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About

Amirreza Razmjoo is a robotics researcher whose work sits at the intersection of geometry, control, and learning for dexterous manipulation. His primary contributions center on representing and reasoning about robot geometry and configuration spaces using signed distance fields (SDFs). In his highly cited 2024 paper, "Representing Robot Geometry as Distance Fields," he introduced Robot Distance Fields (RDFs)—a method that extends SDF principles to articulated kinematic chains using Bernstein polynomials, enabling whole-body manipulation. This work, along with "Configuration Space Distance Fields for Manipulation Planning" (14 citations), provides a powerful implicit representation that seamlessly integrates with control, optimization, and learning pipelines. Razmjoo also advances skill acquisition through his work on geometric optimal control for imitation and generalization of manipulation skills (9 citations), and on logic learning from demonstrations for multi-step tasks in dynamic environments (7 citations). His earlier research on combining emulation and imitation for physical assistance skills (4 citations) rounds out a portfolio that is both theoretically rigorous and practically impactful. With over 50 total citations and multiple first-authored papers in top venues, Razmjoo is shaping how robots understand and interact with their environments.