About Me

Modern scientific exploration generates rapidly increasing amounts of data, far outpacing our ability for manual analysis. My research develops computer vision & machine learning methods for complex scientific inquiries and workflows that require expert attention. My goal is to enable more effective ways for human experts and machine learning systems to collaborate, in order to expand our understanding of the world around us. See more about my research or publications.

I am an Assistant Professor at the Computer Science department at Cornell. If you are interested in collaborating or joining my group, feel free to reach out! For PhD students, the application process is handled centrally with more information on how to apply here.

Contact:  jjs533@cornell.edu

Before this, I spent a year as a research scientist at Google. I graduated from Caltech in Computing and Mathematical Sciences, and I was co-advised by Professor Pietro Perona and Professor Yisong Yue. I am grateful to be supported by the Kortschak Scholars Program at Caltech and the NSERC Postgraduate Scholarship from the Natural Sciences and Engineering Research Council of Canada. I have been awarded Amazon AI4Science Fellowship and the Ben P.C. Chou Doctoral Prize.

Select Projects

See the full list of my publications here.

  • Neurosymbolic Programming for Science, AI4Science Workshop at NeurIPS
    Jennifer J. Sun*, Megan Tjandrasuwita*, Atharva Sehgal*, Armando Solar-Lezama, Swarat Chaudhuri, Yisong Yue, Omar Costilla-Reyes
    [paper]
  • Self-Supervised Keypoint Discovery in Behavioral Videos, CVPR 2022
    Jennifer J. Sun*, Serim Ryou*, Roni Goldshmid, Brandon Weissbourd, John Dabiri, David J. Anderson, Ann Kennedy, Yisong Yue, Pietro Perona
    [paper][project website][code]
  • Task Programming: Learning Data Efficient Behavior Representations, CVPR 2021 (Oral)
    Awarded Best Student Paper at CVPR 2021
    Jennifer J. Sun, Ann Kennedy, Eric Zhan, David J. Anderson, Yisong Yue, Pietro Perona
    [paper][project website][code][video]
  • Learning Differentiable Programs with Admissible Neural Heuristics, NeurIPS 2020
    Ameesh Shah*, Eric Zhan*, Jennifer J. Sun, Abhinav Verma, Yisong Yue, Swarat Chaudhuri
    [paper][code]
  • View-Invariant Probabilistic Embedding for Human Pose, ECCV 2020 (Spotlight)
    Jennifer J. Sun, Jiaping Zhao, Liang-Chieh Chen, Florian Schroff, Hartwig Adam, Ting Liu
    [paper][code][video][project website][Google AI blog post]
    [IJCV paper]
  • Workshops & Tutorials: