M4PO
Massively Multi-Task Multi-Embodiment Model-Based Policy Optimization across robot embodiments.
Robotics Researcher
aditya $ cat about.txt
I am a robotics and reinforcement learning researcher working on manipulation problems, in particular making the control smarter, safer and more precise.
I started at MBZUAI as a Research Engineer and am now a master's student in the Robotics Department and AIRoCS Lab. Previously, I worked with the Center for Cognitive Modeling at MIPT, where I completed my BSc in Applied Mathematics and Computer Science.
aditya $ ls research_interests/
Publications
Massively Multi-Task Multi-Embodiment Model-Based Policy Optimization across robot embodiments.
Massively Multi-Task Model-Based Policy Optimization for scalable robotic control.
Knowledge-guided manipulation using online scene graphs and multi-task reinforcement learning.
Timeline
KG-M3PO was accepted to ICRA 2026; started at MBZUAI as a Research Engineer and then became a master's student in August.
M3PO published at IROS 2025; graduated from MIPT after a thesis on multi-task RL for manipulation.
Research Engineer at the Center for Cognitive Modeling, MIPT.
Research intern at MIPT, working across control, trajectory optimization, and robot learning.