Bingnan Huo šŸ¤–
Bingnan Huo 霍ē§‰ę„ 

Masters Student

About Me

Hi! I am Bingnan Huo (霍ē§‰ę„ ), a masters student in Data Science at Brown University. I am a member of the Intelligent Robotics Lab, led by Prof. George Konidaris, where I conduct research on reinforcement learning and robotics. My current work focuses on option generalization under the Hierarchical Reinforcement Learning framework, aiming to develop reusable skills for robotic applications.

I have contributed to multiple research projects, including a paper submitted to ICLR 2025 on learning transferable subgoals, and Iā€™m currently leading a project on applying these concepts to robotic motion planning using the Franka Emika Panda robot. Previously, I worked on medical image processing using computer vision and machine learning at Bucknell University, where I developed a system for diagnosing Facial Nerve Paralysis with over 80% accuracy.

My research interests lie at the intersection of artificial intelligence, reinforcement learning, and robotics, with a particular focus on developing AI systems that can learn and adapt to solve complex real-world tasks. I am passionate about bridging the gap between theoretical advances in AI and practical applications in robotics.

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Interests
  • Artificial Intelligence
  • Reinforcement Learning
  • Robotics
  • Psychology & Sociology
Education
  • Sc.M. Data Science

    Brown University

  • B.S. Statistics

    Bucknell University

šŸ¤– Research Overview

I am a masters student in Data Science at Brown University, where I am part of the Intelligent Robotics Lab led by Prof. George Konidaris. My research focuses on developing intelligent robotic systems that can learn and adapt to solve complex real-world tasks.

Currently, I am working on:

  • Option generalization under Hierarchical Reinforcement Learning framework for learning reusable robotic skills
  • Applying transferable subgoals with motion planning for skill generalization across tasks using the Franka Emika Panda robot
  • Developing novel approaches for learning transferable subgoals as option termination classifiers (ICLR 2025 submission)

Previously at Bucknell University, I worked on medical image processing using computer vision and machine learning, developing a system for diagnosing Facial Nerve Paralysis with over 80% accuracy.

I am actively seeking collaborations in reinforcement learning, robotics, and AI. Feel free to reach out! šŸ“«

Featured Publications

Recent research work in reinforcement learning, robotics, and machine learning.

All Publications

(2025). Learning Transferable Sub-goals For Robotic Skills. RSS.
(2024). Learning Transferable Sub-goals by Hypothesizing Generalizing Features. ICLR.
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