• 1997-2002    Ph.D. in Computer Science, Harvard University
• 1989-1992    M.S.E., the University of Texas at Austin
• 1984-1988    B.S.E., Zhejiang University

• 2017 - present, Professor, School of Biomedical Engineering, Shanghai Jiao Tong University
• 2013 - 2017, Professor, School of Medicine, Zhejiang University

Recent Publications:

1.       Y. Tian, J. Wang, W. Yang, J. Wang, D. Qian, “Deep Multi-Instance Transfer Learning for Pneumothorax Classification in Chest X-ray Images,” Medical Physics，2021.

2.       J. Xu, J. Wang, X. Bian, J. Zhu, C. Tie, X. Liu, Z. Zhou, X. Ni, D. Qian, “Deep learning for nasopharyngeal carcinoma identification using both white light and narrow-band imaging endoscopy,” The Laryngoscope, vol 0, pp. 1-9, 2021.

3.       R. Li, Y. Huang, H. Chen, X. Liu, Y. Yu, D. Qian, and L. Wang, “3D Graph-Connectivity Constrained Network for Hepatic Vessel Segmentation”, IEEE Journal of Biomedical and Health Informatics, 2021.

4.       J. Wang, C. Yuan, C. Han, Y. Wen, H. Lu, C. Liu, Y. She, J. Deng, B. Li, D. Qian, C. Chen., “IMAL-Net: Interpretable Multi-task Attention Learning Network for Invasive Lung Adenocarcinoma Screening in CT Images,” Medical Physics，October 21, 2021.

5.       Y. Bao, J. Wang, T. Li, L. Wang, J. Xu, J. Ye and D. Qian, “Self-Adaptive Transfer Learning for Multicenter Glaucoma Classification in Fundus Retina Images”, MICCAI Workshop on Ophthalmic Medical Image Analysis, Strasbourg, France, September 27, 2021.

6.       Z. Zuo, P. Wang, X. Chen, L. Tian, H. Ge, D. Qian, “SWnet: A deep learning model for drug response prediction from cancer genomic signatures and compound chemical structures”, BMC Bioinformatics, vol 22, pp. 434, 2021.

7.       J. Wang, C. Liu, J. Li, C. Yuan, L. Zhang, C. Jin, J. Xu, Y. Wang, Y. Wen, H. Lu, B. Li, C. Chen, X. Li, D. Shen, D. Qian and J. Wang, “y-time prediction of COVID-19 patients”, NPJ Digital Medicine, vol 4, pp. 124, August 16, 2021.

8.       J. Zhang, W. Hu, S. Li, Y. Wen, Y. Bao, H. Huang, C. Xu, D. Qian, “Chromosome Classification and Straightening Based on an Interleaved and Multi-task Network”, IEEE Journal of Biomedical and Health Informatics, vol 25, pp. 3240-3251, August 2021.

9.       C. Yuan, M. Zhang, X. Huang, W. Xie, X. Lin, W. Zhao, B. Li, D. Qian, “Diffuse Large B-cell Lymphoma Segmentation in PET-CT Images via Hybrid Learning for Feature Fusion”, Medical Physics, vol. 48, pp. 28, March, 2021.

10.    J. Xu, R. Zhao, Y. Yu, Q. Zhang, X. Bian, J. Wang, Z. Ge, D. Qian, “Real-Time Automatic Polyp Detection in Colonoscopy using Feature Enhancement Module and Spatiotemporal Similarity Correlation Unit”, Biomedical Signal Processing and Control, vol. 66, February 9, 2021.

11.    D. Chen, J. Zhang, D. Qian, D. Chen, K. Wang, X. Dong, “Segmentation of Lung Adenocarcinoma Cells’ Pathological Image Based on Deep Learning Method”, Proceedings of the 2021 4^th International Conference on Image and Graphics Processing (ICIGP 2021), Sanya, China, January 1-3, 2021.

12.    D. Liu, X. Peng, X. Liu, Y. Li, Y. Bao, J. Xu, X. Bian, W. Xue, D. Qian, “A Real-Time System Using Deep Learning to Detect and Track Ureteral Orifices During Urinary Endoscopy”, Computers in Biology and Medicine, vol 128, January 2021.

13.    J. Wang, Y. Bao, Y. Wen, H. Lu, H. Luo, Y. Xiang, X. Li, C. Liu, D. Qian, “Prior-Attention Residual Learning for More Discriminative COVID-19 Screening in CT Images”, IEEE Transactions on Medical Imaging, pp. 0, November 2020.

14.    X. Guan, S. Wang, P. Kuang, H. Lu, M. Zhang, D. Qian, X. Xu, “The usefulness of imaging quantification in discriminating non-calcified pulmonary hamartoma from adenocarcinoma”, Frontiers in Oncology, vol. 10, October 22, 2020.

15.    M. Zhang, Y. Bao, W. Rui, C. Shangguan, J. Liu, J. Xu, X. Lin, M. Zhang, X. Huang, Y. Zhou, Q. Qu, H. Meng, D. Qian, B. Li, “Performance of 18F-FDG PET/CT Radiomics for Predicting EGFR Mutation Status in Patients with Non-Small Cell Lung Cancer”, Frontiers in Oncology, vol 10, October 8, 2020.

16.    C. Yuan, Y. Tang, D. Qian, “Ovarian Cancer Prediction in Proteomic Data Using Stacked Asymmetric Convolution”, MICCAI 2020, Lima, Peru, October 4-8, 2020.

17.    R. Zhang, G. Li, Z. Li, S. Cui, D. Qian, Y. Yu, “Adaptive Context Selection for Polyp Segmentation”, MICCAI 2020, Lima, Peru, pp. 253-262, September 29, 2020.

18.    L. Tong, C. Ning, Y. Wen, X. Xu, C. Ye, S. Zhang, D. Qian, Y. Liang, “Differentiation of primary open angle-closure glaucoma and primary open angle glaucoma based on disc image with a deep learning method”, Association for Research in Vision and Ophthalmology (ARVO 2020), Baltimore, MD, US, May 3-7, 2020.

19.    J. Wang, X. Chen, H. Lu, L. Zhang, J. Pan, Y. Bao, J. Su, D. Qian, “Feature-shared adaptive-boost deep learning for invasiveness classification of pulmonary sub-solid nodules in CT images”, Medical Physics, vol. 47, No. 4, pp1738-1749, February 5, 2020.

20.    Z. Zhang, K. Lin, Z. Zuo, D. Qian, D. Huang, J. Li, “Prediction for atrial fibrillation recurrence after catheter ablation using an artificial intelligence-assisted coronary sinus electrogram”, American Heart Association Scientific Sessions (AHA2019), Philadelphia,  PA, November 16-18, 2019.

21.    Z. Cheng, J. Zhang, N. He, Y. Li, Y. Wen, H. Xu, R. Tang, Z. Jin, E. Mark Haacke, F. Yan, D. Qian, “Radiomic Features of the Nigrosome-1 Region of the Substantia Nigra: Using Quantitative Susceptibility Mapping to Assist the Diagnosis of Idiopathic Parkinson’s Disease”, Frontiers in Aging Neuroscience, vol. 11, pp. 167, July 16, 2019.

22.    L. Lou, L. Yang, X. Ye, Y. Zhu, S. Wang, L. Sun, D. Qian, J. Ye, “A Novel Approach for Automated Eyelid Measurements in Blepharoptosis Using Digital Image Analysis”, Current Eye Research, vol.44, No. 10, pp. 1075-1079, May 31, 2019.

23.    S. Wang, H. Zhang, D. Qian, “A Semi-supervised Bleeding Detection Method in Wireless Capsule Endoscopy”, Digestive Disease Week (DDW 2019), San Diego, CA, USA, May 18-21, 2019.

24.    L. Zhou, K. Wang, H. Sun, S. Zhao, X. Chen, D. Qian, H. Mao, J. Zhao, “Novel Graphene Biosensor Based on the Functionalization of Multifunctional Nano-bovine Serum Albumin for the Highly Sensitive Detection of Cancer Biomarkers”, Nano-Micro Letters, vol.250, pp. 13, February 20, 2019.

25.    Z. Zuo, K. Wang, L. Gao, V. Ho, H. Mao, D. Qian, “A novel mass-producible capacitive sensor with fully symmetric 3D structure and microfluidics for cell detection”, Sensors, vol.19, pp. 325, January 15, 2019.

26.    M. Zhou, K. Jin, S. Wang, J. Ye, D. Qian, “Color Retinal Image Enhancement Based on Luminosity and Contrast Adjustment”, IEEE Transactions on Biomedical Engineering, vol. 65, No. 3, pp: 521-527, March 2018.

27.    X. Ye, S. Wang, Y. Zhu, H. Shao, L. Lou, D. Qian, J. Ye, “Automatic Design and Fabrication of a Custom Ocular Prosthesis using 3D Volume Difference Reconstruction (VDR)”, IEEE Access, vol. 6, No. 1, pp. 14339~14346, February 5, 2018.

28.    K. Jin, M. Zhou, S. Wang, L. Lou, Y. Xu, J. Ye, D. Qian, “Computer-aided diagnosis based on enhancement of degraded fundus photographs”, Acta Ophthalmology, vol.96, No. 3, pp. 320-326, November 1, 2017.

29.    K. Jin, H. Lu, Z. Su, C. Cheng, J. Ye, D. Qian, “Telemedicine screening of retinal diseases with a handheld portable non-mydriatic fundus camera”, BMC Ophthalmology, vol. 17, No. 1, pp.89, June 13, 2017.

30.     S. Wang, K. Jin, H. Lu, C. Cheng, J. Ye, D. Qian, “Human Visual System-Based Fundus Image Quality Assessment of Portable Fundus Camera Photographs”, IEEE Transactions on Medical Imaging, vol.35, No. 4, pp.1046-1055, April 2016.

31.     C. Deng, Y. Sheng, S. Wang, W. Hu, S. Diao, D. Qian, "A CMOS Smart Temperature Sensor With Single-Point Calibration Method for Clinical Use”, IEEE Transactions on Circuits and Systems II-Express Briefs, vol.63, No.2, pp136-40, Feb. 2016.

• Fall Semester 2020: Undergraduate Course: BioDesign
• Spring Semester 2019, 2020: Graduate Course: Artificial Intelligence in Medicine