Kanak is a Research Scientist at Adobe Research in San Jose. Her research is broadly related to applying machine learning methodologies to build efficient systems. She also works on developing performant ML-based applications by leveraging parallelism and opportunities for communication efficiency. Her research on COGs optimizations has led to significant cost-savings across multiple Adobe products. Kanak earned her Ph.D. in Computer Engineering from Purdue University, West Lafayette in August 2017.