His research investigates the theoretical foundations of machine learning with a focus on societal impact and welfare. In addition, he has worked in a number of application areas, highlighted by work on healthcare, digital forensics, geophysics, energy, transportation, forestry, and finance. He is a recipient of best paper awards/candidates at FAccT’23, ICDM’23, DAMI, and ICDM’21, as well as the NSF CRII Award and recognition in the AAAI’24 New Faculty Highlights. He also regularly serves in the organizing committees across computer science and interdisciplinary venues, most recently Travel Award Chair at AAAI'24, Volunteer Chair at WSDM’24 and Student Program Chair at AIES’23.