I am a member of the technical staff at AMD Research.
I completed my PhD and Postdoc in Computer Science at the
University of Illinois at Urbana-Champaign, working with
Vikram Adve and
I work in the areas of Compilers, Systems for Machine Learning, and Static Analysis.
I am particularly passionate about designing
compiler optimization frameworks that improve the performance and energy-efficiency of machine learning workloads.
Teaching Statement VIDEO
Systems for Machine Learning
Ph.D. in Computer Science, 2014 - 2021
University of Illinois at Urbana-Champaign
BS in Computer Science, 2009 - 2013
National University of Computer and Emerging Sciences, Lahore
[September 2022] Joined AMD Research
[May 2022] HPVM capstone paper accepted at IEEE Micro Magazine Special Issue!
[December 2021] Serving on the PPoPP'22 external program committee
[September 2021] My PhD thesis is now public! PDF
[July 2021] Journal version of the TRIMMER ASE'18 paper accepted at TSE'21
[April 2021] PhD Thesis Completed. Continuing as Postdoc at UIUC.
[April 2021] HPVM v1.0 public release now available! Gitlab project
[March 2021] Presented ApproxTuner at PPoPP'21 (Virtual) - Video
[November 2020] ApproxTuner paper accepted at PPoPP'21
[October 2020] Presented ApproxTuner at LLVM-Dev'20 - Video
[March 2020] Passed PhD Preliminary Exam!
[January 2020] Released HPVM v0.5 - a retargetable compiler for heterogeneous systems. Presented at FOSDEM
[October 2019] ApproxHPVM presented at OOPSLA'19
[September 2019] AppproxHPVM paper accepted at OOPSLA'19
[September 2018] TRIMMER presented at ASE'18
[July 2018] TRIMMER paper accepted at ASE'18
[September 2017] Presented OpenMP-UVM work at OpenMP Developers Conference 2017
[January 2016] Joined the LLVM Group supervised by Vikram Adve