Principal Investigator

Majid Khadiv is an assistant professor in the school of Computation, Information and Technology (CIT). He leads the chair of AI Planning in Dynamics Environment at TUM and is also a member of the Munich Institute of Robotics and Machine Intelligence (MIRMI). Prior to joining TUM, he was a research scientist at the Empirical Inference department at the Max Planck Institute for Intelligent systems. Before that he was a postdoctoral researcher in the Machines in Motion, a joint laboratory between New York University and Max Planck Institute. Since the start of his PhD in 2012, he has been performing research on motion planning, control and learning for legged robots ranging from quadrupeds, lower-limb exoskeleton up to humanoid robots. He is currently an associate editor of the International Journal of Robotics Research (IJRR) and has served for several years as associate editor in major robotics conferences (ICRA, IROS, Humanoids).

Contact: majid.khadivATtum.de

Office: R121, Georg-Brauchle-Ring 60_62, 80992 München

Victor Dhédin is a PhD candidate in ATARI lab. He graduated from CentraleSupélec (University Paris-Saclay) in France with a Master's degree in Data and Information Sciences in addition to a dual degree in Robotics from the University of Lorraine. He does research on using machine learning to control robotic systems with an emphasis on legged locomotion.

Shafeef Omar is a PhD candidate at ATARI lab, specializing in robotics and artificial intelligence. Previously, he was a research fellow (2022-2024) with the Dynamic Legged Systems Lab headed by Dr. Claudio Semini at the Istituto Italiano di Tecnologia where he worked on learning-based foothold adaptations for legged robot locomotion on rough terrain. Before that, he was a research associate (2021-2022) with the Artificial Intelligence and Robotics Laboratory headed by Prof. Suresh Sundaram at the Indian Institute of Science Bangalore where he worked on continual learning for mitigating catastrophic forgetting in neural networks. He graduated from the Indian Institute of Technology Madras with a Dual Degree in Engineering Design. In my current research, I focus on inducing biases using model-based priors to learn safe and robust vision-aided loco-manipulation policies for legged robots. I am broadly interested in supervised learning, reinforcement learning and control theory to apply them in robotics for control and planning in ardous scenarios.

Jorge Playán Garai is a PhD candidate in ATARI lab (Co-supervised by Christopher Mcgreavy at CERN). He obtained his BSc in Electronics and Automation Engineering from the University of Zaragoza (UNIZAR) in 2019 and his MSc in Robotics and Automation from the Polytechnic University of Madrid (UPM) in 2021. He has been working as a robotics engineer at CERN for 3 years in low-level software, control, and algorithms for robotic systems. His main research focus is in navigation for legged locomotive robots in hazardous environments.

Michał Ciebielski is a master student in the ATARI lab. He is passionate about robotics and is currently working on learning methods to improve the performance of legged locomotion. contact: michal.ciebielski@tum.de

Xun Pua is a master student in the ATARI lab. He is currently pursuing his masters in Mechanical Engineering at TUM and is interested in the design and development of robotic systems. contact: xun.pua@tum.de 

Adithya Chinnakkonda is a Robotics Engineer at Synergeticon GmbH, specializing in AMRs and Manipulators. He earned his Master's degree in Mechatronics from TU Hamburg. Previously, he served as a student researcher at the Max Planck Institute for Intelligent Systems in Tuebingen under the supervision of Prof. Khadiv. Adithya's expertise includes Reinforcement Learning, Game Theory, and Machine Learning for legged robots.