Publications

Discovery and Deployment of Emergent Robot Swarm Behaviors via Representation Learning and Real2Sim2Real Transfer

Connor Mattson, Varun Raveendra, Ricardo Vega, Cameron Nowzari, Daniel S Drew, Daniel S Brown

International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2025), May 2025.

Early Failure Detection in Autonomous Surgical Soft-Tissue Manipulation via Uncertainty Quantification

Jordan Thompson, Ronald Koe, Anthony Le, Gabriella Goodman, Daniel S. Brown, Alan Kuntz

Conference, Month, Year

Toward Zero-Shot User Intent Recognition in Shared Autonomy

Atharv Belsare*, Zohre Karimi*, Connor Mattson*, Daniel S. Brown

IEEE/ACM International Conference on Human-Robot Interaction (HRI), 2025.

* denotes equal contribution.

Representation Learning for Cross-Embodiment Inverse Reinforcement Learning from Mixed-Quality Demonstrations

Anurag Aribandi*, C. Mattson* and Daniel S. Brown

Conference, Month, Year

* denotes equal contribution.

(Recently Accepted, Links available soon)

Reward Learning from Suboptimal Demonstrations with Applications in Surgical Electrocautery

Zohre Karimi*, Shing-Hei Ho*, Bao Thach, Alan Kuntz and Daniel S. Brown

International Symposium on Medical Robotics (ISMR), August 2024.

* denotes equal contribution.

Modeling Kinematic Uncertainty of Tendon-Driven Continuum Robots via Mixture Density Networks

Jordan Thompson, Brian Y. Cho, Daniel S. Brown and Alan Kuntz

International Symposium on Medical Robotics (ISMR), August 2024.

Autonomous Assessment of Demonstration Sufficiency via Bayesian Inverse Reinforcement Learning

Tu Trinh, Haoyu Chen and Daniel S. Brown

Human-Robot Interaction, March 2024.

Quantifying Assistive Robustness Via the Natural-Adversarial Frontier

Jerry Zhi-Yang He, Zackory Erickson, Daniel S. Brown and Anca D. Dragan

Conference on Robot Learning (CoRL), October 2023.

* denotes equal contribution.

Leveraging Human Feedback to Evolve and Discover Novel Emergent Behaviors in Robot Swarms

C. Mattson and Daniel S. Brown

Genetic and Evolutionary Computation Conference (GECCO), July 2023.

Exploring Behavior Discovery Methods for Heterogeneous Swarms of Limited-Capability Robots

C. Mattson, J. C. Clark, and Daniel S. Brown

Exploring Behavior Discovery Methods for Heterogeneous Swarms of Limited-Capability Robots, June 2023.

Player-Centric Procedural Content Generation: Enhancing Runtime Customization by Integrating Real-Time Player Feedback

Nancy N Blackburn*, M Gardone* and Daniel S Brown

Companion Proceedings of the Annual Symposium on Computer-Human Interaction in Play (CHI PLAY), October 2023.

* denotes equal contribution.

Efficient Preference-Based Reinforcement Learning Using Learned Dynamics Models

Yi Liu*, Gaurav Datta*, Ellen Novoseller and Daniel S. Brown

International Conference on Robotics and Automation (ICRA), February 2024.

* denotes equal contribution.

Contextual Reliability: When Different Features Matter in Different Contexts

Gaurav Ghosal, Amrith Setlur, Daniel S. Brown, Anca D. Dragan and Aditi Raghunathan

International Conference on Machine Learning (ICML), July 2023.

Causal Confusion and Reward Misidentification in Preference-Based Reward Learning

Jeremy Tien, Jerry Zhi-Yang He, Zackory Erickson, Anca D. Dragan and Daniel S. Brown

International Conference on Learning Representations (ICLR), March 2023.

Benchmarks and Algorithms for Offline Preference-Based Reward Learning

Daniel Shin, Anca D. Dragan and Daniel S. Brown

Transactions on Machine Learning Research (TMLR), January 2023.

SIRL: Similarity-based Implicit Representation Learning

Andreea Bobu, Yi Liu, Rohin Shah, Daniel S. Brown and Anca D. Dragan

International Conference on Human Robot Interaction (HRI), March 2023.

Towards a Gaze-Driven Assistive Neck Exoskeleton via Virtual Reality Data Collection

Jordan Thompson, Haohan Zhang and Daniel S. Brown

HRI Workshop on Virtual, Augmented, and Mixed-Reality for Human-Robot Interactions, March 2023.

The Effect of Modeling Human Rationality Level on Learning Rewards from Multiple Feedback Types.

Gaurav R. Ghosal, Matthew Zurek, Daniel S. Brown and Anca D. Dragan

AAAI Conference on Artificial Intelligence (AAAI), Month 2023.

* denotes equal contribution.