Junfeng Yang is a Professor in Computer Science, a member of the Data Science Institute, and a co-Director of the Software Systems Lab.  Yang’s research centers on building reliable, secure, and fast software systems.  Today’s software systems are large, complex, and plagued with errors, some of which have caused critical system failures, breaches, and performance degradation.  Yang has invented techniques, algorithms, and tools to analyze, test, debug, monitor, and optimize real-world software, including Android, Linux, production systems at Microsoft, machine learning systems, and self-driving platforms, benefiting hundreds of millions of users.  His research has resulted in numerous vulnerability patches to real-world systems, practical adoption at the largest technology companies, and press coverage at Scientific American, The Atlantic, The Register, Communications of ACM, and other news outlets.
Yang received a BS in computer science from Tsinghua University and a PhD in computer science from Stanford University.   He won the Sloan Research Fellowship and the Air Force Office of Scientific Research Young Investigator Program Award, both in 2012; the National Science Foundation CAREER award in 2011; and Best Paper Awards at the USENIX Symposium on Operating System Design and Implementation in 2004 and the ACM Symposium on Operating Systems Principles in 2017.