Reihaneh Mirjalili
Papers
6
Total Citations
64
H-Index
5
About
Reihaneh Mirjalili is a roboticist whose work bridges classical control theory with cutting-edge AI to make robots more adaptive and intelligent. Her research spans humanoid locomotion, whole-body control, and vision-based localization, with a recent focus on integrating foundation models into robotic perception and manipulation. She made early contributions to the SURENA III humanoid robot, developing online path planning methods using Model Predictive Control (MPC) that enabled real-time walking motions. Mirjalili later advanced whole-body MPC schemes that account for vertical center-of-mass motion and external contact forces, expanding humanoid capabilities beyond flat-terrain walking. She also co-designed Surena-Mini, the first small-sized humanoid robot fabricated entirely with 3D printing, demonstrating how additive manufacturing can accelerate prototyping. More recently, Mirjalili has pioneered the use of large language and foundation models for robotics: her work FM-Loc improves visual place recognition under changing conditions by leveraging high-level semantic features, while Lan-grasp uses language models to guide semantic object grasping and placement. With over 60 citations across her most-cited papers, Mirjalili’s trajectory from classical control to AI-powered robotics illustrates a forward-looking approach that is shaping how robots perceive, plan, and interact with the world.
Research Focus
Key Achievements
Top Papers
- 1FM-Loc: Using Foundation Models for Improved Vision-Based Localization16 citations · 2023
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