Anant Madabhushi

Anant Madabhushi (born February 15, 1976) is a prominent biomedical engineer renowned for his pioneering work in developing artificial intelligence (AI) tools to enhance disease diagnosis, prognosis, and treatment planning. He holds a primary faculty appointment in the Department of Biomedical Engineering at Emory University and Georgia Institute of Technology, with secondary appointments in the Departments of Radiology and Imaging Sciences, Biomedical Informatics, and Pathology. Additionally, Dr. Madabhushi serves as the executive director of the Emory Empathetic AI for Health Institute.

In 2018, the magazine Prevention included Madabhushi's work on "Smart Imaging Computers" for identifying lung cancer patients who could benefit from chemotherapy on a list called "The 10 Most Incredible Medical Breakthroughs of 2018”. In 2019, Madabhushi was one of five scientists included in an article in Nature titled "Offbeat approaches to cancer research".

Education Dr. Madabhushi earned his Bachelor of Engineering in Biomedical Engineering from Mumbai University in 1998. He then obtained a Master of Science in Biomedical Engineering from the University of Texas at Austin in 2000, followed by a PhD in Bioengineering from the University of Pennsylvania in 2004.

In 2022, Dr. Madabhushi transitioned to Emory University, where he continues his research and leadership in biomedical engineering and AI applications in healthcare.

Awards and memberships Dr. Madabhushi is a Fellow of the American Institute of Medical and Biological Engineering, the Institute of Electrical and Electronics Engineers (IEEE), and the National Academy of Inventors. In 2017, he received the IEEE Engineering in Medicine and Biology Society award for technical achievements in computational imaging and digital pathology. In 2021, he was recognized as one of Crain's Cleveland Business Notable Entrepreneurs of the year and received a Faculty Distinguished Research Award from Case Western Reserve University.

Selected publications

Flannery, B. T., Sandler, H. M., Lal, P., Feldman, M. D., Santa-Rosario, J. C., Pathak, T., Mirtti, T., Farre, X., Correa, R., Chafe, S., Shah, A., Efstathiou, J. A., Hoffman, K., Hallman, M. A., Straza, M., Jordan, R., Pugh, S. L., Feng, F., & Madabhushi, A. (2025). Stress testing deep learning models for prostate cancer detection on biopsies and surgical specimens. The Journal of Pathology, 245(2), 123-134. Wu, Y., Xu, X., Cheng, Y., Zhang, X., Liu, F., Li, Z., Hu, L., Madabhushi, A., Gao, P., Liu, Z., & Lu, C. (2025). BEEx Is an Open-Source Tool That Evaluates Batch Effects in Medical Images to Enable Multicenter Studies. Cancer Research, 85(1), 45-56. Xu, H., Wang, M., Shi, D., Qin, H., Zhang, Y., Liu, Z., Madabhushi, A., Gao, P., Cong, F., & Lu, C. (2025). When multiple instance learning meets foundation models: Advancing histological whole slide image analysis. Medical Image Analysis, 72, 102145.