I am a first-year Ph.D. student in the Computer Science Dept. at Purdue University, advised by Professor Xiangyu Zhang. Before joining Purdue, I obtained my Master of Science degree in Electrical and Computer Engineering at Carnegie Mellon University and my bachelor degree from University of Science and Technology Beijing.
My research interests lie in interpretable artifical intelligence(AI) and reinforcement learning, machine learning(ML) security and privacy, the vibrant research field that focuses on reducing ML systems vulnerabilities and designing verifiable machine learning approaches with provable robustness. My enthusiasm is to develop trustworthy machine learning solutions as well as deploying reliable AI systems, to help end users trust the AI system and make humans empowered by machine learning.
MSc in Electrical and Computer Engineering, 2020
Carnegie Mellon University
BSc in Electrical Engineering, 2019
University of Science and Technology Beijing
Behavior-level explanations of the Deep-Q-Network trained agents.
A novel transfer learning method for GAN style transfer which consumes fewer computation resources and training time.
Trainable and Diffientiable Loss for Classification Neural Network.