Abhinav Verma is a PhD student in the Computer Science Department at Rice University, where he is advised by Professor Swarat Chaudhuri.
Abhinav’s research lies at the intersection of machine learning and program synthesis. His work focuses on “programmatically interpretable learning”: solving learning tasks using models that can be expressed as descriptive programs in a high-level domain-specific language. Such programmatic models have several benefits, including being human interpretable and amenable to formal certification by scalable symbolic methods. The generation methods for programmatic models also provide a mechanism for systematically using domain knowledge for reducing the variance of the learner.
Abhinav received a MS degree in Mathematics from the University of Oregon. He is passionate about inclusivity in STEM, and is leading a graduate student out-reach program that engages with K-12 students from traditionally underrepresented demographics.
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