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
|
|
|
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.
|
|