I aspire to build machine learning applications that are painless
to compose, easier to reason about, and safer to use.
I work towards these goals by studying the design of programming languages.
I focus on developing the
Hakaru probabilistic programming system
as part of
Prof. Chung-chieh Shan's group.
I have also built a library for composing MCMC sampling algorithms, which can be found
in the mcmc-samplers
- Probabilistic inference by program transformation in Hakaru (system description)
- Praveen Narayanan, Jacques Carette, Wren Romano, Chung-chieh Shan, and Robert Zinkov.
FLOPS 2016 (13th international symposium on functional and logic programming).
- Slides, presented in Kochi, Japan, Mar 4 2016.
- Building blocks for exact and approximate inference
- Jacques Carette, Chung-chieh Shan, Praveen Narayanan, Wren Romano, and Robert Zinkov.
- Black box learning and inference workshop at
- Poster, presented at the workshop in Montréal, Dec 12 2015.
- A combinator library for MCMC sampling
- Praveen Narayanan and Chung-chieh Shan.
3rd NIPS Workshop on Probabilistic Programming at
- Poster, presented at the workshop in Montréal, Dec 13 2014.
- Slides, from talks given at:
- PL-Wonks talk series at Indiana University, Bloomington, Nov 21 2014.
- Seminar on probabilistic programming, Indiana University, Bloomington, May 8 2014.
- Graph algorithms in a guaranteed-deterministic language
- Praveen Narayanan and Ryan R. Newton.
5th Workshop on Determinism and Correctness in Parallel Programming, at
- Slides, from a talk given at the workshop in Salt Lake City, Mar 2 2014.
Discrete structures for computer science - spring 2013
Introduction to programming I - fall 2012
BA in Mathematics
and Physics 2012, Cornell University.
Under Prof. Anil Nerode
I studied modal logic, and in the
I studied 4He solid dynamics.