About Me

I am a 5-th year computer science PhD student at Stanford, advised by Stefano Ermon. I completed my bachelors in engineering physics at the University of Illinois at Urbana-Champaign.

Contact: jkuck at cs dot stanford dot edu

Research Interests

  • Approximate probabilistic inference
  • Combining probabilistic modeling with deep learning
  • Graph neural networks and learning on irregular data (graphs, sets, and point clouds)
  • Robotic perception: object detection and tracking
  • Uncertainty quantification


  1. Belief Propagation Neural Networks
    Jonathan Kuck, Shuvam Chakraborty, Hao Tang, Rachel Luo, Jiaming Song, Ashish Sabharwal, Stefano Ermon
    Neural Information Processing Systems (NeurIPS), 2020
    [paper] [code]
  2. Approximating the Permanent by Sampling from Adaptive Partitions
    Jonathan Kuck, Tri Dao, Hamid Rezatofighi, Ashish Sabharwal, Stefano Ermon
    Neural Information Processing Systems (NeurIPS), 2019
    [paper] [code] [poster]
  3. Adaptive Hashing for Model Counting
    Jonathan Kuck, Tri Dao, Shenjia Zhao, Burak Bartan, Ashish Sabharwal, Stefano Ermon
    Uncertainty in Artificial Intelligence (UAI), 2019
    [paper] [code] [poster]
  4. Approximate Inference via Weighted Rademacher Complexity
    Jonathan Kuck, Ashish Sabharwal, Stefano Ermon
    Conference on Artificial Intelligence (AAAI), 2018
    [paper] [code] [blog]
  5. Query-Based Outlier Detection in Heterogeneous Information Networks
    Jonathan Kuck*, Honglei Zhuang*, Xifeng Yan, Hasan Cam, Jiawei Han
    International Conference on Extending Database Technology (EDBT), 2015


  1. Privacy Preserving Recalibration under Domain Shift
    Rachel Luo, Shengjia Zhao, Jiaming Song, Jonathan Kuck, Stefano Ermon, Silvio Savarese


Winter 2018, Stanford: head course assistant for Probabilistic Graphical Models


I like sports. I enjoy the outdoors, rock climbing, tennis, and rolling on balance balls. I used to focus on speedskating.