Ryan Hoque

I am a final year PhD candidate in the UC Berkeley EECS department and a researcher in Robotics and Artificial Intelligence. I am advised by Ken Goldberg and am part of the Berkeley Artificial Intelligence Research (BAIR) lab. I have also been fortunate to collaborate with researchers from Google DeepMind, NVIDIA SRL, Meta FAIR, Honda Research Institute, Siemens AI, and Uber ATG (acq. Aurora). My research primarily consists of scalable algorithms for robot imitation learning.

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My PhD research is focused on the development of interactive imitation and reinforcement learning algorithms that scale to large robot fleets performing complex tasks (e.g., manipulation). In my undergraduate and Master's research, I worked on learning algorithms for robotic manipulation of deformable objects. In addition to selected publications below (see my CV for the full list), check out:

     Imitation Learning and Fleet Learning Algorithms

ThriftyDAgger: Budget-Aware Novelty and Risk Gating for Interactive Imitation Learning
Ryan Hoque, Ashwin Balakrishna, Ellen Novoseller, Daniel S. Brown, Albert Wilcox, Ken Goldberg
Conference on Robot Learning (CoRL) 2021. Oral Presentation (6.5% of papers).
[Paper] [YouTube] [Website] [Twitter TL;DR]

A novel interactive imitation learning algorithm that reasons about both state novelty and risk to actively query for human interventions more efficiently than prior algorithms.

Fleet-DAgger: Interactive Robot Fleet Learning with Scalable Human Supervision
Ryan Hoque, Lawrence Yunliang Chen, Satvik Sharma, Karthik Dharmarajan, Brijen Thananjeyan, Pieter Abbeel, Ken Goldberg
Conference on Robot Learning (CoRL) 2022. Oral Presentation (6.5% of papers).
[Paper] [YouTube] [Website] [Twitter TL;DR]

We introduce new formalism, algorithms, and open-source benchmarks for "Interactive Fleet Learning": interactive learning with multiple robots and multiple humans.

Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Open X-Embodiment Collaboration (incl. myself and 172 other authors)
IEEE International Conference on Robotics and Automation (ICRA) 2024. Best Conference Paper Award.
[Paper] [Website] [Twitter TL;DR]

(In collaboration with Google DeepMind and 33 academic labs) Cross-embodiment fleet learning with heterogeneous robots. An open-source dataset of 1M+ robot trajectories from 22 robot embodiments, and results with robot foundation models trained on this data.

IIFL: Implicit Interactive Fleet Learning from Heterogeneous Human Supervisors
Gaurav Datta*, Ryan Hoque*, Anrui Gu, Eugen Solowjow, Ken Goldberg
Conference on Robot Learning (CoRL) 2023.
[Paper] [Twitter TL;DR]

An extension of Interactive Fleet Learning to heterogeneous and multimodal human supervision, including a novel approach for quantifying uncertainty in energy-based models.

     Learning Algorithms for Deformable Object Manipulation

Learning to Fold Real Garments with One Arm: A Case Study in Cloud-Based Robotics Research
Ryan Hoque*, Kaushik Shivakumar*, Shrey Aeron, Gabriel Deza, Aditya Ganapathi, Adrian Wong, Johnny Lee, Andy Zeng, Vincent Vanhoucke, Ken Goldberg
IEEE International Conference on Robots and Systems (IROS) 2022.
[Paper] [Website]

(In collaboration with Google DeepMind) We perform the first systematic benchmarking of fabric manipulation algorithms with Google Reach, a prototype hardware testbed for low-latency remote robot control over the Internet.

VisuoSpatial Foresight for Physical Sequential Fabric Manipulation
Ryan Hoque*, Daniel Seita*, Ashwin Balakrishna, Aditya Ganapathi, Ajay Tanwani, Nawid Jamali, Katsu Yamane, Soshi Iba, Ken Goldberg
Autonomous Robots. Vol 45(5), 2021.
[Paper] [Website]

(In collaboration with Honda Research Institute) A novel model-based reinforcement learning technique that trains a visual dynamics model for sequentially manipulating fabric toward a variety of goal images, entirely from random interaction RGBD data in simulation.

Not Research

I'm a Bay Area native and a lifelong bear: I earned my B.S. and M.S. in EECS at UC Berkeley and am still here for my PhD. Outside of research, I have an eclectic mix of hobbies including playing piano covers of heavy metal bands, reading and writing about philosophy (especially metaphysics), traveling, and enjoying the outdoors. For the philosophically inclined, I wrote an essay in 2020 in which I synthesize Western and Eastern thought to answer the age-old "meaning of life" question. I'm currently working on a significantly revised version as a full-length book, but it's very much still in progress...!

Website template from BAIR alum Jon Barron.