About me

Welcome! I am a machine learning, deep learning and reinforcement learning researcher who strives to solve difficult problems in real world. I am also an affiliated graduate research assistant in the Machine Learning and Data Intensive Computing Lab.

Currently, I am a PhD candidate in Computer Science from the Rochester Institute of Technology and my B.E. in Software Engineering from Dalian University of Technology. My academic work has been published in ICDM, KDD, ICML, Neurips, ICLR, MICCAI, ACM MM, among other outlets. Although my research focused on small dataset by developing novel offline or semi-online RL algorithms, I am experienced and interested in applying RL technique to real-world applications like time series analysis, speech recognition, dense object detection, LLMs safety alignment, network compression, recommender system, medical data, etc.

Nowadays, I am focusing on RL guided model compression and safety alignment for LLMs, by incorporating uncertainty related theory and practice. Besides, I also spend time on LLM benchmark construction, including data collection and model evaluation.