Xuezhe Ma

Xuezhe Ma is a Research Assistant Professor in the Department of Computer Science and a Research Lead at the Information Sciences Institute at the University of Southern California (USC).12 His research focuses on natural language processing, machine learning, and deep generative models.3

Academic Background

Dr. Ma received his Ph.D. from the Language Technologies Institute at Carnegie Mellon University, where he worked with Professor Eduard Hovy.2 Prior to that, he completed his master's degree at Shanghai Jiao Tong University in China and his bachelor's degree in Computer Science from the same institution.2

Research Focus

Xuezhe Ma's primary research area is representation learning using deep learning techniques. He aims to enhance the effectiveness, efficiency, interpretability, and robustness of representation learning by developing and analyzing advanced deep learning methods.2 His work has contributed significantly to various aspects of natural language processing and machine learning.

Professional Experience

• Research Assistant Professor at USC's Information Sciences Institute (September 2020 - Present)1
• Graduate Research Assistant at Carnegie Mellon University (September 2014 - September 2020)1
• Research Staff at Johns Hopkins University (June 2015 - August 2015)1
• Student Intern at University of Washington (November 2012 - December 2013)1
• Student Intern at Microsoft Research Asia (July 2009 - October 2009)1

Notable Achievements

Dr. Ma has published numerous influential papers in top-tier conferences and journals in his field. Some of his works have received significant recognition:

• Co-authored a paper that received the Outstanding Paper Award at the 54th Annual Meeting of the Association for Computational Linguistics (ACL 2016)2
• His paper on end-to-end sequence labeling has been cited over 3,400 times3
• Contributed to a paper that received a Best Demo Paper Nomination at ACL 20192

Xuezhe Ma continues to be an active researcher, regularly publishing in major conferences and journals in the fields of natural language processing and machine learning.