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Hanjie Chen

HanjieChen

 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

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

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

📝 My collaborators and I are actively updating a Reading List with interesting papers

  Updates
  • [09/2023] New preprint, Explainability for Large Language Models: A Survey, arXiv
  • [05/2023] REV: Information-Theoretic Evaluation of Free-Text Rationales accepted to 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
  • [12/2022] Presentation on Information-Theoretic Evaluation of Free-Text Rationales with Conditional V-Information at Trustworthy and Socially Responsible Machine Learning (TSRML) Workshop @ NeurIPS
  • [11/2022] Presentation on Explaining Predictive Uncertainty by Looking Back at Model Explanations at WiML Workshop 2022 @ NeurIPS
  • [10/2022] Talk on REV: Information-Theoretic Evaluation of Free-Text Rationales @ Allen Institute for AI (AI2)
  • [05/2022] Paper presentation on Pathologies of Pre-trained Language Models in Few-shot Fine-tuning at Insights Workshop @ ACL 2022
  • [02/2022] Paper presentation on Adversarial Training for Improving Model Robustness? Look at Both Prediction and Interpretation @ AAAI 2022
  • [12/2021] Invited talk on Improving Model Robustness via Interpretation-based Adversarial Training @ MLNLP
  • [12/2021] Presentation on Adversarial Training for Improving Model Robustness? Look at Both Prediction and Interpretation at WiML Workshop 2021 @ NeurIPS
  • [12/2021] Presentation on Adversarial Training for Improving Model Robustness? Look at Both Prediction and Interpretation @ 2021 Fall UVA CS Research Symposium
  • [06/2021] Paper presentation on Explaining Neural Network Predictions on Sentence Pairs via Learning Word-Group Masks @ NAACL 2021
  • [04/2021] 2021 CRA-WP Grad Cohort for Women Workshop
  • [03/2021] Poster presentation @ ACM Capital Region Celebration of Women in Computing (CAPWIC)
  • [11/2020] Paper presentation on Learning Variational Word Masks to Improve the Interpretability of Neural Text Classifiers @ EMNLP 2020
  • [08/2020] Presentation on Learning Variational Masks for Explainable Next Utterance Prediction in Dialog Systems at IBM Research
  • [07/2020] Paper presentation on Generating Hierarchical Explanations on Text Classification via Feature Interaction Detection @ ACL 2020
  • [12/2019] Poster presentation on Improving the Explainability of Neural Sentiment Classifiers via Data Augmentation @ NeurIPS 2019 Workshop on Robust AI in Financial Services
  • [10/2019] Poster presentation on Building Hierarchical Interpretations in Natural Language via Feature Interaction Detection @ UVA CS Research Symposium Fall 2019
  • [04/2019] Invited talk on How to Train a More Interpretable Neural Text Classifier, AIML-Seminar @ UVA
  • [11/2018] Poster presentation on An Empirical Comparison on Convolutional and Recurrent Neural Networks for NLP at the JUMP Undergraduate Research Initiative, UVA

Research Experience

Professional Service

  • 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, NeurIPS 2023, EMNLP 2023, ACL Rolling Review 2021 - 2022, ACL 2020 - 2021, EMNLP BlackboxNLP Workshop 2022, CoNLL 2019 - 2020, NLPCC 2019 - 2021
Last update: 09/2023