Mission

The AYL (A Yang Lab) at Imperial College London, led by Dr. Guang Yang, focuses on developing artificial intelligence (AI)-powered applications for biomedicine, including Smart Imaging, Big Data Analysis, and AI in Drug Discovery. AYL is situated at Imperial College White City Campus. Our Values can be found here.

News

"Our major obligation is not to mistake slogans for solutions." — Edward R. Murrow









AYangLab Introduction

Please join us for your next adventures!

26th UK Conference on Medical Image Understanding and Analysis

Please join us for MIUA’22 @Cambridge

Showcases

"The true sign of intelligence is not knowledge but imagination.” — Albert Einstein

 Latest Research Posters

 Book Chapters

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Amelioration of Alzheimer’s Disease Pathology by Mitophagy Inducers Identified via Machine Learning and a Cross-Species Workflow

Machine Learning Identifies Mitophagy Inducers

Scientists (Dr Guang Yang and Zhangming Niu) at Imperial College London, UK and MindRank AI in Hangzhou, China, used predictive algorithms informed by machine learning to identify molecules capable of promoting the degradation of damaged mitochondria, a process known as mitophagy. Their virtual screen yielded a list of 18 compounds. Working with gerontologist Prof Evandro Fang at the University of Oslo and pharmacologist Prof Jia-Hong Lu at the University of Macau, the group then used human cells, worms and mice to winnow this list down to two drug candidates, both of which target a protein called PINK1 — an important mediator of mitochondrial quality control. Late last year, the researchers showed how the drugs helped to improve memory in worm and mouse models of Alzheimer’s disease.

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RBHT_Showcase_Poster_GY_2019

Deep Learning for Detection of Myocardial Scar Tissue

Goodbye to Gadolinium?

"This study is another important step toward gadolinium-based contrast agent–free cardiac imaging and complements other native techniques such as T1- and T1-rho mapping, feature tracking, and the recently described, highly interesting approach by Baessler et al who studied the ability of texture analysis or radiomics to detect the presence and extent of left ventricle myocardial scar tissue from a single end-diastolic cine imaging frame. It is likely that a combination of both methods—deep learning analysis of cardiac motion as described in the present study as well as analysis of subtle differences in left ventricle myocardial texture—can lead to even better results on a patient level. The authors are also to be commended for making their source code freely available for other investigators.” — by Prof. Tim Leiner

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Research Keywords

Learning is the key ...

I am always looking for collaborators, good students and brilliant ideas!

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Team

"Coming together is a beginning, staying together is progress, and working together is a success." — Henry Ford

Guang Yang

Guang Yang 🇨🇳

⏣ Ph.D, MS.c,
IEEE Senior Member,
SPIE Lif Member,
BMVC & MICCAI Member

⎈ Head of the AYL

⎈ Associate Professor (Senior Lecturer), Bioengineering Department & Imperial-X, Imperial College London

⎈ UKRI Future Leaders Fellow

⎈ Honorary Senior Lecturer,
School of Biomedical Engineering & Imaging Sciences,
King's College London

⎈ Editorial Board Member or Associate Editor of:
npj Digital Medicine;
Medical Image Analysis;
IEEE Transactions on Medical Imaging;
IEEE Transactions on Big Data;
IEEE Transactions on Emerging Topics in Computational Intelligence;
International Journal of Imaging Systems and Technology;
Computerized Medical Imaging and Graphics;
BMC Medical Informatics and Decision Making
Computers in Biology and Medicine;
IEEE Transactions on Cybernetics;
BMC Medical Imaging (Retired);
IET Image Processing;
Neurocomputing.


Fast MRI
Deep Learning
Machine Learning
Federated Learning
Pattern Recognition
Medical Image Analysis
Explainable and Trustworthy AI

 Current Members

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Yingying Fang 🇨🇳 ♀︎

⎈ Postdoc Research Associate,
National Heart and Lung Institute, Imperial College London

 2021-now


Inverse Problems
Multifactorial Analysis
Diagnostic and Prognostic Models 

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Federico Felder 🇦🇷 ⚦

⎈ Clinical Fellow,
National Heart and Lung Institute, Imperial College London

 2021-now


Lung Fibrosis
COVID-19
Radiology

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Sheng Zhang 🇨🇳 ⚦

⎈ Postdoc Research Associate,
National Heart and Lung Institute, Imperial College London

 2022-now


Segmentation
Explainable AI
Diagnostic and Prognostic Models

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Jun-Jie Hu 🇨🇳 ⚦

⎈ Postdoc Research Associate,
National Heart and Lung Institute, Imperial College London

 2023-now


Federated Learning
Quantum Computing
Multifactorial Analysis

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Yang Nan 🇨🇳 ⚦

⎈ PhD Student,
Bioengineering Department, Imperial College London

⎈ Research Associate,
Bioengineering Department, Imperial College London

 2021-now


Data Harmonisation
Unsupervised Segmentation

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Ming Li 🇨🇳 ⚦

⎈ PhD Student,
Bioengineering Department, Imperial College London

⎈ Research Assistant,
Bioengineering Department, Imperial College London

 2021-now


Federated Learning
Explainable and Trustyworthy AI

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Xiaodan Xing 🇨🇳 ♀︎

⎈ PhD Student,
Bioengineering Department, Imperial College London

⎈ Research Associate,
Bioengineering Department, Imperial College London

 2021-now


Data Synthesis
Privacy-preserved Learning

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Jiahao Huang 🇨🇳 ⚦

⎈ PhD Student,
Bioengineering Department, Imperial College London

⎈ Research Assistant,
Bioengineering Department, Imperial College London

 2021-now


Fast MRI
MRI Reconstruction
Generative Adversarial Networks

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Yinzhe Wu 🇨🇳 ⚦

⎈ PhD Student,
Bioengineering Department, Imperial College London

Imperial President’s Scholarship Winner

 2022-now


DT-CMR
Tractography
Super-resolution

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Fanwen Wang 🇨🇳 ♀︎

⎈ PhD Student,
Bioengineering Department, Imperial College London

⎈ Research Assistant,
Bioengineering Department, Imperial College London

 2022-now


Radiomics
Registration

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Zhangming Niu 🇸🇪 ⚦

⎈ PhD Student,
National Heart and Lung Institute, Imperial College London

 2022-now (Part-time)


Prognositic Models
AI in Drug Discovery

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Michael Tanzer 🇮🇹 ⚦

⎈ PhD Student,
AI4Health CDT,
Computing Department, Imperial College London

 2020-now


Fast MRI
MRI Reconstruction
Diffusion Tensor Cardiac MRI

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Ke Wen 🇨🇳 ♀︎

⎈ PhD Student,
KCL-Imperial College Smart Medical Imaging CDT,
National Heart and Lung Institute, Imperial College London

 2021-now


MRI Reconstruction
Sequence Programming

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Yaqing Luo 🇨🇳 ♀︎

⎈ PhD Student,
KCL-Imperial College Smart Medical Imaging CDT,
National Heart and Lung Institute, Imperial College London

 2021-now


MRI Reconstruction
Spiral Diffusion Tensor Cardiac MRI

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Kamrul Hasan 🇧🇩 ⚦

⎈ PhD Student,
Bioengineering Department, Imperial College London

 2022-now


PINN
Segmentation
Fetal Heart Data Analysis

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Shiyi Wang 🇨🇳 ♀︎

⎈ PhD Student,
National Heart and Lung Institute, Imperial College London

 2022-now


Active Learning
Explainable and Trustyworthy AI
Airway and Vessel Segmentation

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Roberto Sesia 🇬🇧 ⚦

⎈ PhD Student,
National Heart and Lung Institute, Imperial College London

 2022-now


Diagnostic Models 
Inforamtion Fusion

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Yihao Luo 🇨🇳 ⚦

⎈ PhD Student,
Bioengineering Department, Imperial College London

 2023-now


Graphics
Biomechanical Modelling

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Liutao Yang 🇨🇳 ⚦

⎈ Visiting PhD Student,
National Heart and Lung Institute, Imperial College London

 2023-now


Low Dose CT Reconstruction

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Caiwen Jiang 🇨🇳 ⚦

⎈ Visiting PhD Student,
Department of Bioengineering, Imperial College London

 2023-now


Federated Learning

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Zi Wang 🇨🇳 ⚦

⎈ Visiting PhD Student,
Department of Bioengineering, Imperial College London

 2024-now


Quantitative MRI

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Zihao Jin 🇨🇳 ⚦

⎈ MRes Student,
Department of Metabolism, Digestion and Reproduction,
Imperial College London
 
2023-2024


Prognostic Models

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Yijian Gao 🇨🇳 ⚦

⎈ MRes Student,
Department of Computing,
Imperial College London
 
2023-2024


Clinical Report Synthesis

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Junzhi Ning 🇨🇳 ⚦

⎈ MRes Student,
Department of Computing,
Imperial College London
 
2023-2024


Super-resolution

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Gavin (Zhiling) Yue 🇨🇳 ♀︎

⎈ MRes Student,
Department of Surgery and Cancer,
Imperial College London
 
2023-2024


Explainable AI Models

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Jey Tse Loh 🇲🇾 ♀︎

⎈ MEng Student,
Department of Bioengineering,
Imperial College London
 
2023-2024


Synthetic Models

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Ryan K L Ang  🇸🇬 ⚦

⎈ MEng Student,
Department of Bioengineering,
Imperial College London
 
2023-2024


Quantum Computing

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Kamrul Eshak 🇬🇧 ⚦

⎈ MEng Student,
Department of Bioengineering,
Imperial College London
 
2023-2024


Segmentation

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Siofra Murdoch 🇮🇪 ♀︎

⎈ MSc Student,
Department of Bioengineering,
Imperial College London
 
2023-2024


Synthetic Models

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Qian Tong Lim 🇲🇾 ♀︎

⎈ MSc Student,
Department of Bioengineering,
Imperial College London
 
2023-2024


Super-resolution

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Zifan Zeng 🇨🇳 ♀︎

⎈ MSc Student,
Department of Bioengineering,
Imperial College London
 
2023-2024


Super-resolution

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Haotian Qi 🇨🇳 ⚦

⎈ UROP Student,
Department of Computing,
Imperial College London
 
2023-now


Myocardium Infarction Segmentation

 Alumni

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Lichao Wang 🇨🇳 ⚦

⎈ MRes Student,
Department of Computing,
Imperial College London
 
2022-2023


Myocardium Infarction Segmentation

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Caiwen Xu 🇨🇳 ♀︎

⎈ MRes Student,
Department of Computing,
Imperial College London
 
2022-2023


COVID CT Segmentation

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Danting Zhang 🇨🇳 ♀︎

⎈ MRes Student,
Department of Computing,
Imperial College London
 
2022-now


Histology Data Analysis

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Michael Yeung 🇬🇧 ⚦

⎈ MRes Student,
Department of Computing,
Imperial College London
 
2022-2023


Instance Segmentation

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Zeyu Tang 🇨🇳 ⚦

⎈ UROP/MEng Student,
Bioengineering Department &
National Heart and Lung Institute, Imperial College London

 2021-2023


Vecocity Mapping MRI
Cardiac MRI Segmentation

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April Wu 🇨🇳 ♀︎

⎈ UROP/MEng Student,
Bioengineering Department &
National Heart and Lung Institute, Imperial College London

 2021-2023


Vecocity Mapping MRI
Cardiac MRI Segmentation

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Hao Li 🇬🇧 ⚦

⎈ UROP Student,
Bioengineering Department &
National Heart and Lung Institute, Imperial College London

 2021-2023


Vecocity Mapping MRI
Cardiac MRI Segmentation

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Weixun Luo 🇬🇧 ⚦

⎈ UROP Student,
Bioengineering Department &
National Heart and Lung Institute, Imperial College London

 2021-2023


Vecocity Mapping MRI
Cardiac MRI Segmentation

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Mehak Gurnani 🇬🇧 ♀︎

⎈ UROP
Medical Biosciences,
Imperial College London

 2022-2023


Airway Segmentation

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Xiandong Zou 🇨🇳 ⚦

⎈ UROP Student,
Mathematics Department,
Imperial College London

 2022-2023


Fuzzy Learning

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Jacob Nicholas Ross Walker 🇨🇭 ⚦

⎈ MSc Student,
Department of Bioengineering,
Imperial College London
 
2022-2023


Synthetic Models

Avatar_ML

Yinzhe Wu 🇨🇳 ⚦

⎈ MEng/UROP Student,
Bioengineering Department &
National Heart and Lung Institute, Imperial College London

 2019-2022


Vecocity Mapping MRI
Cardiac MRI Segmentation

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Yutong Chen 🇨🇳 ⚦

⎈ UROP Student,
Faculty of Biology,
Cambridge University

 2019-2022


Fast MRI
MRI Reconstruction

JH_MRes

Jonathan Hewlett 
🇬🇧 ⚦

⎈ MRes Student,
Department of Computing,
Imperial College London
 
2021-2022


GAN Based Fast DT-CMR

CO

Chibudom Onuorah 🇬🇧 ♀︎

⎈ MRes Student,
Department of Computing,
Imperial College London
 
2021-2022


Long/Short-term COVID Prognosis

JH_MRes

Yifan Yuan 🇨🇳 ⚦

⎈ MRes Student,
Department of Physics,
Imperial College London
 
2021-2022


Whole Heart Segmentation

JH_MRes

Baiyu Su 🇨🇳 ⚦

⎈ UROP Student,
Cambridge University
 
2021-2022


Airway Segmentation

JH_MRes

Selena Linden 🇬🇧 ♀︎

⎈ UROP Student,
Mathematics Department,
Imperial College London
 
2021-2022


Multi-organ Segmentation

JH_MRes

Jonathan Rubin 🇬🇧 ⚦

⎈ UROP Student,
Mathematics Department,
Imperial College London
 
2021-2022


Multi-organ Segmentation

JH_MRes

Michael Yeung 🇬🇧 ⚦

⎈ UROP Student,
Department of Radiology,
Cambridge University

 2021-2022


Biomedical Image Segmentation

Teaching

"Teaching is the greatest act of optimism." — Colleen Wilcox

BIOE70074 - MSc Journal Club 2023-2024

BIOE70074 MSc Journal Club Computational stream

https://www.imperial.ac.uk/study/courses/postgraduate-taught/biomedical-engineering-computational/

This is the cohort module, in which we will read exciting papers in the fields of computational bioengineering together.

We will meet on Mondays 12-1pm, in RSM303 seminar room, in person.

Module leader:
Dr Guang Yang (g.yang@imperial.ac.uk)

Module GTA:
Miss Xiaodan Xing (x.xing@imperial.ac.uk)

BIOE60008/70036 - Image Processing (Spring 2023-2024)

One of the challenges of a course on image processing is the very high rate at which the field is evolving. Another is to provide educational content in such a way that students who have come either from engineering or biological sciences can find a way to make connections with ideas they have met before, or to concepts which they will meet elsewhere in one of the many streams of the Bioengineering department.

Lecturers:
Prof Anil A Bharath
Dr Guang Yang

RSM- 228 - Bagrit Lecture Theatre

BIOE70074 - MSc Journal Club 2023-2024

BIOE70074 MSc Journal Club Computational stream

https://www.imperial.ac.uk/study/courses/postgraduate-taught/biomedical-engineering-computational/

This is the cohort module, in which we will read exciting papers in the fields of computational bioengineering together.

We will meet on Mondays 12-1pm, in RSM303 seminar room, in person.

Module leader:
Dr Guang Yang (g.yang@imperial.ac.uk)

Module GTA:
Miss Xiaodan Xing (x.xing@imperial.ac.uk)

BIOE60008/70036 - Image Processing (Spring 2023-2024)

One of the challenges of a course on image processing is the very high rate at which the field is evolving. Another is to provide educational content in such a way that students who have come either from engineering or biological sciences can find a way to make connections with ideas they have met before, or to concepts which they will meet elsewhere in one of the many streams of the Bioengineering department.

Lecturers:
Prof Anil A Bharath
Dr Guang Yang

RSM- 228 - Bagrit Lecture Theatre

BIOE70074 - MSc Journal Club 2023-2024

BIOE70074 MSc Journal Club Computational stream

https://www.imperial.ac.uk/study/courses/postgraduate-taught/biomedical-engineering-computational/

This is the cohort module, in which we will read exciting papers in the fields of computational bioengineering together.

We will meet on Mondays 12-1pm, in RSM303 seminar room, in person.

Module leader:
Dr Guang Yang (g.yang@imperial.ac.uk)

Module GTA:
Miss Xiaodan Xing (x.xing@imperial.ac.uk)

BIOE60008/70036 - Image Processing (Spring 2023-2024)

One of the challenges of a course on image processing is the very high rate at which the field is evolving. Another is to provide educational content in such a way that students who have come either from engineering or biological sciences can find a way to make connections with ideas they have met before, or to concepts which they will meet elsewhere in one of the many streams of the Bioengineering department.

Lecturers:
Prof Anil A Bharath
Dr Guang Yang

RSM- 228 - Bagrit Lecture Theatre

Collaborators

We are standing on the shoulders of giants

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Radiomics
MC2
QUIBIM
Thirona
CDISC
GE
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Call for Collaborations

We are always looking for collaborators to work together on UKRI Networking grant, ERC Horizon Europe grant,
National Natural Science Foundation of China international programme grant and other collaborative grant proposals. 

Projects

"If you don't know where you are going. How can you expect to get there?" — Basil S. Walsh

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  • ERC H2020 Funded Project
    H2020-SC1-FA-DTS-2019-1 952172

  • Cancer Imaging

  • Artificial Intelligence

  • Decentralised Data Lake

    Total Awards: €8,784,038.75

    Awards to Imperial College London (fEC): £567,126.73

    2020-2025 (Extended)

    PI: Dr. Guang Yang

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  • UKRI Funded Future Leaders Fellowship
    MR/V023799/1

  • Smart Imaging

  • Super-Resolution

  • Multimodal Data Analysis

    Cardiac MRI

    Total Awards (fEC): £1,707,214.21

    2021-2025

    PI: Dr. Guang Yang

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  • IMI Funded Project
    H2020-JTI-IMI2
    101005122

  • COVID-19 Research

  • Data Harmonisation

  • Federated Learning

    Total Awards: €11,381,970.00

    Awards to Imperial College London (fEC): £1,156,258.91

    2020-2024 (Extended)

    PI: Dr. Guang Yang

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  • Wellcome Leap Dynamic Resilience

  • Delirium

  • Big Data

  • Cohort Analysis

    Multimodal Data Analysis

    Total Awards: $5,358,752

    Awards to Imperial College London (fEC): £1,393,897.34

    2023-2026

    Co-PI: Dr. Guang Yang

IC_BRC



Imperial College Healthcare NHS Trust- BRC Funding

AI-Based Prognosis Models For Progressive Lung Fibrosis Using Multimodal Data

Total Awards (fEC): £108,769.27

2022

Co-PI: Dr. Guang Yang




More Info
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The Royal Society

4D-CINENet: Attentive Generative Adversarial Network Based Fast 4D Whole Heart CINE MRI

Total Awards (fEC): £44,909.20

2022-2025 (Extended)

Sole PI: Dr. Guang Yang

More Info
NTU_Logo

Imperial–Nanyang Technological University Collaboration Fund

Novel Noise Disentanglement Using Flow-based Joint Image and Noise Modelling: A Computational Imaging Application to Cardiovascular MR

Total Awards (fEC): £13,000

2022-2023

PI: Dr. Guang Yang


More Info
NRF

UKRI MRC with Korean Ministry of Science and ICT (MSIT) and National Research Foundation of Korea (NRF)

Fully Automatic Segmentation and Assessment of Atrial Scars for Atrial Fibrillation Patients Using LGE MRI: A Multicentre and Cross-National Research

Total Awards (fEC): £53,718.00

2021-2023 (Extended)

 PI: Dr. Guang Yang

More Info
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  • BHF Funded Project
    PG/16/78/32402

    LGE MRI

  • Segmentation

  • Domain Adaptation

  • GAN Based Reconstruction

    Total Awards (fEC): £356,950.61

    2017-2020

    Co-PI: Dr. Guang Yang

SABER
  • Boehringer Ingelheim Funded Project

    Data Synthesis

  • COVID-19 Research

  • Prognosis Prediction

  • Multifactorial Analysis

    Total Awards (fEC): £1,339,284.44

    2021-2024 (Extended)

    Co-PI: Dr. Guang Yang

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  • BHF Funded Project
    TG/18/5/34111

    Synthesis

  • Segmentation

  • Fast Imaging

  • Velocity Mapping

    Awards: £27,617

    2021-2022

    Co-PI: Dr. Guang Yang

MRC
  • Multicentre Validation

  • Detection/Classification

  • LGE CMR Data Analysis

  • Total Awards (fEC): £53,718.00

    2021-2022

    PI: Dr. Guang Yang

Nvidia
  • Data Harmonisation

  • Whole Heart Segmentation

  • Motion Abnormality Detection

  • Total Awards: £7,416.13

    2016, 2017, 2021

    PI: Dr. Guang Yang

Highlights

"Coming together is a beginning, staying together is progress, and working together is a success." — Henry Ford

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Hiring

We are always looking for good colleagues.

If you are interested in medical data analysis, digital healthcare, AI applications please talk to us.

Postdocs and junior research fellows who are seeking for mentorship in Imperial College Research Fellowships, Marie Skłodowska-Curie Postdoc Fellowships, and Imperial-X Fellowships please contact Dr Guang Yang for further information.

New Opening: 2x Research Associates (Closing date 21 Dec 2023)
New Opening: 2x Research Associates (Closing date 21 July 2022)
New Opening: Research Associate (Closing date 23 November 2021)

More Info

£5M+

Funding Awards

20+

Team Members

40+

GPUs

260+

Publications

46

H-Index

10,000+

Google Citations

Publications

"Publish or perish"

Funders

"I am always ready to learn although I do not always like being taught." – Winston Churchill
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