Junxian He

Junxian He is an Assistant Professor at the Department of Computer Science and Engineering (CSE), the Hong Kong University of Science and Technology (HKUST). He received his Ph.D. from Carnegie Mellon University and his bachelor's degree from Shanghai Jiao Tong University. His main research interests are in natural language processing. His work has been recognized by the best demo paper nomination in ACL 2019, the most influential paper list in ICLR 2022 (paper digest), and Baidu PhD fellowship.

Junxian He is a researcher at the Hong Kong University of Science and Technology, specializing in Machine Learning and Natural Language Processing. His work focuses on advancing transfer learning, parameter-efficient models, and evaluating the performance of large language models. He has contributed to developing frameworks for factuality detection, confidence elicitation, and multi-task learning. His research also explores the use of pre-trained language models for tasks such as text summarization, style transfer, and cross-lingual learning. He has published extensively on improving the efficiency and effectiveness of neural sequence generation and alignment techniques.