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Computer Science

D-Index
41
Citations
8474
World Ranking
8730
National Ranking
3736

Overview

Dorsa Sadigh is a researcher affiliated with Stanford University in the United States, specializing in fields spanning Computer Science and Engineering. Their work primarily focuses on subfields such as Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Automotive Engineering, and Social Psychology.

The researcher's publications cover a range of topics including Reinforcement Learning in Robotics, Robot Manipulation and Learning, Multimodal Machine Learning Applications, Topic Modeling, Human Pose and Action Recognition, Traffic Control and Management, and Natural Language Processing Techniques.

Frequent publication venues for their work include:

  • arXiv (Cornell University)
  • IEEE Robotics and Automation Letters
  • 2022 International Conference on Robotics and Automation (ICRA)
  • The International Journal of Robotics Research
  • Autonomous Robots

Among recent papers associated with this researcher are:

  • "On the Opportunities and Risks of Foundation Models" (2021), arXiv (Cornell University)
  • "Toward verified artificial intelligence" (2022), Communications of the ACM
  • "Open X-Embodiment: Robotic Learning Datasets and RT-X Models" (2023), arXiv (Cornell University)
  • "Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback" (2023), arXiv (Cornell University)
  • "Social Coordination and Altruism in Autonomous Driving" (2022), IEEE Transactions on Intelligent Transportation Systems

Collaborations have been frequent with several co-authors, including:

  • Erdem Bıyık
  • Chelsea Finn
  • Jeannette Bohg
  • Suneel Belkhale
  • Siddharth Karamcheti

Best Publications

  • On the Opportunities and Risks of Foundation Models.

    Rishi Bommasani;Drew A. Hudson;Ehsan Adeli;Russ Altman

  • Planning for Autonomous Cars that Leverage Effects on Human Actions

    Dorsa Sadigh;Shankar Sastry;Sanjit A. Seshia;Anca D. Dragan

  • Reactive synthesis from signal temporal logic specifications

    Vasumathi Raman;Alexandre Donzé;Dorsa Sadigh;Richard M. Murray

  • Active preference-based learning of reward functions

    Dorsa Sadigh;Anca D. Dragan;Shankar Sastry;Sanjit A. Seshia

  • Information gathering actions over human internal state

    Dorsa Sadigh;S. Shankar Sastry;Sanjit A. Seshia;Anca Dragan

  • Hierarchical Game-Theoretic Planning for Autonomous Vehicles

    Jaime F. Fisac;Eli Bronstein;Elis Stefansson;Dorsa Sadigh

  • Planning for cars that coordinate with people: leveraging effects on human actions for planning and active information gathering over human internal state

    Dorsa Sadigh;Nick Landolfi;Shankar S. Sastry;Sanjit A. Seshia

  • A learning based approach to control synthesis of Markov decision processes for linear temporal logic specifications

    Dorsa Sadigh;Eric S. Kim;Samuel Coogan;S. Shankar Sastry

  • Toward verified artificial intelligence

    Unknown

  • Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback

    Unknown

  • Safe Control under Uncertainty with Probabilistic Signal Temporal Logic.

    Dorsa Sadigh;Ashish Kapoor

  • OpenVLA: An Open-Source Vision-Language-Action Model

    Unknown

  • Towards Verified Artificial Intelligence

    Sanjit A. Seshia;Dorsa Sadigh

  • Multi-Agent Generative Adversarial Imitation Learning

    Jiaming Song;Hongyu Ren;Dorsa Sadigh;Stefano Ermon

  • Synthesis for Human-in-the-Loop Control Systems

    Wenchao Li;Dorsa Sadigh;S. Shankar Sastry;Sanjit A. Seshia

  • Open X-Embodiment: Robotic Learning Datasets and RT-X Models

    Unknown

  • Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration0

    Unknown

  • SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities

    Unknown

  • Automating exercise generation: a step towards meeting the MOOC challenge for embedded systems

    Dorsa Sadigh;Sanjit A. Seshia;Mona Gupta

  • Data-Driven Probabilistic Modeling and Verification of Human Driver Behavior

    Dorsa Sadigh;Katherine Rose Driggs-Campbell;Alberto Puggelli;Wenchao Li

  • Learning Reward Functions by Integrating Human Demonstrations and Preferences

    Malayandi Palan;Gleb Shevchuk;Nicholas Charles Landolfi;Dorsa Sadigh

  • Efficient and Trustworthy Social Navigation via Explicit and Implicit Robot–Human Communication

    Yuhang Che;Allison M. Okamura;Dorsa Sadigh

  • Multi-Agent Generative Adversarial Imitation Learning

    Jiaming Song;Hongyu Ren;Dorsa Sadigh;Stefano Ermon

  • Dynamic multi-robot task allocation under uncertainty and temporal constraints

    Shushman Choudhury;Jayesh K. Gupta;Mykel J. Kochenderfer;Dorsa Sadigh

  • Active Preference-Based Gaussian Process Regression for Reward Learning

    Erdem Biyik;Nicolas Huynh;Mykel J. Kochenderfer;Dorsa Sadigh

  • When Humans Aren't Optimal: Robots that Collaborate with Risk-Aware Humans

    Minae Kwon;Erdem Biyik;Aditi Talati;Karan Bhasin

  • Learning Reward Functions by Integrating Human Demonstrations and Preferences

    Malayandi Palan;Nicholas C. Landolfi;Gleb Shevchuk;Dorsa Sadigh

Frequent Co-Authors

Sanjit A. Seshia
Sanjit A. Seshia University of California, Berkeley
Shankar Sastry
Shankar Sastry University of California, Berkeley
Jeannette Bohg
Jeannette Bohg Stanford University
Mykel J. Kochenderfer
Mykel J. Kochenderfer Stanford University
Stefano Ermon
Stefano Ermon Stanford University
Anca D. Dragan
Anca D. Dragan University of California, Berkeley
Percy Liang
Percy Liang Stanford University
Noah D. Goodman
Noah D. Goodman Stanford University
Chelsea Finn
Chelsea Finn Stanford University
Alberto Sangiovanni-Vincentelli
Alberto Sangiovanni-Vincentelli University of California, Berkeley

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