Lihao Liu

Applied Scientist

Amazon, USA



Biography  

I am an Applied Scientist at Amazon, USA. I obtain my Ph.D. degree from University of Cambridge under the supervision of Carola-Bibiane Schönlieb and Angelica I. Aviles-Rivero, and Pietro Liò. Before that, I received my M.Phil. degree from Dept. of Computer Science and Engineering (CSE), Chinese University of Hong Kong, under the supervision of Prof. Pheng-Ann Heng, and my B.Eng. degree from Dept. of Software Engineering, Chongqing University. My research interests include LLM-based Agent and AI for Healthcare.

News

  • [02/2025] Two papers are accepted at CVPR'2025.
  • [08/2024] One paper is accepted at ACM MM'2024.
  • [05/2024] I’ve officially submitted my Ph.D. thesis and am now a Doctor! I’ll be joining Amazon USA next month!
  • [11/2023] Two paper are accepted at Medical Image Analysis (MIA)!
  • [02/2023] Our paper on video shadow detection is accepted at CVPR'2023!
  • [02/2023] Our paper on surgical video recognition is accepted at ICLR-TML4H’23.
  • [06/2022] Our challenge method paper is accepted on MIUA'2022, and win the Merit NVIDIA Paper Award.
  • [05/2022] Two papers are accepted on WBIR'2022.
  • [03/2022] We win the 4th place on the grand challenge CoNIC'2022.
  • [03/2021] I will join Microsoft Research Cambridge as an intern to work on self-supervised cross-modality problems.
  • [06/2020] I pass my M.Phil. thesis oral defense, and will join Cambridge Image Analysis group as a Ph.D. student!
  • [01/2020] Our paper on supervised 3d brain segmentation is accepted at IEEE Transactions on Medical Imaging (TMI).
  • [07/2019] Our extended paper on lung nodule analysis is accepted at IEEE Transactions on Medical Imaging (TMI).
  • [06/2019] Our paper on unsupervised 3d brain image registration is early accepted at MICCAI'2019!
  • [08/2018] Our paper on lung nodule analysis is accepted at MICCAI-DLMIA'2018.

Publications

                                                   
TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios

Lihao Liu, Yanqi Cheng, Zhongying Deng, Shujun Wang, Dongdong Chen, Xiaowei Hu, Pietro Liò, Carola-Bibiane Schönlieb, and Angelica I Aviles-Rivero.
Arxiv Tech Report, 2023.

[paper]

Traffic Video Object Detection using Motion Prior

Lihao Liu, Yanqi Cheng, Dongdong Chen, Jing He, Pietro Liò, Carola-Bibiane Schönlieb, and Angelica I Aviles-Rivero.
Arxiv Tech Report, 2023.

[paper]

SCOTCH and SODA: A Transformer Video Shadow Detection Framework

Lihao Liu, Jean Prost, Lei Zhu, Nicolas Papadakis, Pietro Liò, Carola-Bibiane Schönlieb, and Angelica I Aviles-Rivero.
Computer Vision and Pattern Recognition (CVPR), 2023.

[paper] [project]

Why Deep Surgical Models Fail?: Revisiting Surgical Action Triplet Recognition through the Lens of Robustness

Yanqi Cheng, Lihao Liu, Shujun Wang, Yueming Jin, Carola-Bibiane Schönlieb, Angelica I. Aviles-Rivero.
Trustworthy Machine Learning for Healthcare (ICLR-TML4H), 2023.

[paper] [project]

TrafficCAM: A Versatile Dataset for Traffic Flow Segmentation

Zhongying Deng, Yanqi Chen, Lihao Liu, Shujun Wang, Rihuan Ke, Carola-Bibiane Schonlieb, and Angelica I Aviles-Rivero.
Arxiv Tech Report, 2022.

[paper] [project]

PC-SwinMorph: Patch Representation for Unsupervised Medical Image Registration and Segmentation

Lihao Liu, Zhening Huang, Pietro Liò, Carola-Bibiane Schönlieb, and Angelica I Aviles-Rivero.
Major Revision at Medical Image Analysis. (MIA), 2023.

[paper]

You Only Look at Patches: A Patch-wise Framework for 3D Unsupervised Medical Image Registration

Lihao Liu, Zhening Huang, Pietro Liò, Carola-Bibiane Schönlieb, and Angelica I Aviles-Rivero.
Biomedical Image Registration (WBIR), 2022.

[paper]

MammoDG: Generalisable Deep Learning for Cross-Domain Multi-Center Breast Cancer Screening

Yijun Yang, Shujun Wang, Lihao Liu, Sarah Hickman, Fiona J Gilbert, Carola-Bibiane Schönlieb, Angelica I. Aviles-Rivero.
Arxiv Tech Report, 2023.

[paper]

CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

Simon Graham, Quoc Dang Vu, ..., Lihao Liu, Chengyang Hong, and et. al.
Medical Image Analysis (MIA), 2023.

[paper] [code] [project]

Simultaneous Semantic and Instance Segmentation for Colon Nuclei Identification and Counting

Lihao Liu, Chengyang Hong, Angelica I Aviles-Rivero, and Carola-Bibiane Schönlieb.
Medical Image Understanding and Analysis (MIUA), 2022.

[paper] [code] [algorithm]

[Merit NVIDIA Paper Award!] [Ranking 4/373 in the CoNIC-2022!]

Learning Homeomorphic Image Registration via Conformal-Invariant Hyperelastic Regularisation

Jing Zou, Noémie Debroux, Lihao Liu, Jing Qin, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero.
Medical Image Analysis (MIA), 2023.

[paper]

Deformable Lung CT Registration by Decomposing Large Deformation

Jing Zou, Lihao Liu, Youyi Song, Kup-Sze Choi, Jing Qin.
Biomedical Image Registration (WBIR), 2022.

[paper]

Contrastive Registration for Unsupervised Medical Image Segmentation

Lihao Liu, Angelica I Aviles-Rivero, Carola-Bibiane Schönlieb.
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.

[paper] [code]

Ψ-Net: Stacking Densely Convolutional LSTMs for Sub-cortical Brain Structure Segmentation

Lihao Liu, Xiaowei Hu, Lei Zhu, Chi-Wing Fu, Jing Qin, and Pheng-Ann Heng.
IEEE Transactions on Medical Imaging (TMI), 2020.

[paper] [code]

Probabilistic Multilayer Regularization Network for Unsupervised 3D Brain Image Registration

Lihao Liu, Xiaowei Hu, Lei Zhu, and Pheng-Ann Heng.
Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019.

[paper] [code]

Multi-Task Deep Model with Margin Ranking Loss for Lung Nodule Analysis

Lihao Liu, Qi Dou, Hao Chen, Jing Qin, and Pheng-Ann Heng.
IEEE Transactions on Medical Imaging (TMI), 2019.

[paper] [code]

MTMR-Net: Multi-Task Deep Learning with Margin Ranking Loss for Lung Nodule Analysis

Lihao Liu, Qi Dou, Hao Chen, Iyiola E. Olatunji, Jing Qin, and Pheng-Ann Heng.
Deep Learning in Medical Image Analysis (MICCAI-DLMIA), 2018.

[paper] [code]

Experience

  • University of California, Los Angeles, USA
    Aug. 2023 – Jul. 2024

    Visiting Scholar at Stan's Group
    - I work with Prof. Stan on joint diffusion model and medical image registration.
  • Microsoft Research, Cambridge, UK
    Jun. 2021 – Aug. 2021

    Research Intern at Healthcare Intelligence Group
    - I work with Ozan Oktay on joint multi-modality self-supervised learning for chest radiology applications.
  • University of Cambridge, UK
    Feb. 2020 – Jul. 2020

    Visiting Student at Cambridge Image Anaylsis Group (CIA)
    - Designed a registration-based unsupervised segmentation architecture for brain images.
  • Imsight Technology, Shenzhen, China
    Aug. 2017 – Oct. 2017

    Research Intern at AI for Imaging Group
    - Deployed the AI-based lung nodule analysis software to multiple hospitals in Beijing for clinical usage.
  • Chinese University of Hong Kong, Hong Kong
    Feb. 2017 – Jul. 2017

    Junior Research Assistant at Medical Imaging Lab (CUMed)
    - Developed a DeepLung software which integrated the deep learning based lung nodule analysis algorithms into ITK-SNAP.
  • Weiboyi Technology Co., Ltd, Beijing, China
    May. 2016 – Feb. 2017

    Data Mining Engineer at Big Data Group
    - Developed a hive-based auto-update system for big files storing and updating.

Honors & Awards

  • Cody Award, University of Cambridge, 2023

  • BMVC Doctoral Consortium with Travel Award, Aberdeen, 2023

  • University Travel Award, University of Cambridge, 2023

  • Oracle Ph.D. Project Award, Oracle, 2023

  • ICIAM FS1 Award, Tokyo, 2023

  • Rouse Ball Award, University of Cambridge, 2023

  • NoMADS Travel Award for UCLA Visting Graduate Researcher, NoMADS, 2023

  • Merit NVIDIA Paper Award, MIUA, 2022

  • Smith-Knight and Rayleigh-Knight Essay Prizes, University of Cambridge, 2022

  • Ranking 4/373 in the Grand Challenge CoNIC, 2022

  • GSK Ph.D. Fellowship, GlaxoSmithKline (GSK), 2020

  • Girton College - Graduate Research Scholarship, University of Cambridge, 2020

  • CUHK M.Phil. Student Scholarship, Chinese University of Hong Kong, 2017

  • Outstanding Student Award, Chongqing University, 2016

  • Qiu Shi Scholarship, Chongqing University, 2014

Professional Activities

  • Invited Talks:
    - SIAM Conference on Imaging Science, “Contrastive Registration for Unsupervised Image Segmentation”, March 2022.
    - Chongqing University, “How Registration can Help to Segment Medical Images without Ground Truths?”, November 2021.
    - Microsoft Research, “Multi-modal Contrastive Representation Learning for Chest X-ray Diagnosis.”, August 2021.
    - East China Normal University, "Deep Learning Application in Medical Image Anaylsis", November 2020.

  • Memberships:
    MICCAI Student, IEEE Student

  • Paper Reviews:
    MICCAI, TMI, MIA, CVPR, ICCV, ECCV, and IJCV

  • Supervision for Master Students:
    - Zhening Huang (master student in Cambridge, now Ph.D. in Cambridge.)
    - Jing Zou (master student in CUHK, now Ph.D. in PolyU.)
    - Yanqi Chen (master student in Cambridge, now Ph.D. in Cambridge.)

  • Teaching Assistant:
    - 2019-2020SpringCSCI2100 Data Structures
    - 2018-2019FallCSCI3160 Design and Analysis of Algorithms
    - 2017-2018FallCSCI3160 Design and Analysis of Algorithms

  • Volunteer Experience:
    - I am an in-person volunteer in GeoMedIA'22 workshop, and ICCV'23.
    - I am the webpage manager and event in-person volunteer in MIUA'22 conference and Women in MIUA workshop.