CV

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General Information

Full Name Dr Shangqi Gao
Affiliation Early Cancer Institute, University of Cambridge
Address CB2 0XZ, Cambridge, UK
Email sg2162@cam.ac.uk
Research Interests Explainable and trustworthy medical AI; generalizable medical image analysis; Bayesian deep learning; multimodal cancer data integration

Academic Experience

  • Mar 2024 - Present
    Research Associate
    University of Cambridge, Cambridge, UK
    • AI for cancer imaging integrating machine learning and multi-omics data
    • Affiliated with the Early Cancer Institute, Department of Oncology
    • Supervisor: Dr Mireia Crispin-Ortuzar
  • Apr 2023 - Feb 2024
    Postdoctoral Research Assistant
    University of Oxford, Oxford, UK
    • Urological cancer pathology AI and uncertainty-aware deep learning
    • Affiliated with the Nuffield Department of Surgical Sciences
    • Supervisors: Prof Clare Verrill and Prof Jens Rittscher

Education

  • Sep 2018 - Jul 2022
    PhD in Statistics
    School of Data Science, Fudan University, Shanghai, China
    • Thesis: Deep Image Decomposition and Reconstruction
    • Advisor: Prof Xiahai Zhuang
  • Sep 2015 - Jul 2018
    MSc in Applied Mathematics
    School of Mathematics and Statistics, Wuhan University, Wuhan, China
    • Thesis: Regularization-Based Approaches for Tensor Completion
    • Advisor: Prof Qibin Fan
  • Sep 2011 - Jul 2015
    BSc in Applied Mathematics
    Department of Mathematics, Northwestern Polytechnical University, Xi'an, China
    • Thesis: Fourier Analysis and Its Applications in Solving Differential and Integral Equations
    • Advisor: Prof Pengcheng Niu

Honors and Awards

  • 2026
    • Best Paper Award Candidate, CVPR
  • 2025
    • Best Paper Award, MICCAI AMAI
  • 2023
    • Shanghai Natural Science Award (2/5), Shanghai Government
    • Elsevier-MedIA First Prize and Medical Image Analysis Best Paper Award, MICCAI
  • 2022
    • Excellent Graduate Award, Shanghai Higher Education Department
    • Best Paper Finalist, MICCAI
  • 2021
    • National Graduate Scholarship (PhD), Fudan University
  • 2017
    • National Graduate Scholarship (MSc), Wuhan University
  • 2014
    • Meritorious Winner of the Mathematical Contest in Modeling, SIAM
  • 2013
    • Honorable Mention in the Mathematical Contest in Modeling, CSIAM
  • 2012
    • National Endeavor Scholarship, Northwestern Polytechnical University

Research Projects

  • 2025 - 2026
    Multi-omics Data Integration for Ovarian Carcinoma
    DAWN Pioneer Project, Cambridge, UK
    • Principal Investigator
    • 10,000 GPU hours (£5,500)
  • 2024 - 2025
    Computational Pathology and Multi-omics Data Integration for Ovarian Carcinoma
    EPSRC Tier-2 HPC, Cambridge, UK
    • Co-lead
    • 40,000 GPU hours (£22,000)
  • 2024 - 2026
    Longitudinal Image and Volumetric Analysis, Visualisation and Measurements
    GE HealthCare-Cambridge, Cambridge, UK
    • Research Associate
  • 2023 - 2024
    Urological Cancer Pathology AI - Beyond Prostate
    Medical Research Council, Oxford, UK
    • Postdoctoral Research Assistant
  • 2020 - 2023
    Methodologies and Applications of Combined Segmentation of Multimodality Cardiac Images Based on Multivariate Mixture Models
    National Natural Science Foundation of China, Shanghai, China
  • 2021 - 2023
    Self-supervised Deep Learning for Multimodal Whole Heart Segmentation of Four-dimensional Cine Images
    NSFC-STINT China-Sweden Joint Research Grant, Shanghai, China
  • 2020 - 2022
    Cardiac Image Segmentation via Deep Learning with Regularization Using Prior Subnetworks
    NSFC-NRF China-Korea Joint Research Grant, Shanghai, China

Teaching and Supervision

  • 2025
    Supervisor, Why Should I Trust You? Explainable AI in Cancer Imaging
    MPhil in Data Intensive Science, Department of Physics, University of Cambridge
  • 2025 - 2026
    Supervisor, Training-free OOD Medical Tumor Segmentation via Anatomical Reasoning and Statistical Rejection
    PhD candidate, School of Computer Science, Carnegie Mellon University
  • 2024 - 2025
    Supervisor, Towards Generalizable Retinal Vessel Segmentation with Deformable Graph Priors
    PhD candidate, School of Computer Science, Zhejiang University
  • 2024 - 2025
    Co-supervisor, Multi-modal MRI Translation via Evidential Regression and Distribution Calibration
    PhD candidate, TSTBI, Fudan University
  • Aug 2024
    Guest Lecturer, Image Processing and Analysis
    Summer Programme, Homerton College, University of Cambridge
  • 2023 - 2024
    Co-supervisor, InDeed - Interpretable Image Deep Decomposition with Guaranteed Generalizability
    PhD candidate, School of Data Science, Fudan University
  • 2020 - 2021
    Guest Lecturer, DATA630015 Medical Image Analysis
    School of Data Science, Fudan University
  • 2019 - 2020
    Teaching Assistant, DATA130012.01 Data Visualization
    School of Data Science, Fudan University
  • 2018 - 2019
    Teaching Assistant, Sparsity in Statistics
    School of Data Science, Fudan University

Presentations and Talks

  • Jul 2026
    Invited talk: Explainable Integration of Radiology and Pathology for Pan-Cancer Analysis
    Early Cancer Institute, University of Cambridge
  • Apr 2026
    Invited talk: Probabilistic Modelling and Bayesian Deep Learning in Multimodal Data Integration
    Hawkes Institute, University College London
  • Dec 2025
    Oral: Towards Generalizable Retinal Vessel Segmentation with Deformable Graph Priors
    NeurIPS@Cam Early Career Researcher Conference, University of Cambridge
  • Nov 2025
    Poster: Can Foundation Segmentation Models Generalize to Breast Cancer?
    ESMO AI and Digital Oncology, Berlin, Germany
  • Oct 2025
    Invited talk: Explainable Integration of Kidney Cancer Radiology and Pathology
    Jeffrey Cheah Biomedical Centre, University of Cambridge
  • Sep 2025
    Poster: Probabilistic Integration of Renal Cancer Radiology and Pathology Using Graph Neural Networks
    MICCAI, Daejeon, South Korea
  • Sep 2025
    Oral: Evaluating Foundation Models with Pathological Concept Learning for Kidney Cancer
    MICCAI AMAI, Daejeon, South Korea
  • Jun 2024
    Oral: Bayesian Modeling for Medical Image Segmentation with Interpretable Generalizability
    Robust Cancer Early Detection Systems under Distribution Shifts and Uncertainty Workshop, University of Cambridge
  • Apr 2023
    Invited talk: Bayesian Modeling for Medical Image Segmentation with Interpretable Generalizability
    First Youth Academic Forum on Intelligent Imaging, Chinese Society of Stereology
  • Sep 2022
    Poster: Joint Modelling of Image and Label Statistics for Enhancing Model Generalizability of Medical Image Segmentation
    MICCAI, Singapore
  • Jun 2022
    Invited talk: Bayesian Deep Learning - Applications in Natural Image Super-Resolution and Medical Image Segmentation
    1075th Academic Seminar on Biomedical and Health Engineering, Shenzhen
  • Jun 2021
    Seminar: Rank-One Network - An Efficient Framework for Image Restoration
    Applied Mathematics PhD Seminar, School of Mathematics, Fudan University

Selected Publications

  • 2026
    R2Seg: Training-free OOD Medical Tumor Segmentation via Anatomical Reasoning and Statistical Rejection
    CVPR (Oral; Best Paper Award Candidate)
    • S Shen, K Liu, J Xie, S Gao, C Shen, G Liu, M Crispin-Ortuzar, and S Gao
  • 2025
    Towards Generalizable Retinal Vessel Segmentation with Deformable Graph Priors
    NeurIPS
    • K Liu, S Gao, Y Fu, and S Gao
  • 2023
    BayeSeg: Bayesian Modeling for Medical Image Segmentation with Interpretable Generalizability
    Medical Image Analysis, 89(7), 102889
    • S Gao, H Zhou, Y Gao, and X Zhuang
    • Elsevier-MedIA First Prize and MICCAI Medical Image Analysis Best Paper Award
  • 2023
    Bayesian Image Super-Resolution with Deep Modelling of Image Statistics
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(2), 1405-1423
    • S Gao and X Zhuang
  • 2022
    Rank-One Network: An Effective Framework for Image Restoration
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(6), 3224-3238
    • S Gao and X Zhuang

Academic Service

  • Leadership and Organization
    • President, MICCAI Special Interest Group on Explainable AI for Medical Image Analysis, May 2024 - Present
    • Program Chair, Workshop on Interpretability of Machine Learning in Medical Image Computing, MICCAI 2025, Daejeon, South Korea
    • Co-organizer, Challenge on Comprehensive Analysis and Computing of Real-world Medical Images, MICCAI 2025, Daejeon, South Korea
    • Organizer, Online Seminar on Explainable AI for Medical Image Analysis, June 2025
    • Co-organizer, Challenge on Comprehensive Analysis and Computing of Real-world Medical Images, MICCAI 2024, Marrakesh, Morocco
    • Co-organizer, First Workshop on Multimodal Imaging and Explainable Artificial Intelligence Analysis and International Symposium on Sino-Swedish Medical Image Analysis, Xiamen, China, July 2024
  • Peer Review
    • IEEE Transactions on Pattern Analysis and Machine Intelligence
    • Cancer Discovery
    • Nature Communications
    • IEEE Transactions on Image Processing
    • Medical Image Analysis
    • IEEE Transactions on Medical Imaging
    • IEEE Transactions on Neural Networks and Learning Systems
    • Neural Networks
    • Neurocomputing
    • NeurIPS, CVPR, ICCV, ECCV, ACM Multimedia, and MICCAI