Chang Lou
Assistant Professor, University of Virginia

mail chlou [AT] virginia [DOT] edu

Department of Computer Science
University of Virginia
Rice Hall 304, 85 Engineer’s Way
Charlottesville, VA 22904


We are hiring! Our lab has Ph.D. student positions starting from Fall 2026. If you are interested in building/hacking systems, we should talk. [Link]
Update: GRE and application fee are waived for all 2026 applications.

Update: Read mentoring principles in our group.

About

I am a tenure-track assistant professor in Department of Computer Science at University of Virginia. My research centers on building robust and highly available systems. One major focus is to enhance the capabilities of distributed systems to detect, localize, and react to complex failures at runtime. I am also interested in solving reliability challenges in real-world systems from other domains, such as deep learning systems.

Our ongoing research efforts focus on:

  • runtime assurance via reasoning/enforcing system semantics/dynamics: [NSF abstract]
  • a generative verification approach to prevent cloud regressions: [HotNets’25]
  • formal verification techniques to uncover silent errors in ML models: [EuroMLSys’25]
  • incident management in production cloud infrastructure:

My earlier dissertation works include runtime solutions to handle:


News

  • 2026/7: BRAIN is accepted by NSDI’27. Congratulations to the team!
  • 2026/7: Co-organizing the Symposium on Rigorous LLM Systems (RigoLLM), a workshop co-located with ACM SIGOPS ATC’26. Welcome to submit your work!
  • 2026/4: Honored to receive the ACM@UVA Rising Star Faculty Award, presented by the UVA student chapter of ACM. Many thanks to our students for this meaningful recognition!
  • 2026/4: Our undergrad intern Julian Sutadi will attend The Cornell, Maryland, Max Planck Pre-doctoral Research School this summer at Saarbrücken, Germany.
  • 2025/12: Pilot is accepted by NSDI’26. Congratulations to Zhenyu and Angting!
  • 2025/10: Interviewed by NPR (Jaclyn Diaz) and ABC News Australia (James Glenday and Emma Rebellato) to discuss the global AWS outage.
screenshots
ABC News Australia interview screenshot ABC News Australia interview screenshot
  • 2025/4: Our proposal on low-level semantics inference is awarded by Accelerating Foundation Models Research. Big thanks to Microsoft and our collaborators!
  • 2025/3: T2C is accepted by OSDI’25!
  • 2024/12: Awarded NSF CAREER for my proposal “Low-Effort Runtime Assurance for Robust Cloud Systems.” Thank you NSF!
More news
  • 2025/9: Our position paper on preventing cloud regressions via inferred low-level semantics is accepted to appear at HotNets’25. Congrats Dimas!
  • 2025/4: Congratulations to Zhenyu winning UVA CS Outstanding Graduate Teaching Award for his excellent service in CS4740 Cloud Computing!
  • 2025/2: Our workshop paper on Verifying Large ML Models has been accepted by EuroMLSys ‘25.
  • 2025/1: Will be serving on the NSDI’26 Program Committee.
  • 2024/12: Will present our position paper on host anomaly detection and mitigation at AIOps’25.
  • 2024/10: Congratulations to Tseganesh (Grace) for being selected to present her work at SOSP SRC!
  • 2024/10: Zhenyu, Dimas, and Kahfi received SOSP travel grants. Thanks to the sponsors!
  • 2024/10: Will be serving on the SOSP’25 Program Committee.
  • 2024/5: Co-organizing a SIGCOMM workshop on Formal Methods × Networked Systems.
  • 2024/4: Received grants from the 4-VA Collaborative Program.
  • 2024/3: Invited to give a talk at the University of Chicago Systems Seminar.
  • 2024/3: Will be serving on the NSDI’25 Program Committee.
  • 2023/12: Gave a talk to student interns at Alibaba on graduate school advice.
  • 2023/10: My Ph.D. thesis received an Honorable Mention for the ACM SIGOPS Dennis M. Ritchie Doctoral Dissertation Award.
  • 2023/10: Will be serving on the EuroSys’25 Program Committee.
  • 2023/9: Will be teaching CS4740: Cloud Computing with a new syllabus in Spring 2024.
  • 2023/9: Received Google Cloud Computing Research Credits.
  • 2023/8: A new chapter at UVA started.

Publications

BRAIN: A Unified and Centralized Approach to Automated Outage Declaration at Azure Scale
Cong Chen, Youjiang Wu, Chang Lou, Peng Huang, Yingnong Dang, Feng Gao, Maira Babang, Rajive Kumar, John Socha-Leialoha, Azad Naik, Lauren Zhang, Jonathan Chen, Xiangyang Cao, UV Yadav, Zhiyong Hu, Yi Chen, Aditya Mate, Jasmine Vaghei, Francisco Mandujano Reyes, Akshit Bhalla, Honghua Chang, Bing Hu, Meng Jin, Hrishi Kulkarni, Shane Hu, Justin Bang, Yueli Lu, Andy Stumpp, Souvik Debnath, Yusuf Tinwala, Piyali Jana, Jeffrey Sun, Amandeep Singh, Gabe Wishnie, Rigel Carlson, Sumer Sen, Matthew Hetrick, Salome Jacob, Jeff Davis, Jian Zhang, Bryan Alexander, Hong Gao, Si Qin, Qingwei Lin, Dongmei Zhang, Mathew John, Zhangwei Xu, and John Sheehan.
NSDI’27 [ blog#1#2 ]

Pilot Execution: Simulating Failure Recovery In Situ for Production Distributed Systems
Zhenyu Li, Angting Cai, Chang Lou
NSDI’26 [ bib, slides, code ]

Once Bitten, Still Shy: Can We Prevent Cloud Systems from Repeating Their Mistakes?
Dimas Shidqi Parikesit, Chang Lou
HotNets’25 [ bib, slides ]

Deriving Semantic Checkers from Tests to Detect Silent Failures in Production Distributed Systems
Chang Lou, Dimas Shidqi Parikesit, Yujin Huang, Zhewen Yang, Senapati Diwangkara, Yuzhuo Jing, Achmad Imam Kistijantoro, Ding Yuan, Suman Nath, Peng Huang
OSDI’25 [ bib, slides, code, talk ]

Verifying Semantic Equivalence of Large Models with Equality Saturation
Kahfi S. Zulkifli*, Wenbo Qian* (co-first author), Shaowei Zhu, Yuan Zhou, Zhen Zhang, Chang Lou
EuroMLSys Workshop (co-located with EuroSys’25) [ bib, slides ]

Orchestrating Cross-Layer Anomaly Detection and Mitigation to Address Gray Failures in Large-Scale Cloud Infrastructure
Ze Li, Chang Lou, Vignatha Yenugutala, Vivek Ramamurthy, Eion Blanchard, Minghua Ma, Murali Chintalapati.
AIOps Workshop (co-located with ICSE’25)

Enhancing Cloud System Runtime to Address Complex Failures
Chang Lou
Ph.D. Dissertation (2023) ACM Dennis M. Ritchie Dissertation Award (Honorable Mention)

Demystifying and Checking Silent Semantic Violations in Large Distributed Systems
Chang Lou, Yuzhuo Jing, Peng Huang.
OSDI’22 [ bib, slides, code, talk ]

RESIN: A Holistic Service for Dealing with Memory Leaks in Production Cloud Infrastructure
Chang Lou, Cong Chen, Peng Huang, Yingnong Dang, Si Qin, Xinsheng Yang, Xukun Li, Qingwei Lin, Murali Chintalapati.
OSDI’22 Deployed on Microsoft Azure [ bib, slides, talk, blog ]

Understanding, Detecting and Localizing Partial Failures in Large System Software
Chang Lou, Peng Huang, Scott Smith.
NSDI’20 Best Paper Award [ bib, slides, talk ]
(A TL;DR version from Morning Paper)

Comprehensive and Efficient Runtime Checking in System Software through Watchdogs
Chang Lou, Peng Huang, Scott Smith.
HotOS’19 [ bib, slides ]


Students

I am very fortunate to work with these students:

We are always actively looking for enthusiastic undergrad/graduate interns. Are you one of them? Send us an email if you are interested!


Teaching


Academic Service

Program Committee

  • 2027: OSDI, NSDI
  • 2026: SOSP, NSDI
  • 2025: SOSP, NSDI, EuroSys, APSys, SIGCOMM FMANO
  • 2024: ATC, SIGCOMM FMANO

Misc.

  • Reviewer: ACM TOCS, IEEE TMC, ACM TOPS, IEEE TCC, ACM TACO
  • Shadow PC: EuroSys’23
  • AEC: EuroSys’23
  • Web Chair: HAOC’21 (in conjunction with EuroSys’21)

Work Experience

  • Data Scientist Intern (part-time), Microsoft Azure, Nov 2021 - Jan 2022
  • Data Scientist Intern, Microsoft Azure, Jun 2021 - Aug 2021
  • Data Scientist Intern, Microsoft Azure, Jun 2020 - Sept 2020
  • Research Intern, Microsoft Research Asia, Oct 2015 - Jun 2016

Misc.


Bio

I received my Ph.D. from Johns Hopkins University in May 2023, advised by Prof. Ryan (Peng) Huang. I obtained my B.S. degree in Computer Science from Shanghai Jiao Tong University in June 2016 and spent one gap year at IPADS working with Prof. Haibo Chen and Prof. Rong Chen.