I am a PhD. student at U.C.L.A., co-advised by Guy Van den Broeck and Todd Millstein. My research interests include:

  • Machine Learning
  • Probabilistic Programming
  • Program Analysis
  • Computer Security

I would love to hear from you:


Sound Abstraction and Decomposition of Probabilistic Programs (pdf, bib)

Steven Holtzen, Guy Van den Broeck, Todd Millstein

International Conference on Machine Learning (ICML 2018)
Probabilistic Program Abstractions (pdf, bib)

Steven Holtzen, Todd Millstein, Guy Van den Broeck

Uncertainty in Artificial Intelligence (UAI 2017),
Seventh International Workshop on Statistical Relational AI (StarAI 2017)
Inferring Human Intent from Video by Sampling Hierarchical Plans (pdf)

Steven Holtzen*, Yibiao Zhao*, Tao Gao, Josh Tenenbaum, Song-Chun Zhu

IEEE International Conference on Intelligent Robots and Systems, (IROS 2016)
Represent and Infer Human Theory of Mind for Human-Robot Interaction (pdf)

Yibiao Zhao, Steven Holtzen, Tao Gao, Song-Chun Zhu

2015 AAAI Fall Symposium Series.
Classification system with methodology for efficient verification (link)

David Lisuk, Steven Holtzen

U.S. Patent #9390086

Invited Talks

  1. Invited talk at LAFI 2019 for our work on exact symbolic inference for probabilistic programs.
  2. Invited talk at POPL PPS 2018 for our work on probabilistic program abstractions for probabilistic program inference.
  3. Invited spotlight presentation at StarAI 2017 for our UAI work on probabilistic program abstractions.

Professional Service



  • Sept. 2017 – Present.
    PhD., Computer Science. UCLA.
  • Sept. 2015 – Jul. 2017.
    M.S., Computer Science. UCLA.
  • Sept. 2011 – Jun. 2015.
    B.S., Computer Science. UCLA.


  • July 2015 – Present.
    Sandia National Laboratories. Member of technical staff.
  • June 2014 – Sept. 2014
    Palantir Technologies. Forward Deployed Engineering Intern on the Healthcare Team (Helix).
  • Apr. 2013 – Sept. 2013
    Symantec Corporation. Security technology and response team intern.

Awards & Honors