Hanjie Chen


 Hanjie Chen

  Center for Language and Speech Processing

  Johns Hopkins University

  Address: Hackerman Hall, 3101 Wyman Park Dr, Baltimore, MD 21218

  Email: hchen210@jh.edu


About Me

I am a Postdoctoral Fellow in the Center for Language and Speech Processing @ Johns Hopkins University, working with Prof. Mark Dredze. My research interests lie in Trustworthy AI, Natural Language Processing (NLP), and Interpretable Machine Learning. I aim to develop explainable AI techniques that are easily accessible to system developers and end users for building trustworthy and reliable intelligent systems. My current research is centered around trustworthy NLP, with an emphasis on interpretability, robustness, and fairness, to support the understanding and interaction between humans and neural language models. I obtained my Ph.D. in Computer Science in May 2023 at the University of Virginia, where my advisor was Prof. Yangfeng Ji.

⭐ I will join the Department of Computer Science @ Rice University as a tenure-track Assistant Professor starting July 2024. I'm actively looking for motivated students to join my group. Please feel free to reach out (hanjie@rice.edu) if you are interested in collaborating or working with me.

🔥 Prospective students: I am recruiting 1-2 PhD students for Fall 2024. Please apply to our graduate programs.

📌 Research Overview

   Future Research Themes✨
  • Trustworthy and Responsible NLP: model interpretability/explainability, robustness, fairness, privacy/security, ethics
  • Human-AI Interaction and Collaboration: model evaluation, diagnosis/debugging, interactive AI systems
  • NLP for Social Good: applications in healthcare, biomedicine, education, social equality and inclusion


🎓 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


Research Experience

Professional Service

  • Organizer: BlackboxNLP 2024
  • Diversity Representative for UVA Computer Science Graduate Student Group (CSGSG) Council, 2022
  • Area Chair for 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, COLM 2024, NeurIPS 2023, EMNLP 2023, ACL Rolling Review 2021 - now, ACL 2020 - 2021, EMNLP BlackboxNLP Workshop 2022, CoNLL 2019 - 2020, NLPCC 2019 - 2021

Last update: 01/2024