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Develop and validate decoders that map high-density surface EMG into continuous force and joint angles, exploit a 30–100 ms intent window, design data capture and labeling protocols, run experiments on signal quality and generalization, and collaborate with robotics ML team for real-time integration.

Develop and debug embedded firmware for multi-camera and HD-sEMG synchronization, implement sub-millisecond hardware timestamping, build on-device capture/offload pipelines, perform hardware bring-up and low-level debugging, and collaborate with ML on data format and integrity.

Design and improve reinforcement-learning and post-training methods for robust robot policies. Train and evaluate models on human-demonstration data, build scalable training and evaluation pipelines, collaborate with RAI, hardware, and data teams, and deploy research results to production robots.

Own low-level control of humanoid arms and hands: design joint and whole-arm controllers, tune for smooth, safe, precise manipulation, and integrate controllers with the RAI policy stack.