Hanjie Chen

  Department of Computer Science

  Rice University

  Address: Duncan Hall 2081, 6100 Main St, Houston, TX 77005

  Email: hanjie@rice.edu

             

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About Me

I am an Assistant Professor in the Computer Science Department @ Rice University. I am also affiliated with the Ken Kennedy Institute. I am broadly interested in Natural Language Processing, Interpretable Machine Learning, and Trustworthy AI. My research focuses on explaining and evaluating the properties, mechanisms, and capabilities of neural language models, enabling their alignment, interaction, and collaboration with humans, and enhancing their impact on real-world applications such as medicine, healthcare, sports, and more. By developing explainable AI techniques, I aim to make intelligent systems controllable by system developers, accessible to general users, applicable to various domains, and beneficial to society.

Prior to joining Rice, I was a Postdoctoral Fellow in the Center for Language and Speech Processing @ Johns Hopkins University from 2023 to 2024, hosted by Dr. Mark Dredze. I completed my Ph.D. in Computer Science in May 2023 at the University of Virginia, where my advisor was Dr. Yangfeng Ji.

Highlights

🎓 Received the Outstanding Doctoral Student Award, UVA, 2023

🎉 Received the John A. Stankovic Graduate Research Award, UVA, 2023

🎉 I was awarded the Carlos and Esther Farrar Fellowship, 2022 - 2023

👩‍🏫 Received the UVA CS Outstanding Graduate Teaching Award and University-wide Graduate Teaching Awards Nominee (top 5% of graduate instructors) for the course, CS 6501/4501 Interpretable Machine Learning, I co-designed and instructed at UVA in Spring 2022

📝 I maintain a Reading List with interesting papers

  Updates

• [11/2024] Organize the BlackboxNLP Workshop @ EMNLP 2024
• [11/2024] Invited talk, Incredible Yet Limited Large Language Models in the Wild, CS @ FSU
• [10/2024] New preprint, Language Models are Symbolic Learners in Arithmetic, arXiv
• [10/2024] New preprint, MiCEval: Unveiling Multimodal Chain of Thought’s Quality via Image Description and Reasoning Steps, arXiv
• [10/2024] New preprint, From Babbling to Fluency: Evaluating the Evolution of Language Models in Terms of Human Language Acquisition, arXiv
• [10/2024] New preprint, SPORTU: A Comprehensive Sports Understanding Benchmark for Multimodal Large Language Models, arXiv
• [07/2024] Invited to serve as a Senior Area Chair for ACL 2025
• [06/2024] Tutorial on Explanation in the Era of Large Language Models @ NAACL 2024
• [06/2024] Invited to serve as an Area Chair for EMNLP 2024
• [04/2024] New preprint, Will the Real Linda Please Stand up...to Large Language Models? Examining the Representativeness Heuristic in LLMs, arXiv
• [03/2024] Invited talk at How Sustainable is Artificial Intelligence?
• [02/2024] New preprint, Benchmarking Large Language Models on Answering and Explaining Challenging Medical Questions, arXiv
• [02/2024] New preprint, RORA: Robust Free-Text Rationale Evaluation, arXiv
• [01/2024] Co-teach the course Trustworthy and Responsible NLP with Sharon Levy, Spring 2024, JHU
• [12/2023] Co-host the 22nd MLNLP Seminar
• [11/2023] Guest lecture on Interpretable and Explainable NLP at 601.467/667 Introduction to Human Language Technology @ JHU
• [11/2023] Guest lecture on Interpretable and Explainable NLP at CSCI 699 Ethics in NLP @ USC
• [10/2023] I will co-organize the BlackboxNLP 2024 Workshop at EMNLP 2024
• [10/2023] Our tutorial Explanation in the Era of Large Language Models is accepted to appear at NAACL 2024
• [09/2023] New preprint, Explainability for Large Language Models: A Survey, arXiv
• [05/2023] REV: Information-Theoretic Evaluation of Free-Text Rationales is accepted by ACL 2023
• [03/2023] Invited Talk on Bridging the Trustworthy Gap between AI and Humans: Interpretation Techniques for Modern NLP at the CLSP Seminar @ Johns Hopkins University

Research Experience

• Johns Hopkins University, Baltimore, MD, June 2023 - June 2024

  Center for Language and Speech Processing

  • Postdoctoral Fellow
  • Advisor: Mark Dredze
• University of Virginia, Charlottesville, VA, Aug. 2018 - May 2023

  Information and Language Processing Lab

  • Research Assistant
  • Advisor: Yangfeng Ji
• Allen Institute for AI (AI2), Seattle, WA, May 2022 - Oct. 2022

  Mosaic Group

  • Research Intern
  • Manager: Yejin Choi
  • Mentors: Swabha Swayamdipta, Faeze Brahman, Xiang Ren
• Microsoft Research, Redmond, WA, May 2021 - Aug. 2021

  Language and Information Technologies Group

  • Research Intern
  • Manager: Ahmed H. Awadallah
  • Mentors: Guoqing Zheng, Srinagesh Sharma
• IBM Research, New York, NY, Jun. 2020 - Aug. 2020

  Thomas J. Watson Research Center

  • Research Intern
  • Manager: Luis Lastras
  • Mentors: Chulaka Gunasekara, Song Feng, Hui Wan, Jatin Ganhotra, Sachindra Joshi

Professional Service

• Organizer: BlackboxNLP Workshop @ EMNLP 2024
• Senior Area Chair: ACL 2025
• Area Chair: NAACL 2025, COLING 2025, EMNLP 2024, ACL ARR 2024 - Now, WiML Workshop @ NeurIPS 2022
• Program Committee: ACL 2023, AAAI 2023, EMNLP 2021 - 2023, NAACL 2021, EACL 2023, CoNLL 2021 - 2022, NLPCC 2022, ACL DialDoc Workshop 2022, EMNLP BlackboxNLP Workshop 2021, 2023, NeurIPS Explainable AI Approaches for Debugging and Diagnosis Workshop 2021, Document-grounded Dialogue Workshop 2021, MASC-SLL 2020
• Reviewer: TACL 2023 - 2025, ICLR 2024 - 2025, COLM 2024, NeurIPS 2023, EMNLP 2023, ACL ARR 2021 - 2024, ACL 2020 - 2021, EMNLP BlackboxNLP Workshop 2022, CoNLL 2019 - 2020, NLPCC 2019 - 2021
• Diversity Representative for UVA Computer Science Graduate Student Group (CSGSG) Council, 2022

Tutorial

• Explanation in the Era of Large Language Models @ NAACL 2024

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