Shubham Derhgawen

I am a robotics graduate student at the University of California, Riverside, where I focus on embodied AI, machine learning, motion planning, and social robot navigation. My recent work spans crowd simulation for robot navigation, human-in-the-loop autonomous driving experiments, and reinforcement learning for sequential decision-making.

At UC Riverside, I have worked with the Motion Planning Lab and the Collaborative Intelligence Systems Lab on platforms for reproducible robotics evaluation and multimodal autonomous driving data collection. Before graduate school, I worked as a software developer at Vijeta Transport and as a systems engineer at Tata Consultancy Services, building production software, ETL workflows, and cloud data pipelines.

I am especially interested in robot learning, embodied intelligence, simulation-driven evaluation, and real-world autonomy. My coursework and projects have covered reinforcement learning, computer vision, natural language processing, warehouse robotics, and demonstration-augmented policy optimization.