Teaching:

Talks and Events:

  • Simulation-Based Data Generation: Bridging the Gap to the Real World, RSS 2024 workshop on “Data Generation for Robotics”, July 2024
  • Language as Bridge between Simulation and the Real World, ICRA24 workshop Vision-Language Models for Navigation and Manipulation (VLMNM), May 2024
  • Learning to control contact-rich interactions, UT Center for Non-Linear Dynamics, February 2024
  • Mobile Manipulation: Towards Truly Autonomous Service Robots, KAIST Remote Lecture, December 2023
  • Technologies for Household Robotics, Texas Robotics Symposium, October 2023
  • Launching event for Queer in Robotics at IROS’23, October 2023
  • Perceiving to Interact, Interacting to Perceive, IROS’23 workshop on Integrated Perception, Planning, and Control for Physically and Contextually-Aware Robot Autonomy, October 2023
  • Probabilistic Modeling, MOOC course Essentials of AI for Life and Society, September 2023
  • Learning Contact-rich Interaction Control, RSS’23 workshop on Robotics and AI: The Future of Industrial Assembly Tasks, July 2023
  • What can robots learn from videos about long-horizon activities?, UT Austin Computer Vision Group (Prof. Grauman), April 2023
  • Mobile Manipulation: Integration vs. Factorization, TEROS’23. April 2023
  • RobIN: A Quest for Intelligence at GradFest’23. This presentation summarizes some of the core ideas of our lab and broad future research directions.
  • Talk at the Texas Innovation Center’s Engineering Education and Research Center. More info. Feb 8, 2023
  • Datasets in Robotics at the Living and Working with Robots initiative, part of the Good Systems Challenge, Jan 25, 2023
  • Studying Physically Interactive Intelligence by Benchmarking Household Activities. Invited talk at the Texas Robotics Portfolio Seminar, Sept. 27, 2022
  • RobIN: The Robotic Interactive Intelligence Lab. Invited talk at CS398T: Supervised Teaching in Computer Science, 9/20/22
  • Applications of Virtualizing and Simulating Real People for Embodied AI. Invited talk at the Stanford Metaverse Workshop of the 2022 HAI Spring Conference on Key Advances in Artificial Intelligence, 4/12/22

Curriculum Vitae:

Bio (for talks):


Roberto Martin-Martin is an Assistant Professor of Computer Science at the University of Texas at Austin. His research bridges robotics, computer vision, and machine learning, focusing on enabling robots to operate autonomously in human-centric, unstructured environments such as homes and offices. To achieve this, he develops advanced AI algorithms grounded in reinforcement learning, imitation learning, planning, and control. His work also addresses challenges in robot perception, including pose estimation, tracking, video prediction, and scene understanding.

Martin-Martin earned his Ph.D. from the Berlin Institute of Technology (TUB) with Oliver Brock and later conducted postdoctoral research at the Stanford Vision and Learning Lab under the mentorship of Fei-Fei Li and Silvio Savarese. His contributions have been recognized with several prestigious awards, including the RSS Best Systems Paper Award, ICRA Best Paper Award, IROS Best Mechanism Award, RSS Pioneer designation, and he was part of the team that won the Amazon Picking Challenge. Beyond academia, he serves as chair of the IEEE Technical Committee on Mobile Manipulation and is a co-founder of QueerInRobotics, promoting diversity and inclusion in the field.