Dinesh Jayaraman is an assistant professor at UPenn CIS. Before this, he was a visiting research scientist at Facebook AI Research, Menlo Park and was a postdoctoral scholar at UC Berkeley. He received his PhD from UT Austin (2017), and his Bachelor's degree from IIT Madras (2011). Dinesh's research focuses on questions at the intersections of perception, learning, and robotic control, such as: how might perception (such as from high-resolution optical / tactile sensors) benefit from the ability to act in the world, and vice versa? And how can effective visual control algorithms that exploit these perception-action cycles help in bringing general purpose affordable robots into our homes and workplaces? Towards answering these questions, he studies a broad range of topics, from predictive models for model-based RL and planning, to self-supervised visual representation learning, active perception, visuo-tactile robotic manipulation, causal inference, visual servoing, semantic visual attributes, and zero-shot categorization.