Aaron Chan

PhD Candidate at USC   •   Research Intern at Meta AI   •   chanaaro [at] usc [dot] edu


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Hi! :wave: I’m a computer science PhD candidate in the INK Lab at the University of Southern California (USC), where I’m advised by Prof. Xiang Ren. I’m also a member of USC’s Information Sciences Institute (ISI).

My research is at the intersection of machine learning and natural language processing. In particular, I’m excited about:

  • model explainability: explaining language model behavior more faithfully, plausibly, and efficiently.
  • explanation-based learning: operationalizing explanations to improve language model decision-making.

Currently, I’m working as a research intern at Meta AI, on the AI Integrity Team. Previously, I was a hardware engineering intern at Google, on the Android Camera Team.

Before coming to USC, I earned a master’s degree in robotics from the University of Pennsylvania and a bachelor’s degree in electrical engineering from the University of Maryland, College Park.

On a personal note, I grew up in the suburbs of Washington, DC and now live with my wife in Los Angeles, CA. Outside of work, you might find me playing/watching basketball (go Wizards!), skiing, hiking, board gaming, or foodie-ing (:sushi::curry::crab::pizza:). Plus, I’m a huge fan of the TV shows Seinfeld and BoJack Horseman.


News

Jan 10, 2022 In Spring 2022, I’m a TA for CSCI 566 (Deep Learning and its Applications) at USC.
Dec 16, 2021 A preprint of my Meta AI intern project, UniREx, has been published on arXiv.
Dec 09, 2021 I’ll be presenting SalKG today at NeurIPS 2021. Come chat with me at Poster Session 7!
Sep 28, 2021 Our SalKG paper was accepted to NeurIPS 2021! :tada:
Sep 20, 2021 I started my research internship at Facebook Meta AI, where I’ll be working on language model explainability with the AI Integrity Team.
Jul 31, 2021 This summer, I had an awesome time mentoring Wyatt Lake, as part of USC’s SHINE program. Check out Wyatt’s project on explanation-based regularization of BERT models.
Jun 08, 2021 I passed my PhD qualifying exam and am now a PhD candidate! :ballot_box_with_check:

Selected Publications

  1. arXiv
    UniREx: A Unified Learning Framework for Language Model Rationale Extraction
    A. Chan, M. Sanjabi, L. Mathias, L. Tan, S. Nie, X. Peng, X. Ren, and H. Firooz
    arXiv:2112.08802, 2021
  2. NeurIPS
    SalKG: Learning From Knowledge Graph Explanations for Commonsense Reasoning
    A. Chan, J. Xu, B. Long, S. Sanyal, T. Gupta, and X. Ren
    Advances in Neural Information Processing Systems (NeurIPS), 2021
  3. ACL Findings
    Learning Contextualized Knowledge Structures for Commonsense Reasoning
    J. Yan, M. Raman, A. Chan, T. Zhang, R. Rossi, H. Zhao, S. Kim, N. Lipka, and X. Ren
    Findings of the Annual Meeting of the Association for Computational Linguistics (ACL), 2021
  4. ICLR
    Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation
    M. Raman, A. Chan*, S. Agarwal*, P. Wang, H. Wang, S. Kim, R. Rossi, H. Zhao, N. Lipka, and X. Ren
    International Conference on Learning Representations (ICLR), 2021