Sam Stites

My name is Sam Stites – I'm a functional programmer and Ph.D. student studying Bayesian inference and the semantics of probabilistic programming. Prior to starting my Ph.D. program, one of my more successful endeavors has been writing the Haskell bindings to PyTorch, called Hasktorch.

My research is on how to compose small, highly specialized probabilistic languages to make probabilistic programs with heterogeneous inference easier to reason about. More broadly, I'm interested in semantics, type theory, and formal verification; I often find myself typing away in an Agda file, against my better judgment.

I've lead a few different lives before I started programming. In roughly chronological order: I've lived in a few different continents, was part of a couple of circus troupes, in college and beyond, spinning fire and eventually falling for juggling. I still working on 6/7-ball occasionally. I like to mention that part of the first class of Venture for America, and met ex-presidential candidate Andrew Yang – but I find this is more of an embarrassing fact these days.

When I'm not a disheveled mess working on research I'm trying to squeeze in more sleep or parenting.

Contact: The best way to contact me is by email, just apply ROT13 to the following: [email protected]. I'm also reachable as .stites on discord.


I actively work on a rust compiler and formalization that prototypes a multi-language approaches to probabilistic inference.

A small project from my past which I actively maintain (although it's a small commitment) is redirect-to-abstract (github). If this piques your interest and you want to use it, feel free to reach out!

Projects I no longer work on, but are still going strong:

Unmaintained projects:

  • reinforce reinforcement learning in Haskell.
  • CSSR (v2). Causal State Splitting Reconstruction of recursive hidden Markov models. I coded this up with Cosma Shalizi before starting my Ph.D. studies and it is currently in an unpublished state (written in Scala). If this work is relevant to you, please contact Cosma directly and cc me.

Feel free to reach out if want to talk about stenography, Agda, or parenting in grad school.


  • Spring 2024: CS4400 Introduction to Programming Languages

  • Fall 2020: CS6220 Data Mining Techniques

#Publications and Talks

Published works include:

‍​Sam Stites, Heiko Zimmermann, Hao Wu, Eli Sennesh, Jan-Willem van de Meent Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1056-1066, 2021. (abstract, pdf, code)

Invited talks include:

  • LAFI 2024: A Multi-language Approach to Probabilistic Program Inference. Sam Stites, Steven Holtzen
  • NPFL 2018: Hasktorch: A Comprehensive Haskell Library for Differentiable Functional Programming. Sam Stites, Austin Huang


  • PLDI 2023 Student Volunteer
  • Northeastern 2022 Faculty Admissions Volunteer
  • Northeastern 2021 Ph.D. Review Committee Volunteer