Shaunak is a senior research scientist in the advertising science and research group. He holds a B.Tech degree from the Indian Institute of Technology (IIT) Kharagpur (2010), an M.S. degree from UCLA (2011), and a PhD degree from UCLA (2016). Making sense of web scale data from heterogenous sources using very large scale deep learning models is an integral part of his work at Yahoo Research. This includes deep user understanding, discovering relationships between online activities, inferring non-trivial yet actionable insights for advertisers, sentiment analysis, and ad creative design guidance. Shaunak's work also involves helping advertisers (via recommendations) to create better ad text and image (encompassing text generation, text and image understanding via NLP and computer vision models). His work at Yahoo Research has led to several publications in top tier conferences in machine learning (KDD, WWW, RecSys, CIKM), and over multiple patents and defensive publications around advertising. His research interests are broadly in recommender systems, relevance ranking, NLP, and user modeling.
Advertising Science, Content Understanding, Data Science, Image & Video Understanding, Information Retrieval, Machine Learning, Natural Language & Dialogue Understanding, Optimization & Feedback Control, User Modeling and Personalization