Baoru Huang

Baoru Huang

Assistant Professor

University of Liverpool

Biography

I am currently an Assistant Professor in the Department of Computer Science at the University of Liverpool. Prior to this, I worked as a Research Fellow in the Department of Computer Science at University College London, funded by the EU Horizon 2020 program EndoMapper. I completed my PhD at the Hamlyn Centre, Imperial College London. I also had the privilege of working as a Research Scientist at Reality Labs, Meta (Facebook), where I gained invaluable experience and contributed to pioneering projects in Eye Tracking for AR/VR applications.

I earned my BEng degree in Mechanical Engineering with First Class Honours from the University of Birmingham, UK, in 2018, followed by an MRes degree in Medical Robotics and Image-Guided Intervention with Distinction from Imperial College London, UK, in 2019.

Interests
  • Computer vision - 3DV, Scene understanding
  • Robotics - Robot manipulation, Robot vision, Medical Robotics
  • Surgical vision - Foundation model, Image-Guided Intervention
Education
  • PhD in AI, Computer Vision & Medical Robotics, 2023

    Imperial College London

  • MRes in Medical Robotics and Image-guided Intervention (with Distinction), 2019

    Imperial College London

  • BEng in Mechanical Engineering (with Honours Class I), 2018

    University of Birmingham

Experience

 
 
 
 
 
Assistant Professor in the Department of Computer Science
Sep 2024 – Present Liverpool, UK
 
 
 
 
 
Research Fellow at WEISS
May 2023 – Sep 2024 London, UK
 
 
 
 
 
Research Scientist at Reality Labs
Oct 2023 – Feb 2024 Seattle, US
 
 
 
 
 
Research Assistant at Hamlyn Center
Sep 2019 – Mar 2023 London, UK
 
 
 
 
 
Research Assistant at Autonomous Re-manufacturing Lab
Jul 2017 – Sep 2018 Birmingham, UK

Accomplish­ments

Best Paper Award @ International Conference on Robot Intelligence Technology and Applications
Best Poster Award @ European Molecular Imaging Meeting

Recent Publications

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(2024). Guide3D: A Bi-planar X-ray Dataset for 3D Shape Reconstruction. In ACCV 2024.

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(2024). HabiCrowd: A High Performance Simulator for Crowd-Aware Visual Navigation. In IROS 2024.

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(2024). Language-driven Grasp Detection with Mask-guided Attention. In IROS 2024.

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(2024). Lightweight language-driven grasp detection using conditional consistency model. In IROS 2024.

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(2024). Spatial-temporal graph feature learning driven by time–frequency similarity assessment for robust fault diagnosis of rotating machinery. In Advanced Engineering Informatics.

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(2024). Cathsim: an open-source simulator for endovascular intervention. In TMRB.

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(2024). Language-Driven 6-DoF Grasp Detection Using Negative Prompt Guidance. In ECCV 2024.

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(2024). Grasp-anything: Large-scale grasp dataset from foundation models. In ICRA 2024.

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(2024). Language-Conditioned Affordance-Pose Detection in 3D Point Clouds. In ICRA 2024.

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(2024). Open-vocabulary affordance detection using knowledge distillation and text-point correlation. In ICRA 2024.

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(2024). Language-driven Grasp Detection. In CVPR 2024.

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(2024). Residual Aligner-based Network (RAN): Motion-separable structure for coarse-to-fine discontinuous deformable registration. In MedIA.

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(2023). Detecting the Sensing Area of A Laparoscopic Probe in Minimally Invasive Cancer Surgery. In MICCAI 2023 Oral.

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(2022). Self-Supervised Depth Estimation in Laparoscopic Image using 3D Geometric Consistency. In MICCAI 2022.

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(2022). Polarization-based smoke removal method for surgical images. In Biomedical Optics Express.

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(2021). Self-supervised generative adversarial network for depth estimation in laparoscopic images. In MICCAI 2021.

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(2020). Tracking and visualization of the sensing area for a tethered laparoscopic gamma probe. In IJCARS.

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(2019). A self-adaptive motion scaling framework for surgical robot remote control. In RA-L.

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