Simon Stepputtis

Simon Stepputtis

Postdoctoral Fellow | Carnegie Mellon Univeristy | Robotics Institute

  • Paper: Sample-Efficient Learning of Novel Visual Concepts

    Sample-efficient extraction of novel objects, affordances, and attributes from images using symbolic domain knowledge, which will be presented at CoLLAs 2023
  • Paper: Introspective Action Advising for Interpretable Transfer Learning

    We propose an alternative approach to transfer learning between tasks based on action advising, which will be presented at CoLLAs 2023!
  • RSS 2023: Articulate Robots Workshop

    I am organizing a workshop at RSS 2023 in Daegu, Republic of Korea on Articulate Robots: Utilizing Language for Robot Learning
  • Paper: Explainable Action Advising for Multi-Agent Reinforcement Learning

    Our new paper will be presented at ICRA 2023 in London, England! Paper on arXiv
  • Paper: Modularity through Attention: Efficient Training and Transfer of Language-Conditioned Policies for Robot Manipulation

    Our new paper with our collaborators at Intel will be presented at CORL 2022 in Auckland, New Zeland! Paper on OpenReview
  • Paper: Concept Learning for Interpretable Multi-Agent Reinforcement Learning

    Interpretable concept learning for multi-agent robot systems: CORL 2022 in Auckland, New Zeland! Paper on OpenReview
  • Paper: A System for Imitation Learning of Contact-Rich Bimanual Manipulation Policies

    Our paper in collaboration with Intrinsic got accepted to IROS 2022, which we will be presenting in Kyoto, Japan. View full paper
  • IROS 2022: TOM4HAT Workshop

    I organized a workshop at IROS 2022 in Kyoto, Japan on Theory of Mind
  • Workshop: RSS Pioneers

    I was accepted to the RSS Pioneers Workshop 2022 with my work on Language-Conditioned Human-Agent Teaming.
  • Postdoctoral Fellow at Carnegie Mellon University

    I started as a postdoctoral fellow at Carnegie Mellon University (CMU) with Prof. Katia Sycara.
  • Graduation: Ph.D. in Computer Science

    I completed my Ph.D. in Computer Science at Arizona State University with Prof. Heni Ben Amor!
  • Imperial College London: Invited Talk

    I will be giving brief summary and outlook of my work presented in our NeurIPS 2020 paper at the Imperial College London!
  • Resident @ X, The Moonshot Factory

    Over the summer, I will be a resident at X, The Moonshot Factory, where I will be working on industrial manipulation tasks for Intrinsic, a robotics software and AI project at X .
  • Video: Language Conditioned Imitation Learning

    We contributed a video to the robot expo at IJCAI 2021 that is a direct extension to our NeurIPS 2020 paper. You can check out the video here!
  • Paper: Language-Conditioned Imitation Learning for Robot Manipulation Tasks

    We published a new paper at NeurIPS 2020! Our paper got accepted as a spotlight presentation (top ~4% of accepted papers). View full paper
  • Intel AI Labs: Invited Talk

    I am excited to give a talk, Language for Robotics at Intel AI Labs summarizing our efforts on learning robot policies from natural language instructions.
  • Teaching Introduction to Theoretical Computer Science at ASU

    I will be teaching CSE 355: Introduction to Theoretical Computer Science at Arizona State University as the main instructor during the upcoming Summer 2020 semester!
  • Intel AI: Talk at the Deep Learning Community

    I will be giving a talk at the Deep Learning Community of Practice titled Imitation Learning for Adaptive Robot Control Policies from Language, Vision, and Motion.
  • Workshop Paper: Imitation Learning of Robot Policies by Combining Language, Vision and Demonstration

    We contributed a workshop paper to the Workshop on Robot Learning at NeurIPS 2019!
  • Best Poster Award

    I received the Best Poster Award by Nvidia at the Southwest Robotics Symposium for my work on Neural Policy Translation for Robot Control!
  • Robotics Intern @BOSCH

    I will be joining Robot BOSCH in Sunnyvale for an internship to work on semantic data analysis with a focus on time series segmentation.
  • Paper: Extrinsic Dexterity through Active Slip Control using Deep Predictive Models

    We got our paper accepted to ICRA 2018, and I will be presenting our work in Brisbane, Australia! Paper on IEEE Xplore
  • Best Video Award

    Awarded at the International Conference on Humanoid Robots (Humanoids) 2016 for our work on Learning human-robot interactions from human-human demonstrations Video on YouTube