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 connects robotics, computer vision, and machine learning. He studies and develops novel AI algorithms that enable robots to perform tasks in human uncontrolled environments such as homes and offices. He creates novel decision-making solutions based on reinforcement learning, imitation learning, planning, and control in that endeavor. He explores topics in robot perception, such as pose estimation and tracking, video prediction, and parsing. Martin-Martin received his Ph.D. from the Berlin Institute of Technology (TUB) before a postdoctoral position at the Stanford Vision and Learning Lab under the supervision of Fei-Fei Li and Silvio Savarese. His work has been selected for the RSS Best Systems Paper Award, RSS Pioneer, ICRA Best Paper Award, Winner of the Amazon Picking Challenge, and has been a finalist for ICRA, RSS, and IROS Best Paper. He is chair of the IEEE Technical Committee in Mobile Manipulation and co-founder of QueerInRobotics.