I'm a rising junior at MIT, currently pursuing my B.S. in Computer Science and Electrical Engineering. I enjoy and place a strong focus on robotics and machine learning, particularly reinforcement learning and it's applications to Sim2Real training for whole body control of humanoids. I currently work with the Improbable AI Lab, where I develop reinforcement learning pipelines for humanoid robots, experiment with policy ensembles, and scale data collection for visuomotor policies. I’ve also contributed to projects across the robotics stack—from teleoperation systems to control tuning—during internships at [Stealth Robotics Startup] and Tangible Robotics.
My work blends low-level programming, algorithmic rigor, and hands-on hardware debugging. I'm particularly interested in the Sim2Real problem and enabling intelligent robotic behaviors through data-efficient learning. With experience ranging from RISC-V architecture to CNN-based speech analysis, I’m driven by solving hard technical problems and building systems that actually work in the real world. Outside of academics, I play varsity soccer at MIT and enjoy diving deep into interdisciplinary research that pushes the boundaries of autonomous systems.