Dorsa Sadigh
Associate Professor of Computer Science, of Electrical Engineering and Senior Fellow at the Stanford Institute for Human-Centered AI
Studies robot learning and human-robot interaction, including learning from human preferences.
Dorsa Sadigh's lab at Stanford works on manipulation & robot learning and human-robot interaction & assistive robots. 86 papers since 2023, 80 at top venues, mostly CoRL and ICRA. 12 PhD students and 1 master's student. 35 alumni, most often to Google DeepMind and Meta. Applications close .
At a glance
- papers, 2023–2026
- 22/ year
- at T1 venues
- 93%
- PhD students
- 12
- MS students
- 1
- alumni listed
- 35
Papers by yearfrom the lab homepage, 2023–2026
- 11 papers2026 · T1 10 · collecting
- 19 papers2025 · T1 17
- 28 papers2024 · T1 26
- 28 papers2023 · T1 27
T1 venuesOtherVenues: CoRL, ICRA, RSS, ICLR, ICML
Research focuspaper titles that use each topic's words
- Manipulation & robot learning57 papers
- Human-robot interaction & assistive robots30 papers
- human-robot3 papers
- studies robot0 papers
- human-robot interaction0 papers
Paper list
From the lab homepage.
202611 papers
- RA-LA Taxonomy for Evaluating Generalist Robot Manipulation Policies (opens in a new tab)
- ICRA (T1)Cross-Embodiment Transfer via Behavior-Aligned Representations (opens in a new tab)
- ICLR (T1)EXPO: Stable Reinforcement Learning with Expressive Policies (opens in a new tab)
- ICRA (T1)HoMeR: Learning In-the-Wild Mobile Manipulation via Hybrid Imitation and Whole-Body Control (opens in a new tab)
- ICRA (T1)Physically-Grounded Data Generation via Video Diffusion Models
- TMLR (T1)Policy Learning with a Language Bottleneck (opens in a new tab)
- ICLR (T1)Polychromic Objectives for Reinforcement Learning (opens in a new tab)
- ICRA (T1)RoboCade: Gamifying Robot Data Collection (opens in a new tab)
- ICLR (T1)Value Flows (opens in a new tab)
- ICLR (T1)What Matters for Batch Online Reinforcement Learning in Robotics? (opens in a new tab)
- ICRA (T1)Will People Enjoy a Robot Trainer? A Case Study with Snoopie the Pacerbot (opens in a new tab)
202519 papers
- CoRL (T1)Action-Free Reasoning for Policy Generalization (opens in a new tab)
- RSS (T1)Bridging Perception and Action: Spatially-Grounded Mid-Level Representations for Robot Generalization (opens in a new tab)
- CoRL (T1)Data Retrieval with Importance Weights for Few-Shot Imitation Learning (opens in a new tab)
- ICML (T1)Diffusion Models are Secretly Exchangeable: Parallelizing DDPMs via Auto Speculation (opens in a new tab)
- ICRA (T1)Efficiently Generating Expressive Quadruped Behaviors via Language-Guided Preference Learning (opens in a new tab)
- CoRL (T1)Gen2Act: Human Video Generation in Novel Scenarios enables Generalizable Robot Manipulation (opens in a new tab)
- ICRA (T1)How to Train Your Robots? The Impact of Demonstration Modality on Imitation Learning (opens in a new tab)
- ICML (T1)Latent Diffusion Planning for Imitation Learning (opens in a new tab)
- RA-LMotIF: Motion Instruction Fine-tuning (opens in a new tab)
- ICRA (T1)MOTION TRACKS: A Unified Representation for Human-Robot Transfer in Few-Shot Imitation Learning (opens in a new tab)
- RA-LProVox: Personalization and Proactive Planning for Situated Human-Robot Collaboration (opens in a new tab)
- ICRA (T1)RoboCrowd: Scaling Robot Data Collection through Crowdsourcing (opens in a new tab)
202428 papers
- IJRR (T1)Active Preference-Based Gaussian Process Regression for Reward Learning and Optimization (opens in a new tab)
- Journal of Transactions on Human Robotics InteractionBatch Active Learning of Reward Functions from Human Preferences (opens in a new tab)
- ICML (T1)Chain of Code: Reasoning with a Language Model-Augmented Code Emulator (opens in a new tab)
- ICLR (T1)Contrastive Preference Learning: Learning from Human Feedback without RL (opens in a new tab)
- ICRA (T1)Distilling and Retrieving Generalizable Knowledge for Robot Manipulation via Language Corrections (opens in a new tab)
- RSS (T1)DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset (opens in a new tab)
- RSS (T1)Efficient Data Collection for Robotic Manipulation via Compositional Generalization (opens in a new tab)
- RSS (T1)Explore until Confident: Efficient Exploration for Embodied Question Answering (opens in a new tab)
- RSS (T1)FLAIR: Feeding via Long-horizon AcquIsition of Realistic dishes (opens in a new tab)
- CoRL (T1)FlowRetrieval: Flow-Guided Data Retrieval for Few-Shot Imitation Learning (opens in a new tab)
- HRI (T1)Generative Expressive Robot Behaviors using Large Language Models (opens in a new tab)
- ICRA (T1)How to Prompt Your Robot: A Prompt Book for Manipulation Skills with Code as Policies (opens in a new tab)
202328 papers
- HRI (T1)"No, to the Right" – Online Language Corrections for Robotic Manipulation via Shared Autonomy (opens in a new tab)
- ICRA (T1)Active Reward Learning from Online Preferences (opens in a new tab)
- RSS (T1)Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasets (opens in a new tab)
- NeurIPS (T1)Data Quality in Imitation Learning (opens in a new tab)
- ICML (T1)Distance Weighted Supervised Learning for Offline Interaction Data (opens in a new tab)
- NeurIPS (T1)Diverse Conventions for Human-AI Collaboration (opens in a new tab)
- ICML (T1)Generating Language Corrections for Teaching Physical Control Tasks (opens in a new tab)
- CoRL (T1)Gesture-Informed Robot Assistance via Foundation Model (opens in a new tab)
- CoRL (T1)HYDRA: Hybrid Robot Actions for Imitation Learning (opens in a new tab)
- ICRA (T1)In-Mouth Robotic Bite Transfer with Visual and Haptic Sensing (opens in a new tab)
- NeurIPS (T1)Inverse Preference Learning: Preference-based RL without a Reward Function (opens in a new tab)
- CoRL (T1)KITE: Keypoint-Conditioned Policies for Semantic Manipulation (opens in a new tab)
Where alumni went35 listed, 13% to industry
Industry 2Academia 14
Most often to
- Google DeepMind
- Meta
Also to
- MIT
- Stanford University
- UC Berkeley
Apply to StanfordFall 2027
Stanford Computer Science PhD
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