Masoud Moghani

I am a PhD student at the University of Toronto, advised by Animesh Garg working at the intersection of robotics, machine learning, and simulation. My research focuses on robot learning for manipulation and deformable object simulation. I am also working on autonomy in surgical robotics.

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Publications

Adapt3R, an imitation learning algorithm utilizing 3D scene representations to enable zero-shot transfer to novel embodiments and camera poses.

SuFIA-BC, visual behavior cloning policies in an enhanced surgical digital twin with photorealistic human anatomical organs.

SuFIA, a framework for natural language-guided augmented dexterity for robotic surgical assistants.

ORBIT-Surgical, a physics-based surgical robot simulation framework with photorealistic rendering.

A trimodal framework for vascular shunt insertion assisted by a da Vinci Research Kit (dVRK) robotic surgical assistant.

A soft robotic approach for a steerable tip capable of guiding a small flexible insertion tube.

The design and validation of a high-performance compliant actuator for robotic manipulators.

A neural network based closed-loop torque control strategy for a compliant actuator.

A novel compliant actuator for safe robotic applications.

Technical Blogs

Teaching

Source code from Jon Barron website's source code.