I am a fourth-year PhD student at Columbia University advised by Carl Vondrick. The core of machine learning often involves humans instructing machines with existing knowledge. My focus is on advancing machine learning methods that can impart novel insights back to humans. My research interests span interpretability and knowledge discovery across multi-modal domains such as vision, muscle activity, and audio.

I previously graduated from the University of Pennsylvania advised by Jianbo Shi, with a BA in Computer Science, and minors in Math, Computational Neuroscience, and Systems Eng. In my free time I like to read in parks (my GoodReads), dance, play piano, and sometimes, scuba dive.


  • Evolving Interpretable Visual Classifiers with Large Language Models Mia Chiquier, Utkarsh Mall, Carl Vondrick
    PaperProject Page
    arXiv 2024
  • Muscles in Action Mia Chiquier, Carl Vondrick
    PaperProject PageTalk (5 min)
    ICCV 2023
  • Multiparty Perception for Navigation Hui Lu, Mia Chiquier, Carl Vondrick
    PaperProject Page
    Neurips 2022
  • Real-Time Neural Voice Camouflage Mia Chiquier, Chengzhi Mao, Carl Vondrick
    PaperProject PageScience.orgTalk (12 min)
    ICLR 2022 (Oral,Top 1.6%)
  • The Boombox: Visual Reconstruction from Acoustic Vibrations Boyuan Chen, Mia Chiquier, Hod Lipson, Carl Vondrick
    PaperProject Page
    CoRL 2021
  • Adversarial Attacks are Reversible with Natural Supervision Chengzhi Mao, Mia Chiquier, Hao Wang, Junfeng Yang, Carl Vondrick
    ICCV 2021


Advanced Computer Vision (COMS 4731, Summer 2021)
Head Teaching Assistant
Columbia University
Dynamical Systems (ESE 210, Fall 2019)
Head Teaching Assistant
University of Pennsylvania
Organizer: Quo Vadis, Computer Vision? Workshop (ICCV 2023)
Workshop Organizer
ICCV 2023
ICCV 2021, CVPR 2022
Columbia University
BEARS Mentorship (Spring 2021, Spring 2022)
Undergraduate Mentor
Barnard College
Organizer: Learning from Unlabeled Video Workshop (CVPR 2021)
Workshop Organizer
CVPR 2023