I am a first year PhD student in MIT’s EECS Department advised by Professor Pablo Parrilo and Professor Russ Tedrake. I am broadly interested in pushing the frontier of control theory and its application to robotics by making advances in the fields of optimization and machine learning, and am grateful to be supported by MIT’S Hewlett Packard Fellowship
As the complexity of cyber-physical systems increases, modelling, controlling, and verifying the performance of these systems is being increasingly challenged. Data-driven techniques have shown great promise in this domain, helping us solve challenging manipulation tasks and computationally difficult scheduling tasks. Despite their success, these techniques can be brittle making their deployment in safety-critical scenarios questionable.
My research seeks to exploit common structures found in complex cyber-physical systems to overcome the current challenges in their control and verification. By combining tools from control theory, optimization, and machine learning my work seeks to make these systems robust enough that they can be safely deployed in our daily lives.
Prior to coming to MIT, I spent four wonderful years at the University of Pennsylvania where I completed my Bachelors in Electrial Engineering and Mathematics as well as my Masters in Robotics in 2020. While there, I wrote my Master’s Thesis under the supervision of Professor Alejandro Ribeiro and completed my Senior Design Capstone under Professor Manfred Morari. During the summer of 2019, I worked as a perception engineering intern at Uber ATG, improving the sensor fusion algorithms of the autonomous vehicle’s on board radar system.
I am enthusiastic about spending time outside hiking, skiing, and sailing. I have also been fencing competitively since 2005, including throughout my time at Penn.