Industrial Research

My industrial research work has been a continuation of and a massive extension of what I got to do during my Phd - Esp. in the context of scaling prototypes and models to production scale quality. Recommendation Systems, Scaling neural networks through hashing, Anomaly Detection are some of the customer driven applications I have gotten to tackle while at work. See more on Phd research below.

Phd Research

During my Phd, I worked in the areas of Optimization Theory, Compressed Sensing, Parsimonious modeling and Rank approximation problems. This included matrix rank minimization, low-rank + sparse decomposition problems and non-negative matrix factorization problems.

Phd Research Applications

My research interests took me to applications such as, “How do you best recommend movies or products to customers?” or “What are some genes that mutate in correlation with disease conditions such as cancer?” “What are the common mathematical under-pinnings behind these seemingly diverse problems?”

Publications

For a full list of publications, please refer to my google scholar profile.