Cancer reseacher Dr. Aydogan Ozcan smiling and looking at the camera

Aydogan Ozcan, PhD

Chancellor's Professor, Departments of Engineering and Bioengineering

Languages

English

Education

Fellowship

Engineering, Stanford University, Stanford, CA, 2006

Degrees

PhD, Stanford University, Stanford, CA, 2005
MS, Stanford University, Stanford, CA, 2002
BS, Bilkent University, Ankara, Turkey, 2000

Contact Information

Scientific Interests

Computational microscopy and sensing, virtual staining of tissue, multiplexed biomarker imaging.

Highlighted Publications

S.Y. Selcuk, X. Yang, B. Bai, Y. Zhang, Y. Li, M. Aydin, A. F. Unal, A. Gomatam, Z. Guo, D. M. Angus, G. Kolodney, K. Atlan, T. K. Haran, N. Pillar, and A. Ozcan, “Automated HER2 Scoring in Breast Cancer Images Using Deep Learning and Pyramid Sampling,” BME Frontiers (AAAS) DOI: 10.34133/bmef.0048 (2024)

B. Bai, H. Wang, Y. Li, K. de Haan, F. Colonnese, Y. Wan, J. Zuo, N.B. Doan, X. Zhang, Y. Zhang, J. Li, X. Yang, W. Dong, M. Angus Darrow, E. Kamangar, H. Sung Lee, Y. Rivenson, A. Ozcan, “Labelfree virtual HER2 immunohistochemical staining of breast tissue using deep learning,” BME Frontiers (AAAS) DOI: 10.34133/2022/9786242 (2022)

J. Li, J. Garfinkel, X. Zhang, D. Wu, Y. Zhang, K. de Haan, H. Wang, T. Liu, B. Bai, Y. Rivenson, G. Rubinstein, P. Scumpia and A. Ozcan, “Biopsy-free in vivo virtual histology of skin using deep learning,” Light: Science & Applications (Nature Publishing Group) DOI: 10.1038/s41377-021- 00674-8 (2021)

K. de Haan, Y. Zhang, J.E. Zuckerman, T. Liu, A.E. Sisk, M.F.P. Diaz, K. Jen, A. Nobori, S. Liou, S. Zhang, R. Riahi, Y. Rivenson, W.D. Wallace, and A. Ozcan, “Deep learning-based transformation of H&E stained tissues into special stains,” Nature Communications DOI: 10.1038/s41467-021- 25221-2 (2021)

Y. Rivenson, H. Wang, Z. Wei, K. de Haan, Y. Zhang, Y. Wu, H. Günaydın, J.E. Zuckerman, T. Chong, A.E. Sisk, L. M. Westbrook, W.D. Wallace, and A. Ozcan, “Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning,” Nature Biomedical Engineering DOI: 10.1038/s41551-019-0362-y (2019)