Sanvesh Srivastava is an Assistant Professor the Department of Statistics and Actuarial Science and a member of Iowa Informatics Initiative.  His research aims to develop flexible Bayesian methods and efficient computational algorithms for big data sets, tailored for both their complexity and size.  Motivating examples include big data in genomics, medical imaging, and recommender systems.  Simultaneously optimizing for the size and complexity is a challenge with current Bayesian methods. He is developing novel and computationally tractable Bayesian methods using principles from machine learning and optimal transportation. Before coming to the University of Iowa, Sanvesh received his Ph.D. in Statistics in August, 2013 from Purdue University, where he also won I.W. Burr Award for "promise of contribution to the profession as evidenced by academic excellence in courses and exams, by the quality of research, and by excellence in teaching and consulting." After Ph.D., he spent two years at Duke University and Statistical and Applied Mathematical Sciences Institute (SAMSI) as a postdoctoral researcher.  He has extensive experience in collaborating with scientists and teaching statistics to students from diverse areas and varied expertise.