Chang Lou
Assistant Professor at University of Virginia
Charlottesville, Virginia, United States
Summary
👤
Senior🎓
Top SchoolChang Lou is a tenure-track assistant professor in computer science at the University of Virginia with a decade of experience building robust, highly available distributed systems. His research and engineering work focuses on making distributed services detect, localize, and react to complex runtime failures, drawing on a PhD from Johns Hopkins and internships at Microsoft Research Asia and Columbia. He has practical systems experience contributing to the well-known rDSN framework—fixing replication tutorials, improving profiling tools, and hardening backend code—which informs his hands-on approach to research. Prior projects span cloud service availability, graph-query optimization using hardware features, and tooling to find kernel data races, reflecting a blend of theory and production-grade engineering. Based in Charlottesville, he combines academic rigor with pragmatic contributions to open-source and cloud systems.
10 years of coding experience
6 years of employment as a software developer
Ph.D, Computer Science, Ph.D, Computer Science at Johns Hopkins Whiting School of EngineeringBachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at Shanghai Jiao Tong University
Github Skills (12)
distributed-systems10
c-language10
cprogramming-language10
debug9
debugging9
performance-analysis8
performance-monitor8
performance-analytics8
profiling8
code-profiling8
performance-monitoring8
thrift7
Programming languages (4)
Github contributions (5)
microsoft/rDSN
Oct 2015 - Jul 2016
Robust Distributed System Nucleus (rDSN) is an open framework for quickly building and managing high performance and robust distributed systems.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:106 commits, 2 PRs, 1 comment in 9 months
Contributions summary:Chang primarily focused on fixing bugs in the tutorial section of the rDSN project. Their contributions involved modifying the source code, specifically in the tutorial/counter.replication directory, by changing lock types and correcting variable names to resolve compiler errors. The user also added testing tools and updated the profiler interface by adding new commands. Their work improved the stability and functionality of the replication tutorial and enhanced the profiling capabilities.
distributed-systemperformancedistributed-databasedistributed-systemsnucleus
OrderLab/YCSB
Apr 2019 - Nov 2023
Yahoo! Cloud Serving Benchmark
Contributions:1 push, 1 branch in 4 years 7 months
benchmarkyahookubernetesserving
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