- +852 2766 7670
- shu-jun.wang@polyu.edu.hk
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Prof. Emma Shujun WANG is an Assistant Professor at PolyU BME. Before that, she was a Research Associate in the Department of Applied Mathematics and Theoretical Physics, at the University of Cambridge from 2022 to 2023. She was a Postdoctoral Researcher in the Department of Computer Science and Engineering at The Chinese University of Hong Kong from 2021 to 2022. She received her Ph.D from the Department of Computer Science and Engineering at The Chinese University of Hong Kong in 2021, and B.Eng from Honors College at Northwestern Polytechnical University in 2017.
Prof. Wang's research is in the interdisciplinary field of artificial intelligence (AI) and healthcare. More specifically, she specializes in the areas of machine learning (ML), deep learning (DL), and their major applications on digital health and computational precision medicine. She is dedicated to designing AI-driven computational methods to enable reliable decision-making models for precision medicine, covering from disease diagnosis to prognosis, and from medical image computing to multi-modal biomedical data integration. Her current and future research will facilitate personalized prognosis and treatment with multi-modal biomedical data computing from both imaging and non-imaging information and reliable machine learning-based disease diagnosis algorithms.
Prof. Wang has published 20 papers on top-tier conferences and journals (on The Lancet Digital Health (IF: 36.615), IEEE-TMI, MedIA, NeurIPS, AAAI, ECCV, MICCAI, etc.). Her team won the Best Paper Award of CMMCA workshop at MICCAI 2022. She has attended several international challenges on medical image analysis and won the Champion of the REFUGE challenge in 2018 and the second place of PALM challenge in 2019. She also co-organized the workshop of Women in Medical Image Understanding and Analysis in 2022. Additionally, she serves as reviewer for top-tier journals and conferences, and was selected as IEEE TMI Distinguished Reviewer in 2023.
Prof. Wang's research is in the interdisciplinary field of artificial intelligence (AI) and healthcare. More specifically, she specializes in the areas of machine learning (ML), deep learning (DL), and their major applications on digital health and computational precision medicine. She is dedicated to designing AI-driven computational methods to enable reliable decision-making models for precision medicine, covering from disease diagnosis to prognosis, and from medical image computing to multi-modal biomedical data integration. Her current and future research will facilitate personalized prognosis and treatment with multi-modal biomedical data computing from both imaging and non-imaging information and reliable machine learning-based disease diagnosis algorithms.
Prof. Wang has published 20 papers on top-tier conferences and journals (on The Lancet Digital Health (IF: 36.615), IEEE-TMI, MedIA, NeurIPS, AAAI, ECCV, MICCAI, etc.). Her team won the Best Paper Award of CMMCA workshop at MICCAI 2022. She has attended several international challenges on medical image analysis and won the Champion of the REFUGE challenge in 2018 and the second place of PALM challenge in 2019. She also co-organized the workshop of Women in Medical Image Understanding and Analysis in 2022. Additionally, she serves as reviewer for top-tier journals and conferences, and was selected as IEEE TMI Distinguished Reviewer in 2023.
學歷
- Ph.D., Department of Computer Science and Engineering, The Chinese University of Hong Kong (CUHK), Hong Kong, Aug. 2017 – Jul. 2021
- B.Eng., Honors College, Computer Science and Engineering, Northwestern Polytechnical University (NPU), Xi’An, China, Sep. 2013 – Jun. 2017
學術和專業經驗
- Postdoctoral Researcher, Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, Sep. 2021 – Apr. 2022
- Research Associate, Department of Applied Mathematics and Theoretical Physics, University of Cambridge, United Kingdom, May. 2022 – Mar. 2023
