About me
I am an Ph.D. student in the Department of Computer Science and Engineering at University of Connecticut since 2021 spring. I obtained my B.S. degree in electrical engineering from Huazhong University of Science and Technology in 2018 and and M.S. degree in electrical engineering from University of Akransas in 2020.
I am generally interested in Large Language Model, efficient ML, secure and Trustworthy AI/ML, and ML system. My current research focuses are listed as follows:
Recent News
12/2023 I’m starting a new internship at Microsoft GenAI team, under the supervision of Abhishek Goswami, Dr. Shuohang Wang, Dr. Yelong Shen, Dr. Weizhu Chen
11/2023 Our paper MaxK-GNN on accelerating GNN training through MaxK nonlinearity & GPU kernel co-design has been accepted by ASPLOS 24. [Code].
10/2023 I accepted the Synchrony Fellowships from UConn CSE. Thanks UConn CSE![News]
09/2023 Our paper LinGCN on accelerating GCN private inference under Homomorphical Encryption Setting has been accepted by NEURIPS 23. [Code].
09/2023 We release Medusa, a easy-to-use framework which accelerates LLM generation through multiple light-weighted decoding head. No draft model needed! [Blog], [code].
07/2023 Our paper AQ2PNN on adaptive quantization in private inference under multi-party computation setting has been accepted by MICRO 23.
07/2023 Our paper Accel-GCN on graph learning acceleration on GPUs has been accepted by ICCAD 23. [Code].
07/2023 Our paper AutoReP on ReLU replacement for fast private inference under multi-party computation setting has been accepted by ICCV 23. [Code].
07/2023 I accepted the GE Fellowship from School of Engineering. Thanks School of Engineering!
05/2023 I accepted the Predoctoral Fellowship from UConn CSE. Thanks UConn CSE!
02/2023 Our paper PASNet on NAS for private inference acceleration under multi-party computation setting has been accepted by DAC 23. [Code].
01/2023 Our paper on GNN sparsification has been accepted by ICCD 23. [Code].
05/2022 I accepted the Taylor L. Booth predoctoral fellowship for top 1 scholarly achievements by UConn CSE. Thanks UConn CSE!
02/2022 Our paper on Transformer model acceleration has been accepted by DAC 2022.