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researcher

Ryan Hoque

18 papers hereh-index 162.2k citations25 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author7
  • middle author8

Across the 15 of 18 papers where every author was matched, so the position is known.

fields
  • cs.RO17
  • cs.CV1
same name
  • Ryan Hoque — 3 papers, h 3
  • Ryan Hoque — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192025
most citedOpen X-Embodiment: Robotic Learning Datasets and RT-X Models

103 citations · 191 across the 17 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.RO2023★ 103 cited

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

Embodiment Collaboration, Abby O'Neill, Abdul Rehman +291

Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, thi…

cs.RO2023

FogROS2-SGC: A ROS2 Cloud Robotics Platform for Secure Global Connectivity

Kaiyuan Chen, Ryan Hoque, Karthik Dharmarajan +5

The Robot Operating System (ROS2) is the most widely used software platform for building robotics applications. FogROS2 extends ROS2 to allow robots to access cloud computing on de…

cs.RO2023

IIFL: Implicit Interactive Fleet Learning from Heterogeneous Human Supervisors

Gaurav Datta, Ryan Hoque, Anrui Gu +2

Imitation learning has been applied to a range of robotic tasks, but can struggle when robots encounter edge cases that are not represented in the training data (i.e., distribution…

cs.RO2023★ 4 cited

Semantic Mechanical Search with Large Vision and Language Models

Satvik Sharma, Huang Huang, Kaushik Shivakumar +4

Moving objects to find a fully-occluded target object, known as mechanical search, is a challenging problem in robotics. As objects are often organized semantically, we conjecture…

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