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As the Chief Data Officer of VideoAmp, I'm focused on building the next generation of video advertising that bridges across all screens: TV, mobile and desktop, by leveraging data from multiple sources and utilizing machine learning and artificial intelligence algorithms. My team of data engineers have built a Big Data platform on Apache Spark to process large volumes of data rapidly in batch, and do real-time computations. My team of data scientists are building graph-based based algorithms that combine behavioral data from multiple devices and make predictions across screens.

While working on my doctoral research at California Institute of Technology (Caltech) in Computation and Neural Systems, specializing in Machine Learning and Behavioral Economics, I was attracted to Advertising Technology as the ultimate application of the two fields. I founded Pasadena Labs out of my research at Caltech, that was rapidly bootstrapped to profitability and provides automated SEM management and optimization products to marketing aggregators and SMBs. Our clients included enterprises like Microsoft Corporation, CityGrid Media (IAC) and NewEgg. The technology continues to be used profitably and licensed by media and ecommerce companies.


Prior to that, I have created Machine Learning methods for mining massive security datasets; developed Bayesian methods for high-frequency trade-execution in finance; developed computer vision and image detection algorithms; created graph-based algorithms for gene function prediction.



VideoAmp Inc. Santa Monica, CA

Chief Data Officer


California Institute of Technology

Phd, Computation and Neural Systems

Pasadena Labs Inc. Pasadena, CA

Chief Science Officer

Runner Inc, Chai Energy, StyleWhere Inc, Angiomead Corp.

Board of Advisors


Gatsby Computational Neuroscience Unit, UCL

MPhil, Machine Learning


University of Toronto


Cerebral Media Pvt Ltd. India

Board of Directors

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