CV

Education

• Ph.D in Biomedical Engineering, Georgia Institute of Technology and Emory University, 2020
  • Advisor: Professor May D. Wang, Ph.D., IEEE Fellow
  • Thesis: “Enable precision medicine by integrating multimodal biomedical data.”
• B.S. in Biomedical Engineering, Peking University, 2014
  • Academic Performance: Top 5%

Work Experience

• Dec. 2025 - Present: Assistant Professor
  • School of Biomedical Engineering, Shenzhen University, Shenzhen, China
  • Research Interest:
    • Medical image processing
    • Machine learning and deep learning for biomedical and healthcare applications, especially focused in multi-modal biomedical data fusion for precision medicine
    • Large language models and multi-modal vision language models in medicine
• Aug. 2021 - Nov. 2025: Staff Engineer (Medical Imaging Analysis/Machine Learning)
  • Shanghai United Imaging Healthcare Co., Ltd., Shanghai, China
  • Led a team of fifteen engineers as the technical leader (six Ph.D. and seven Master’s), driving AI-enpowered technology and application development for MRI systems.
  • Successfully developed products that are widely deployed across United Imaging’s full range of 1.5T, 3T, and 5T MRI devices, providing high-quality and efficient medical imaging services to a large number of patients worldwide.
  • Collaborated closely with multiple leading hospitals and research institutions, resulting in over 20 domestic and international patents.
• Aug. 2014 - Dec. 2020: Graduate Research Assistant
  • Georgia Institute of Technology and Emory University, Atlanta, GA, USA
  • Supervisor: Professor May D. Wang
  • Multi-Modality Biomedical Data Integration
    • Designed deep autoencoders to combine medical images (MRI & PET) with genomics and electronic health records (EHRs) for accurate diagnosis of Alzheimer’s Disease (AD).
    • Developed a cross-modality translation network to integrate multi-omics data for cancer survival analysis.
    • Designed a divergence-based consensus learning method to learn modality-invariant representation.
    • Proposed a gene embedding-based collaborative filtering framework for multi-omics data integration.
  • Medical Imaging Analysis
    • Developed a convolutional autoencoder for semi-supervised learning of endomicroscopic images for improved diagnosis of Barrett’s Esophagus (BE).
    • Designed a whole-slide imaging (WSI) classification pipeline for heart rejection diagnosis.
    • Developed a multi-scale convolutional network for improved classification by utilizing image pyramid of WSI.
• Summer 2018 & 2019: Summer Intern (Medical Imaging Analysis/Machine Learning)
  • Intuitive Surgical, Inc, Sunnyvale, CA, USA
  • Deep Learning based CT Images Segmentation for Lung Blood Vessels(May 2019 - Aug 2019)
    • Implemented a 3D U-Net model for volumetric medical image segmentation.
    • Developed adversarial training to regularize the network with Wasserstein distance or multi-scale L1 loss.
  • Partial 3D Reconstruction with Digital Tomosynthesis (DTS)(May 2018 - Aug 2018)
    • Implemented a pipeline for C-arm X-ray camera calibration and pose estimation with 2D fiducial markers.
    • Implemented partial 3D chest X-ray reconstruction with the shift-and-add (SAA) algorithm and the simultaneous algebraic reconstruction technique (SART).

Publications

Journal Publications

1. Tong L, Shi W, Isgut M, Zhong Y, Lais P, Gloster L, Sun J, Swain A, Giuste FO, and Wang MD. “Integrating multi-omics data with EHR for precision medicine using advanced artificial intelligence.” IEEE Reviews in Biomedical Engineering. 2023 Oct 12;17:80-97.
2. Tong L, Wu H, Wang MD, Wang G. “Introduction of medical genomics and clinical informatics integration for p-Health care.” Progress in molecular biology and translational science. 2022 Jan 1;190(1):1-37.
3. Tong L, Mitchel J, Chatlin K, and Wang MD. “Deep Learning based Feature-Level Integration of Multi-Omics Data for Breast Cancer Patients Survival Analysis.” BMC Medical Informatics and Decision Making. 2020 Sep 15;20(1):225.
4. Tong L, Wu H, and Wang MD. “Integrating Multi-Omics Data by Learning Modality Invariant Representations for Improved Prediction of Overall Survival of Cancer.” Methods. 2021 May 1;189:74-85.
5. Tong L, Wu H, and Wang MD. “CAESNet: Convolutional AutoEncoder based Semi-supervised Network for Improving Multi-class Classification of Endomicroscopic Images.” Journal of American Medical Informatics Association. 2019 Nov;26(11):1286-96.
6. Tong L, Wu PY, Phan JH* (equal contribution first authors), Hassanzadeh HR, SEQC Consortium, Tong WD, and Wang MD. “Impact of RNA-seq Data Analysis Algorithms on Gene Expression Estimation and Downstream Prediction.” Scientific Reports. 2020 Oct 21;10(1):1-20.
7. Wu S, She H, Wang Z, Tong L, Wang Z, Du YP. Real‐Time Phase‐Contrast Cardiovascular MRI Using a Deep Learning Reconstruction Network With Combined Dictionary Learning and CNN. Magnetic Resonance in Medicine. 2025 Oct 17.
8. Venugopalan J, Tong L, Hassanzadeh H, and Wang MD. “Multimodal Deep Learning Models for Early Detection of Alzheimer’s Disease Stage.” Scientific Reports. 2021 Feb 5;11(1):1-3.
9. Choudhary A, Tong L (equal contribution first authors), Zhu Y, Wang MD. “Advancing Medical Imaging Informatics by Deep Learning-Based Domain Adaptation.” Yearbook of Medical Informatics. 2020 Aug;29(01):129-38.
10. Wu H, Zhu Y, Shi W, Tong L, and Wang MD, “Fairness Artificial Intelligence in Clinical Decision Support: Mitigating Effect of Health Disparity.” IEEE Journal of Biomedical and Health Informatics, 2024 Dec. 9.
11. Giuste FO, Sequeira R, Keerthipati V, Lais P, Mirzazadeh A, Mohseni A, Zhu Y, Shi W, Marteau B, Zhong Y, Tong L, Das B, Shehata B, Deshpande S, and Wang MD. “Explainable synthetic image generation to improve risk assessment of rare pediatric heart transplant rejection.” Journal of biomedical informatics. 2023 Mar 1;139:104303.
12. Giuste FO, Shi W, Zhu Y, Naren T, Isgut M, Sha Y, Tong L, Gupte M, Wang MD. “Explainable artificial intelligence methods in combating pandemics: A systematic review.” IEEE Reviews in Biomedical Engineering. 2022 Jun 23;16:5-21.
13. Anklam E, Bahl MI, Ball R, Beger RD, Cohen J, Fitzpatrick S, Girard P, Halamoda-Kenzaoui B, Hinton D, Tagle D, Tong L, Tong W, and Wang MD. “Emerging technologies and their impact on regulatory science.” Experimental Biology and Medicine. 2022 Jan;247(1):1-75.
14. Shi W, Tong L, and Wang MD. “COVID-19 Automatic Diagnosis with Radiographic Imaging: Explainable Attention Transfer Deep Neural Networks.” IEEE Journal of Biomedical and Health Informatics. 2021 Apr; 25 (7): 2376–87.
15. Littman AR, Janssen KM, Tong L, Wu H, Wang MD, Blum E, and Kirsch AJ. “Did COVID-19 Affect Time to Presentation in the Setting of Pediatric Testicular Torsion?” Pediatric Emergency Care. 2021 Feb;37(2):123.
16. Zhang Y, Wu H, Liu H, Tong L, and Wang MD. “Mitigating the Effect of Dataset Bias on Training Deep Models for Chest X-rays.” arXiv preprint arXiv:1910.06745 (2019).

Conference Publications

1. Tong L, Wang P, Zhu L, Qin S, and Wang Z. “A deep-learning-based framework for spark artifacts detection and correction.” 2024 ISMRM & ISMRT Annual Meeting & Exhibition. May 4-9, 2024. Singapore.
2. Tong L, Wang P, and Wang Z. “A deep-learning-based Signal-to-Noise Ratio (SNR) adaptive uniformity correction method.” 2024 ISMRM & ISMRT Annual Meeting & Exhibition. May 4-9, 2024. Singapore.
3. Tong L, Sha Y, and Wang MD. “Improving Classification of Breast Cancer by Utilizing the Image Pyramids of Whole-Slide Imaging and Multi-Scale Convolutional Neural Networks.” Conf Proc IEEE Computer Society Signature Conference on Computers, Software and Applications (COMPSAC). Milwaukee, Wisconsin, USA. July 15-19, 2019. Vol. 1, pp. 696-703.
4. Tong L, Hoffman RA, Deshpande SR, and Wang MD. “Predicting Heart Rejection Using Histopathological Whole-Slide Imaging and Deep Neural Network with Dropout.” Conf Proc IEEE EMBS Biomed Health Inform, BHI. Orlando, FL, USA. 2017 Feb. 16-19. pp. 1-4.
5. Tong L, Yang C, Wu PY and Wang MD. “Evaluating the impact of sequencing error correction for RNA-seq data with ERCC RNA spike-in controls.” Conf Proc IEEE EMBS Biomed Health Inform, BHI. Las Vegas, NV, USA. 2016 Feb. 24; 74-77.
6. Cui Y, Qi H, Zhang Z, Zhang H, Yuan S, Cai B, Li J, Zhang M, Wang Z, Tong L, and Luo J. “DTI with minimal data: image translation based distortion correction and FA map generation for clinical efficiency.” 2025 ISMRM & ISMRT Annual Meeting & Exhibition. May 10-15, 2025, Honolulu, Hawaii, USA.
7. Wu S, She H, Wang Z, Tong L, Wang Z, and Du Y. “Accelerated Free-Breathing Phase Contrast Cardiovascular MRI using Spatial-Temporal Dictionary Learning Neural Network.” Proceedings of the 2024 9th International Conference on Biomedical Signal and Image Processing. pp. 29-33.
8. Wang C, Chen J, Zhang X, Tong L, and Yang Y. “MRI proton density fat fraction (PDFF) optimization for bone marrow protection in RT.” 2024 AAPM 66th Annual Meeting & Exhibition. July 21-25, 2024. Los Angeles, CA, USA.
9. Cui Y, Yuan S, Wang Z, Tong L, and Luo J. “A multi-contrast translation-based registration approach for distortion correction in DTI.” 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). July 15-19, 2024. Orlando, FL, USA.
10. Patil SM, Tong L, and Wang MD. “Generating Region of Interests for Invasive Breast Cancer in Histopathological Whole-Slide-Image.” 2020 IEEE Computer Society Signature Conference on Computers, Software and Applications (COMPSAC). Madrid, Spain. pp. 732-728.
11. Giuste FO, Venkatesan M, Zhao C, Tong L, Zhu Y, Deshpande S, and Wang MD. “Automated Classification of Acute Rejection from Endomyocardial Biopsies.” The 11th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB). pp. 1-9.
12. Shi W, Tong L, Zhuang Y, Zhu Y and Wang MD. “EXAM: An Explainable Attention-based Model for COVID-19 Automatic Diagnosis.” The 11th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB). pp. 1-6.
13. Jiang Y, Alford K, Ketchum F, Tong L, and Wang MD. “TLSurv: Integrating Multi-Omics Data by Multi-Stage Transfer Learning for Cancer Survival Prediction.” The 11th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB). pp. 1-10.
14. Mitchel J, Chatlin K, Tong L, and Wang MD. “A Translational Pipeline for Overall Survival Prediction of Breast Cancer Patients by Decision-Level Integration of Multi-Omics Data.” 2019 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2019). November 18-21, 2019. San Diego, CA, USA. pp. 1573-1580.
15. Choudhary A, Wu H, Tong L, and Wang MD. “Learning to Evaluate Color Similarity for Histopathology Images Using Triplet Networks.” The 10th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB). Niagara Falls, NY, Sept 7-10, 2019. pp. 466-474.
16. Vizcarra J, Place R, Tong L, Gutman D and Wang MD. “Fusion in Breast Cancer Histology Classification.” The 10th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB). Niagara Falls, NY, Sept 7-10, 2019. pp. 485-493.
17. Zhu Y, Tong L, and Wang MD. “Improved Prediction on Heart Transplant Rejection Using Convolutional Autoencoder and Multiple Instance Learning on Whole-Slide Imaging.” 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI). Chicago, IL, USA. May 2019. pp. 1-4.
18. Dooley AE, Tong L, and Wang MD. “Prediction of Heart Transplant Rejection Using Histopathological Whole-Slide Imaging.” Conf Proc IEEE EMBS Biomed Health Inform, BHI. Las Vegas, NV, USA. 2018 Mar. 4-7; 251-254.
19. Wu H, Tong L, and Wang MD. “Improving Multi-class Classification for Endomicroscopic Images by Semi-supervised Learning.” Conf Proc IEEE EMBS Biomed Health Inform, BHI. Orlando, FL, USA. 2017 Feb. 16-19. pp. 5-8.
20. Kothari S, Wu H, Tong L, Woods KE, and Wang MD. “Automated Prediction for Esophageal Optical Endomicroscopic Images.” Conf Proc IEEE EMBS Biomed Health Inform, BHI. Las Vegas, NV, USA. 2016 Feb. 24; 160-163.
21. Yang C, Wu PY, Tong L, Phan JH and Wang MD. “The impact of RNA-seq aligners on gene expression estimation.” ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM BCB). Atlanta, GA, USA. 2015 Sept. 9; 462-471.

Selected Patents

1. Tong L. Systems and methods for signal processing. US20240046469A1. 2024-02-08.
2. Tong L, Sun T, and Xin Y. Calibration methods and systems for medical imaging. US20230181146A1. 2023-06-15.
3. Tong L, Sun T, and Xin Y. Method and device for water-fat separation of image, computer apparatus, and computer-readable storage medium. US20230384407A1. 2023-11-30.
4. Sun T, Tong L, Lu H, and Hu K. Coil fault detection methods and systems. EP4329603A1. 2024-03-06.

Teaching

• Industrial Co-Advisor, Shanghai United Imaging Healthcare/Shanghai Jiaotong University Joint Program, Shanghai, China, 2023 – 2025
  • Master Student: Sifan Wu (Co-advised with Prof. Yiping Du)
  • Master Student: Cui Ya (Co-advised with Prof. Jie Luo)
  • PhD Student: Tian Zeng (Co-advised with Prof. Hongjiang Wei)
  • PhD Student: Weitao Zu (Co-advised with Prof. Cheng Jin)
• Project Mentor, Bio-MIBLab, Georgia Institute of Technology and Emory University, Atlanta, GA, USA, 2015 - 2020
  • Mentored multiple junior PhD students, two Master students, and seven undergraduate students.
• Graduate Teaching Assistant, BME, Georgia Institute of Technology and Emory University, Atlanta, GA, USA, 2015 - 2020
  • Facilitated “BMED6780/ECE6780/BMED4783/ECE4783 Medical Image Processing” (undergraduate and graduate level): giving guest lectures, leading discussion sessions, and mentoring course projects.
  • Facilitated “BMED 2210 Conservation Principles in Biomedical Engineering” (undergraduate level): giving guest lectures and leading discussion sessions.
  • Facilitated “BMED 8813 Biomedical and Health Informatics” (graduate level): giving guest lectures, leading discussion sessions, and mentoring course projects.

Honors and Awards

• Company-Level Outstanding Team Award, Shanghai United Imaging Healthcare, 2024
• MRI BU Outstanding Individual Award, Shanghai United Imaging Healthcare, 2023
• MRI BU Outstanding Team Award, Shanghai United Imaging Healthcare, 2023
• IEEE BSN/BHI Travel Award, Mar 2018
• IEEE BHI 2018 Big Data Competition Awards 1st Award, Mar 2018
• Ph.D. Scholarship, China Scholarship Council (CSC), July 2014
• Undergraduate Exchange Scholarship, China Scholarship Council (CSC), Jan 2014
• Jinlongyu Scholarship (Top 5%), Peking University, Sept 2013
• Model Student of Academic Records (Top 5%), Peking University, Sept 2013
• Xiashouyu-Huangyuceng Scholars (Top 10%), Peking University, Apr 2012
• Junzheng Foundation Research Fellowship (Top 10%), Peking University, Apr 2012
• POSCO Fellowship (Top 5%), Peking University, Sept 2011
• Jiangzehan Mathematical Modeling Contest Third Prize, Peking University, June 2011

Service and leadership

• Young Professional Activities Co-Chair for IEEE Healthcare Summit (IHS), 2021
• Webmaster, IEEE The International Conference on Biomedical and Health Informatics (BHI), 2017
• Webmaster, The ACM Conference on Bioinformatics, Computational Biology, and Health Informatics(ACM-BCB), 2015
• Volunteer, 2015 ACM-BCB conference, Atlanta, Georgia (three days in Sept. 2015)
• Student activity co-chair, 2015 ACM-BCB conference, Atlanta, Georgia (three days in Sept. 2015)
• Volunteer, 2014 Gensips conference, Atlanta, Georgia (two days in Dec. 2014)
• Secretary of Youth-Volunteer Association at College of Engineering, Peking University, 2012-2013
• Voluntary teaching for disabled children in Beijing, Peking University, 2012-2013
• Advisor for freshmen, Peking University, 2012-2013

Skills

• Language: Mandarin Chinese and English
• Programming Languages: Python, MATLAB, and C/C++
• Others: Shell, TensorFlow, PyTorch, LlamaFactory, and LaTeX