Code Updates with LLM Agents Automated Lifting for Cloud Infrastructure-as-Code Programs
R Vivek RamamurthyRamamurthy, Vivek Microsoft AzureUnited States Orchestrating Cross-Layer Anomaly Detection and Mitigation to Address Gray Failures in Large-Scale Cloud Infrastructure
S Weiyi ShangShang, Weiyi University of Waterloo Invited Talk1: Towards Pragmatic Pre-processing of Logs
Gagan SomashekarSomashekar, Gagan MicrosoftUnited States Automated Service Design with Cerulean (Project Showcase)
T Patrick Tser Jern KonTser Jern Kon, Patrick University of MichiganUnited States Automated Bug Discovery in Cloud Infrastructure-as-Code Updates with LLM Agents Automated Lifting for Cloud Infrastructure-as-Code Programs
W Xinyu WangWang, Xinyu University of MichiganUnited States Automated Lifting for Cloud Infrastructure-as-Code Programs
X Yong XiaXia, Yong HSBCChina Breaking the Cycle of Recurring Failures: Applying Generative AI to Root Cause Analysis in Legacy Banking Systems
Yiming XiangXiang, Yiming University of MichiganUnited States Automated Bug Discovery in Cloud Infrastructure-as-Code Updates with LLM Agents
Zhangwei XuXu, Zhangwei Microsoft Azure Keynote1: AIOps Unleashed: Transforming Cloud Operations at Microsoft
Y Zhenning YangYang, Zhenning University of MichiganUnited States Automated Bug Discovery in Cloud Infrastructure-as-Code Updates with LLM Agents
Vignatha YenugutalaYenugutala, Vignatha Microsoft AzureUnited States Orchestrating Cross-Layer Anomaly Detection and Mitigation to Address Gray Failures in Large-Scale Cloud Infrastructure
Z Jian ZhangZhang, Jian Microsoft Session Chair of Session1 (part of AIOps) Session Chair of Session4 (part of AIOps) Session Chair of Session2 (part of AIOps) Session Chair of Session 3 (part of AIOps)
Pinhan ZhaoZhao, Pinhan University of MichiganUnited States Automated Lifting for Cloud Infrastructure-as-Code Programs