Zexue He

I recently recieved my Ph.D. in Computer Science and Engineering department at University of California, San Diego, advised by Prof. Julian McAuley. I am now a researcher at the MIT-IBM Lab and an affiliate researcher at MIT CSAIL. Previously, I was an intern at the Microsoft Research and Google.

My research focuses on advancing Trustworthy NLP to address high-stakes human-centric tasks, e.g., in human healthcare and college admission. My works utilize human-centered design, diagnose the shortcomings of existing models, and develop AI-driven solutions that are more responsible and better satisifies human needs in real life, with less labor effort and cost:

  • Trustworthy NLP: enhance the fairness, harmlessness, robustness, interpretability, and controllability of LLMs;
  • AI for Social Good : build NLP for Healthcare, AI for Low-Resource, and AI for Therapy.
  • Learning from Humans: understand human cognitive behaviors, brain functions, and reading behaviors
News : I am honored to be awarded the IBM PhD Fellowship 2022 !

Contact: zexueh AT mit.edu or zehe AT ucsd.edu

Full Publications: Google Scholar

Talks

  • Jan. 27th, 2025: I will give a talk at Tufts. Feel free to reach out if you want to chat!
  • Jan. 6th, 2025: Invited talk on Responsible AI for High-Stakes Human-Centric Domains at UCLA. Thanks UCLA NLP group!
  • Nov. 7th, 2025 : Invited talk on Responsible AI for Human-centered Challenges at MIT. Thanks MIT SiA-Lab!
  • Oct. 13th, 2024: Talk on Trustworthy GenAI at UCSD CSE.

Education

Ph.D.          2020 - 2024
                       Computer Science and Engineering, University of California San Diego (UCSD), U.S.
                       Ph.D. student in Computer Science
                       Advisor: Prof. Julian McAuley
                       Committee: Prof. Taylor Berg-Kirkpatrick, Prof. Jingbo Shang, Prof. Zhiting Hu

B.S.              2015 - 2019
                       College of Information Science and Technology, Beijing Normal University (BNU), China
                       B.S. in Computer Science and Technology
Selected Publications

Trustworthy LLM
Yu Wang, Ruihan Wu, Zexue He, Xiusi Chen, Julian McAuley
ICLR 2025.
Jessica Echterhoff, Yao Liu, Abeer Alessa, Julian McAuley, Zexue He
EMNLP 2024 .
Zexue He, Marco Tulio Ribeiro, Fereshte Khani
ACL 2023 .
Bodhi Majumder* Zexue He*, Julian McAuley
EMNLP 2023. *Equal.
Zexue He, Yu Wang, Julian McAuley, Bodhisattwa Majumder
EMNLP2022 Findings
Canwen Xu, Zexue He, Zhankui He, Julian McAuley
AAAI 2022. Press Coverage in UCSD News.
Zexue He, Bodhisattwa Majumder, Julian McAuley
EMNLP 2021 Findings.
Haohan Wang, Zexue He, Zachary C. Lipton, Eric P. Xing.
ICLR 2019, Top 1% Oral.
Fuli Luo, Tianyu Liu, Zexue He, Qiaolin Xia, Zhifang Sui, Baobao Chang
EMNLP 2018
AI for Social Good
Healthcare
Zexue He, Yu Wang, An Yan, Yao Liu, Eric Y Chang, Amilcare Gentili, Julian McAuley, Chun-Nan Hsu
EMNLP 2023.
Zexue He, An Yan, Amilcare Gentili, Julian McAuley, Chun-Nan Hsu
AAAI 2023.
An Yan, Zexue He, Xing Lu. Jiang Du, Eric Chang, Amilcare Gentili, Julian McAuley and Chun-Nan Hsu
EMNLP 2021 Findings.
Zexue He, Li Zhu, Minjie Li, Jinyao Li, Yiran Chen, Yanlin Luo.
SCIENCE CHINA Information Sciences.
Accessibility for Low-Resource
Zexue He*, Graeme Blackwood*, Rameswar Panda, Julian McAuley, Rogerio Feris
ACL2023 Findings.
*Equal Contribution.
Esthetics
Yu Wang, Zexue He, Zhankui He, Hao Xu, Julian McAuley
AAAI 2024 .
Learning from Human Behaviors and Cognitions
Y. Wang*, C. Han*, T. Wu*, X. He*, W. Zhou, N Sadeq, X Chen, Zexue He, W. Wang, G. Haffari, H. Ji, J. McAuley
TMLR 02/2025
Zexue He, Leonid Karlinsky, Donghyun Kim, Julian McAuley, Dmitry Krotov, Rogerio
ICML 2024 LCFM. Press Coverage in IBM News.
T. Shi, Z. Wang, L. Yang, YC. Lin, Z. He, M. Wan, P. Zhou, S. Jauhar, X. Xu, X. Song, J. Neville,
NeurIPS 2024 Behavioral ML
Xiaochuan Wang, Ning Su, Zexue He, Yiqun Liu, Shaoping Ma.
SIGIR 2018
Jiaxin Mao, Yiqun Liu, Noriko Kando, Zeuxe He, Min Zhang, Shaoping Ma.
CHIIR 2018
Xiangsheng Li, Yiqun Liu, Jiaxin Mao, Zexue He, Min Zhang, Shaoping Ma.
CIKM 2018
Work Experience

MIT-IBM AI Lab, Cambridge, MA
Research Scientist (Prev. Research Intern) • summer 2023 - till now
Memory-augmented Foundation Models for Efficient Long-Context Modeling
Collaborators: Dr. Dmitry Krotov at MIT-IBM
Advisors: Prof. Yoon Kim at MIT; Prof. Donghyun Kim at Korea University
                      Dr. Leonid Karlinsky and Dr. Rogerio Feris at MIT-IBM

Microsoft, Redmond, Washington
Research Intern • summer 2022
Targeted Data Generation
Advisor: Dr. Fereshte Khani Prof. Marco Tulio Ribeiro
Office of Applied Research

NEC Labs, Princeton, NJ
Research Intern • June. 2021 to Sept. 2021
Multimodality Data Representation Learning
Advisor: Dr. Yuncong Chen
Data Science & System Security Group

Microsoft Research Asia, Beijing, China
Research Intern • Oct. 2019 to Dec. 2019
Algorithmic Trading: High-Frequency Time Series Machine Learning and Data Mining
Advisor: Dr. Kan Ren
Machine Learning Group

Google, Beijing, China
Engineering Practicum Intern • Jul. 2017 to Sept. 2017
Knowledge Graph Source Discovery: Wikipedia-like Sites Discovery and Analysis
Advisor: Jiang Bian, team manager
Dataz Group
Experiences

Machine Learning Department, Carnegie Mellon University, Pittsburgh, U.S.
Research Intern • Apr. 2018 to Oct. 2018
Robust Learning for Domain Generalization (DG) without Domain Information
Mentor: Haohan Wang, Ph.D. candidate at LTI, CMU
Advisors: Prof. Zachary C. Lipton.
Information Retrieval Group, Tsinghua University, Beijing, China
Research Assistant • Jun. 2017 to May 2018
Investigating Human Examination Behavior on Mobile Search
Advisor: Prof. Yiqun Liu
Key Laboratory of Computational Linguistic, Peking University, Beijing, China
Research Assistant • Dec. 2017 to May 2018
Leveraging Gloss Knowledge in Neural Word Sense Disambiguation (WSD)
Chinese Word Segmentation (CWS) with Character Glyph Embedding
Advisor: Prof. Baobao Chang
Engineering Research Center of Virtual Reality and Applications, Beijing Normal University, Beijing, China
Research Assistant • Jul. 2017 to Feb. 2017
Human Brain's CT-MRI Heterogeneous Data Fusion and Visualization
Advisor: Prof. Yanlin Luo
School of Life Science, Beijing Normal University, Beijing, China
Research Assistant • Nov. 2015 to Sept. 2017
Genetic Biological Parallel Computing System for NP-hard Problems
Advisor: Prof. Xudong Zhu
Honors & Awards

Gold Medal in International Genetically Engineered Machine Competition (iGEM) at Boston, Massachusetts, U.S. • 2016
Silver Medal in International Collegiate Programming Contest at Beijing regional site (ACM/ICPC, Beijing) • 2016
Bronze Medal in International Collegiate Programming Contest at Dalian regional site (ACM/ICPC, Dalian) • 2016
Best Female Team in China Collegiate Programming Final Contest (CCPC Final) • 2016
Scholarships

IBM Ph.D. Fellowship • 2022-2024 • IBM
TwoSigma Ph.D. Fellowship Final Nomination • 2022-2024 • TwoSigma
Jacobs School of Engineering Fellowship • 2020-2021 • University of California San Diego
The First-class Scholarship for Academic Excellence • 2018 • Beijing Normal University
The First-class Scholarship for Competition Excellence • 2016, 2017, 2018 • Beijing Normal University
Google Intern Scholarship • 2017 • Google Inc.