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About

Morteza Azad is a robotics researcher whose work spans robot manipulation, balance control, whole-body motion planning, and physical human-robot interaction. His research is particularly distinguished by its focus on enabling robots to operate robustly in unstructured, real-world environments where contacts, uncertainty, and underactuation present significant challenges. Among his most influential contributions is his work on uncertainty-aware robot pushing using model predictive path integral control, which combines learned forward models with robust planning to achieve reliable manipulation — garnering 39 citations. His involvement in the EU FP7 CoDyCo project (30 citations) reflects his engagement with large-scale collaborative efforts to develop whole-body controllers capable of safe physical human-robot interaction. Azad has also made foundational contributions to balance control for legged and underactuated robots, introducing angular momentum-based frameworks that remain widely referenced across the field. A recurring theme in his research is the rigorous analysis of robot capability through tools like dynamic manipulability, including a notable extension to center-of-mass accelerations (15–24 citations). His work on contact constraint estimation using proprioception further demonstrates his commitment to practical, sensor-efficient solutions. Collectively, his publications reflect a researcher dedicated to bridging theoretical robotics with deployable, physically intelligent systems.