Deepak Agarwal is currently a principal research scientist at Yahoo! Research. Prior to joining Yahoo!, he was a member of the statistics department at AT&T Research.
He obtained a Ph.D in statistics from the University of Connecticut; his thesis advisor was Alan Gelfand. At AT&T, he worked on methods for mining massive graphs, statistical models for social network analysis, anomaly detection using a time series approach and computational approaches for scaling spatial scan statistic to large data sets.
His current research interests at Yahoo! include content optimization, large scale regression for massive, sparse and noisy data via "feature aggregation", anomaly detection in high dimensional spaces, explore/exploit and statistical methods for social network analysis.
Deepak won a best research paper award at Joint Statistical Meetings 2001 for his thesis work which studied deforestation patterns in Madagascar using a two-stage spatial regression model, the best applications paper award at Siam Data Mining 2004 for his Bayesian modeling work on large sparse social networks via stochastic blockmodels and more recently the best research paper award at KDD 2007 for his work that propose a general class of models for large sparse dyadic data. He regularly serves on program committees of prestigious data mining conferences like KDD, SDM and has organized several invited sessions at Joint Statistical Meetings. He is Associate editor of Journal of the American Statistica Association and Applied Stochastic Models in Business and Industry.