Yu Gan
Assistant Professor
Charles V. Schaefer, Jr. School of Engineering and Science
Department of Biomedical Engineering
Education
- PhD (2017) Columbia University (Electrical Engineering)
Research
Artificial Intelligence, Biomedical Imaging, Computer Vision, Image Processing, Machine Learning
General Information
Dr. Yu Gan is an Assistant Professor of Biomedical Engineering at Stevens Institute of Technology. Dr. Gan's research focuses on biomedical image analysis, artificial intelligence (AI), and biomedical imaging. He has authored/co-authored over 40 referred journal papers.
Experience
2022-present, Assistant Professor, Department of Biomedical Engineering, Stevens Institute of Technology
2018-2021, Assistant Professor, Department of Electrical and Computer Engineering, the University of Alabama
2017-2018, Postdoc Research Scientist, Department of Electrical Engineering, Columbia University
2018-2021, Assistant Professor, Department of Electrical and Computer Engineering, the University of Alabama
2017-2018, Postdoc Research Scientist, Department of Electrical Engineering, Columbia University
Institutional Service
- Working Group on SES Core AI Graduate Curriculum Member
- Data Science Committee Member
- Faculty Search Committee Member
- Departmental Graduate Curriculum Committee Member
- Advisor BMES Student Chapter Chair
- Departmental Undergraduate Curriculum Committee Member
Professional Service
- Medical Image Analysis Associate Editor
- NIH ITD Study Section Panel reviewer
- IEEE Biomedical and Health Informatics Organization Chair of special sessions
- IEEE International Symposium in Biomedical Imaging (ISBI) Organization Chair of special sessions
- USDA/NIFA Panel Reviewer
- NSF graduate research fellowship Panel reviewer
- IEEE-EMBS International Conference on Body Sensor Networks Technical Program Committee Member
- Brain Informatics Organization Co-Chair
- NSF Smart Health Sensing Panel Panel Reviewer
- NIH CIDH study section Panel Reviewer
- SPIE Medical Imaging 2023 Program Committee and Reviewer
- Frontiers in Physics Guest Topic Editor
- IEEE Transactions on Image Processing Reviewer
- IEEE Journal of Biomedical Health Informatics Reviewer
- IEEE Transactions on Medical Imaging Reviewer
- Biomedical Optics Express Reviewer
- BMES 2022 Reviewer
- MICCAI 2022, the 25th International Conference on Medical Image Computing and Computer Assisted Intervention Reviewer
- SPIE Medical Imaging 2022 Program Committee member, reviewer, and, session chair
- NSF CISE review panel Panel reviewer
- NIH BIVT study section Panel reviewer
Appointments
Dr. Gan is a senior member of SPIE and Associate Editor for Medical Image Analysis.
Honors and Awards
Scialog Fellow, 2024
CAREER Award, NSF, 2023
Optics and Photonics Educational Scholarship, SPIE, 2014
Wei Foundation Scholarship, Columbia University, 2013
CAREER Award, NSF, 2023
Optics and Photonics Educational Scholarship, SPIE, 2014
Wei Foundation Scholarship, Columbia University, 2013
Professional Societies
- SPIE – Society of Photo-Optical Instrumentation Engineers Senior member
- ARVO – Association for Research in Vision and Ophthalmology Member
- Optica – Optica Member
- IEEE – Institute of Electrical and Electronics Engineers Member
- BMES – Biomedical Engineering Society Member
Grants, Contracts and Funds
Dr. Gan's research has been supported by many US government agencies including NSF, NIH, USDA/NIFA, etc, and by private foundation such as Burroughs Welcome Fund, Arnold and Mabel Beckman Foundation, and New Jersey Health Foundation, etc. He has conducted more than $6M sponsored research.
NIH: R01, NEI, PI, 2024
NIH: R21, NICHD, sub-contract PI, 2024
Scialog Collaborative Award (with Arnold and Mabel Beckman Foundation), PI, 2024
NSF: CAREER, Integrated Information and Informatics, PI, 2023
USDA/NIFA: Agricultural Engineering, co-PI (site-PI), 2023
USDA/NIFA: Data Science for Food and Agricultural Systems, PI, 2022
New Jersey Health Foundation, Research grant, PI, 2022
NIH: R21, NICHD, PI, 2021
Burroughs Wellcome Fund: Collaborative Research Travel Grants, PI, 2020
NSF: CRII, Smart and Connected Health, PI, 2020
NSF: PFI, co-PI, 2019
NIH: R01, NEI, PI, 2024
NIH: R21, NICHD, sub-contract PI, 2024
Scialog Collaborative Award (with Arnold and Mabel Beckman Foundation), PI, 2024
NSF: CAREER, Integrated Information and Informatics, PI, 2023
USDA/NIFA: Agricultural Engineering, co-PI (site-PI), 2023
USDA/NIFA: Data Science for Food and Agricultural Systems, PI, 2022
New Jersey Health Foundation, Research grant, PI, 2022
NIH: R21, NICHD, PI, 2021
Burroughs Wellcome Fund: Collaborative Research Travel Grants, PI, 2020
NSF: CRII, Smart and Connected Health, PI, 2020
NSF: PFI, co-PI, 2019
Patents and Inventions
M. Lipson, J. Xingchen, A. Klenner, X. Yao, Y. Gan, A. L. Gaeta, and C. P. Hendon, “Microresonator-frequency-comb-based platform for clinical high-resolution optical coherence tomography,” pat., USPatent 11,859,972, 2024.
F. Hu, Y. Zuo, and Y. Gan, “Robotic upper trunk support device,” pat., US Patent App. 63/549,236,2024.
F. Hu, Y. Gan, S. Cao, and X. Wang, “Real-time, fine-resolution human intra-gait pattern recognitionbased on deep learning models,” pat., US Patent App. 17/749,754, 2023.
D. A. Brown, C.-Y. Li, M. Ko, S. Cao, X. Wang, F. Hu, Y. Gan, and L. Zhang, “Simulating asplit-belt with a single-belt treadmill,” pat., US Patent App. 17/498,986, 2022.
F. Hu, Y. Zuo, and Y. Gan, “Robotic upper trunk support device,” pat., US Patent App. 63/549,236,2024.
F. Hu, Y. Gan, S. Cao, and X. Wang, “Real-time, fine-resolution human intra-gait pattern recognitionbased on deep learning models,” pat., US Patent App. 17/749,754, 2023.
D. A. Brown, C.-Y. Li, M. Ko, S. Cao, X. Wang, F. Hu, Y. Gan, and L. Zhang, “Simulating asplit-belt with a single-belt treadmill,” pat., US Patent App. 17/498,986, 2022.
Selected Publications
X. Li, X. Hou, N Ravi, Z Huang, and Y. Gan, "A Two-Stage Proactive Dialogue Generator for Efficient Clinical Information Collection Using Large Language Model" , Expert System with Applications, 2025
S. Cao, J. Zhao, F. Hu, and Y. Gan, “Real-time, free-viewpoint holographic patient rendering fortelerehabilitation via a single camera: A data-driven approach with 3d gaussian splatting for real-world adaptation,” IEEE Transactions on Visualization and Computer Graphics, 2025
B. Miao, Z. Hu, R. Mezzadra, L. Hoeijmakers, A. Fauster, S. Du, Z. Yang, M. Sator-Schmitt, H. Engel,X. Li, C. Broderick, ..., Y. Gan, ..., and C. Sun, “CMTM6 shapes antitumor t cell response throughmodulating protein expression of CD58 and PD-L1,” Cancer Cell, 2023
Z. Huang, Y. Gan, T. Lye, Y. Liu, H. Zhang, A. Laine, E. Angelini, and C. Hendon, “Cardiac adiposetissue segmentation via image-level annotations,” IEEE Journal of Biomedical and Health Informatics,vol. 27, no. 6, pp. 2932–2943, 2023
S. Cao, M. Ko, C. Li, D. Brown, X. Wang, F. Hu, and Y. Gan, “Single-belt vs. split-belt: Intelligenttreadmill control via micro-phase gait capture for post-stroke rehabilitation,” IEEE Transactions onHuman-Machine Systems, vol. 53, no. 6, pp. 1006–1016, 2023
X. Li, S. Cao, H. Liu, X. Yao, B. C. Brott, S. H. Litovsky, X. Song, Y. Ling, and Y. Gan, “Multi-scalereconstruction of undersampled spectral-spatial oct data for coronary imaging using deep learning,”IEEE Transactions on Biomedical Engineering, vol. 69, no. 12, pp. 3667–3677, 2022
Z. Huang, Y. Gan, T. Lye, H. Zhang, A. Laine, E. D. Angelini, and C. Hendon, “Heterogeneity mea-surement of cardiac tissues leveraging uncertainty information from image segmentation,” in MedicalImage Computing and Computer Assisted Intervention – MICCAI 2020, Cham: Springer InternationalPublishing, 2020, pp. 782–791
S. Cao, J. Zhao, F. Hu, and Y. Gan, “Real-time, free-viewpoint holographic patient rendering fortelerehabilitation via a single camera: A data-driven approach with 3d gaussian splatting for real-world adaptation,” IEEE Transactions on Visualization and Computer Graphics, 2025
B. Miao, Z. Hu, R. Mezzadra, L. Hoeijmakers, A. Fauster, S. Du, Z. Yang, M. Sator-Schmitt, H. Engel,X. Li, C. Broderick, ..., Y. Gan, ..., and C. Sun, “CMTM6 shapes antitumor t cell response throughmodulating protein expression of CD58 and PD-L1,” Cancer Cell, 2023
Z. Huang, Y. Gan, T. Lye, Y. Liu, H. Zhang, A. Laine, E. Angelini, and C. Hendon, “Cardiac adiposetissue segmentation via image-level annotations,” IEEE Journal of Biomedical and Health Informatics,vol. 27, no. 6, pp. 2932–2943, 2023
S. Cao, M. Ko, C. Li, D. Brown, X. Wang, F. Hu, and Y. Gan, “Single-belt vs. split-belt: Intelligenttreadmill control via micro-phase gait capture for post-stroke rehabilitation,” IEEE Transactions onHuman-Machine Systems, vol. 53, no. 6, pp. 1006–1016, 2023
X. Li, S. Cao, H. Liu, X. Yao, B. C. Brott, S. H. Litovsky, X. Song, Y. Ling, and Y. Gan, “Multi-scalereconstruction of undersampled spectral-spatial oct data for coronary imaging using deep learning,”IEEE Transactions on Biomedical Engineering, vol. 69, no. 12, pp. 3667–3677, 2022
Z. Huang, Y. Gan, T. Lye, H. Zhang, A. Laine, E. D. Angelini, and C. Hendon, “Heterogeneity mea-surement of cardiac tissues leveraging uncertainty information from image segmentation,” in MedicalImage Computing and Computer Assisted Intervention – MICCAI 2020, Cham: Springer InternationalPublishing, 2020, pp. 782–791
Courses
BME 460 Biomedical Digital Signal Processing Lab
BME 571 Machine Learning in Biomedical Application
BME 571 Machine Learning in Biomedical Application