Hongyu Li (李鸿宇)

Welcome! I’m a first-year Ph.D. student in Computer Science at Brown University. I work with Prof. Srinath Sridhar at Interactive 3D Vision & Learning Lab.

I completed my Master’s degree at Northeastern University, where I conducted research on topics related to robot perception and navigation with the guidance of Prof. Huaizu Jiang and Prof. Taskin Padir.

I had the opportunity to intern at Honda Research Institute (HRI). Throughout my two internships at HRI, my research primarily focused on visuotactile manipulation perception. I had the privilege of being supervised by Dr. Nawid Jamali and Dr. Soshi Iba.

My research interests revolve around the convergence of computer vision, machine learning, and robotics, particularly in the field of robot perception and planning. Perception and planning play a crucial role in various robotics domains, and I am currently focused on developing deep learning models for environment and object interaction.

I hold a Bachelor’s degree in Computer Science and Economics (dual major) from Rensselaer Polytechnic Institute.


Jan 20, 2024 Our work E(2)-Equivariant Graph Planning for Navigation is accepted to RA-L. See you in Abu Dhabi :camel: (IROS 2024)!
Aug 25, 2023 Our work ViHOPE is accepted to RA-L. See you in Yokohama :jp: (ICRA 2024)!
May 15, 2023 I receive a $1,300 RAS travel grant for ICRA 2023.
Apr 17, 2023 I will present our work in progress, StereoNavNet: Learning to Navigate using Stereo Camera with Auxiliary Occupancy Voxels, at CVPR 2023 3D Vision and Robotics in Vancouver :canada:.
Apr 14, 2023 I completed my M.S thesis defense on “Toward Efficient Stereo-based Obstacle Detection Using Deep Neural Network”.

Selected Publications

Symbol * or † represents equal contribution or advising.


  1. RA-L
    E(2)-Equivariant Graph Planning for Navigation
    IEEE Robotics and Automation Letters, 2024
    To be presented at IROS 2024 in Abu Dhabi, UAE :camel:.
    We study E(2) Euclidean equivariance in navigation on geometric graphs and develop message passing network to solve it.


  1. RA-L
    ViHOPE: Visuotactile In-Hand Object 6D Pose Estimation with Shape Completion
    Hongyu LiSnehal DikhaleSoshi Iba, and Nawid Jamali
    IEEE Robotics and Automation Letters, 2023
    To be presented at ICRA 2024 in Yokohama, Japan :jp:.
    Presented at NeurIPS 2023 Workshop on Touch Processing in New Orleans, LA :us:.
  2. ICRA
    StereoVoxelNet: Real-Time Obstacle Detection Based on Occupancy Voxels from a Stereo Camera Using Deep Neural Networks
    In IEEE International Conference on Robotics and Automation (ICRA), 2023
    Presented at IROS 2022 Agile Robotics Workshop in Kyoto, Japan :jp:.


  1. IROS
    Deep Reinforcement Learning based Robot Navigation in Dynamic Environments using Occupancy Values of Motion Primitives
    Neset Unver AkmandorHongyu LiGary Lvov, Eric Dusel, and Taskin Padir
    In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022