My general research interests are very broad — I’m interested in programming languages, machine learning, AI, complexity theory, algorithms, security, quantum computing, you name it. At the moment, I’m applying program synthesis techniques to automatically generate incremental update rules that can be used to accelerate approximate sampling algorithms used in probabilistic programming. In the past, I’ve applied partial evaluation and memoization to compile sampling algorithms. I am supported by an NSF Fellowship, and was supported by a Berkeley Fellowship for my first two years in grad school.
- Rohin Shah, Rastislav Bodik. 2017. Automated Incrementalization through Synthesis. In Proceedings of the First Workshop on Incremental Computing (IC ’17).
- Rohin Shah, Emina Torlak, Rastislav Bodik. 2016. SIMPL: A DSL for Automatic Specialization of Inference Algorithms. arXiv:1604.04729.
- Phitchaya Mangpo Phothilimthana, Tikhon Jelvis, Rohin Shah, Nishant Totla, Sarah Chasins, and Rastislav Bodik. 2014. Chlorophyll: synthesis-aided compiler for low-power spatial architectures. In Proceedings of the 35th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI ’14).
- PC Member, First Workshop on Incremental Computing (IC 2017)