Dept of Electronic & Computer Engineering - Distinguished Lecturer - Medical Imaging and Genomic Data Processing in the Era of AI

10:30am - 11:30am
Room 4621 (lift 31/32), Academic Bldg.

AI driven by deep learning have attracted much attention in the last decade. The enormous success of deep learning stems from its unique capabilities of extracting essential features from big data and then making inferences. However, the data-driven process has many potential flaws, such as the demand for a large amount of annotated data and lack of interpretability. In this talk, I will summarize recent advances in deep learning-imaging techniques, in particular, unsupervised and semi-supervised deep learning as well as technical tools that make AI more interpretable and trustworthy. Specific applications of the new generation of deep learning techniques in biomedical imaging, treatment planning, high dimensional genomic data analysis, and clinical decision-making will be discussed.

Event Format
Speakers / Performers:
Prof. Lei Xing
Jacob Haimson and Sarah S. Donaldson Professor Stanford University

Dr. Lei Xing is the Jacob Haimson & Sarah S. Donaldson Professor and Director of Medical Physics Division of Radiation Oncology Department and Department of Electrical engineering at Stanford. Dr. Xing obtained his PhD in Physics from the Johns Hopkins University. His research has been focused on AI in medicine, medical imaging, treatment planning, image guided interventions, and molecular imaging. Dr. Xing is an author on more than 400 peer reviewed publications. He is a fellow of AAPM (American Association of Physicists in Medicine) and AIMBE (American Institute for Medical and Biological Engineering). He is the recipient of the 2023 Edith Quimby Lifetime Achievement Award of AAPM, which denotes outstanding scientific achievements in medical physics, influence on the professional development of others, and organizational leadership.

Recommended For
Faculty and staff
PG students
UG students
Department of Electronic & Computer Engineering
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