I am currently a Research Scientist in Adobe Research. Broadly, I am interested in leveraging machine learning methodologies to build efficient systems. I am also exploring challenging questions pertaining to developing high-performance, communication-optimized, distributed online learning systems.

I completed my PhD from Purdue University, School of Electrical and Computer Engineering in August 2017, and was co-advised by Prof. Milind Kulkarni and Prof. Saurabh Bagchi. My dissertation has provided techniques to scale up genomic applications to handle the exponential growth in genomic data. The techniques use strategies such as exploiting parallelism, data locality, and domain knowledge. Our DSL presented efficient implementations of commonly occurring software modules in genomic applications and its compiler performed domain-specific optimizations to yield high-performance genomic applications.

While in grad school I interned at Intel Labs (PCL) and Argonne National Labs. Before joining Purdue, I worked at Salesforce.com Inc. in the Core Optimizer - Performance Engineering team.