I am currently a Postdoctoral Associate in the Laboratory for Information and Decision Systems (LIDS) at the Massachusetts Institute of Technology.
I am broadly interested in the mathematical foundations of machine perception: optimization, geometry and topology, abstract algebra, probability and statistics, and machine learning. My research applies the tools of these disciplines to build principled, computationally efficient, and provably robust machine perception systems that “just work” in the real world.
ScD Computer Science, 2016
Massachusetts Institute of Technology
MA Mathematics, 2010
University of Texas at Austin
BS Mathematics, 2008
California Institute of Technology
[05-Jan-2021] Our new paper on distributed certifiably-correct SLAM and rotation averaging will appear in the IEEE Transactions on Robotics
[25-Aug-2020] Our new paper presents the first distributed certifiably correct algorithms for pose-graph SLAM and rotation averaging
[16-Jul-2020] Our paper on learning to estimate rotations has received the Best Student Paper Award at Robotics: Science and Systems (RSS) 2020!