I joined College of William and Mary in 2013 to work on my Phd program. My advisor is Dr. Xu Liu. Before that, I get my bachelor's degree and master's degree in Beihang University.

I am instrested in performance analysis area. Works I am currently into are about the memory performance behavior in NUMA architecture and redundant computations. We developed tools to measure the execution of programs and either provide guidence for developers to do the optimization or optimize on-line in the same execution.

As to programming languages, I prefer C, C++, Python.


  • [IPDPS'17] "Dr-BW: Identifying Bandwidth Contention in NUMA Architectures with Supervised Learning", Hao Xu, Shasha Wen, Alfredo Gimenez, Todd Gamblin and Xu Liu. The 31st IEEE International Parallel and Distributed Processing Symposium, May 29 - Jun 2, 2017, Orlando, Florida, USA. Acceptance ratio: 23%.

  • [ASPLOS'17] "RedSpy: Exploring Value Locality in Software", Shasha Wen, Milind Chabbi, Xu Liu. The 22nd International Conference on Architectural Support for Programming Languages and Operating Systems, Apr 8-12, 2017, Xi'an, China. Best paper final list (6/56).

  • [PPOPP'17] "An Efficient Abortable-locking Protocol for Multi-level NUMA Systems", Milind Chabbi, Halim Amer, Shasha Wen and Xu Liu, The 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Feb 4-8, 2017, Austin, Texas, USA. Acceptance ratio: 22% (29/132).

  • [PACT'15] "Runtime Value Numbering: A Profiling Technique to Pinpoint Redundant Computations", Shasha Wen, Xu Liu, Milind Chabbi. The 24th International Conference on Parallel Architectures and Compilation Techniques, Oct 18-21, 2015, San Francisco, California, USA. Acceptance ratio: 21% (38/179)

Research activites

  • PPoPP 2017 artifact committee

  • Research intern at Hewlett Packard Enterprise, 2016

    I work with Lucy Cherkasova on cache performance and also data placement on heterogeneous memory system.

  • PPoPP 2016 artifact committee

  • Summer intern at LLNL, 2015

    I work with Todd Gamblin on a project about diagnosing bandwidth usage using supervised machine learning algorithm.


  • George Healy Fellowship from William and Mary

  • The Stephen K.Park graduate research award from Computer Science Department of William and Mary

  • Student travek grant for ASPLOS2017, IPDPS2017

  • Student travel grant for PACT2015, supported by NSF