My research goal is to make software systems: easy-to-use, fast and reliable by improving their programmability, performance and reliability.
Recently I am working on automating the validation of deep learning toolchains with DNN synthesis and reduction. More generally, I am interested in program analysis/optimization, verification/validation and machine learning techniques.
🤗 Feel free to drop me an email if we share common research interest.
NNSmith: Generating Diverse and Valid Test Cases for Deep Learning CompilersProceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems. Mar 2023
OOPSLA’22Coverage-guided tensor compiler fuzzing with joint IR-pass mutationProceedings of the ACM on Programming Languages 6 (OOPSLA1). Apr 2022
ACMMM’21 (OSC)Fast and Flexible Human Pose Estimation with HyperPoseProceedings of the 29th ACM International Conference on Multimedia. Apr 2021
OctoML, Smr. 2022 Pattern Language
TalksFinding Deep-Learning Compilation Bugs with NNSmith
- Software Engineering Retreat, University of Illinois at Urbana-Champaign Sept. 2022