Dr. Ben Glocker is an Professor in Machine Learning for Imaging and Kheiron Medical / RAEng Research Chair in Safe Deployment of Medical Imaging AI. He is co-leading the Biomedical Image Analysis Group, lead the HeartFlow-Imperial Research Team and he is the Knowledge Transfer Lead of CHAI – The EPSRC Causality in Healthcare AI Hub. His research is at the intersection of medical imaging and artificial intelligence aiming to build safe and ethical computational tools for improving image-based detection and diagnosis of disease.

Kilian’s research is founded on computational science aimed at identifying biomedical phenotypes improving the mechanistic understanding, diagnosis, and treatment of neuropsychiatric disorders. His research embraces the diversity and complexity of disorders through unbiased, machine learning-based searches across measurements derived from highly-dimensional biological, neuroimaging, cognitive, and behavioral data.

Kilian is the founder of the CNS Lab, a Professor in Psychiatry & Behavioral Sciences and (by courtesy) in Electrical Engineering at Stanford University. He received his Ph.D. from the Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology and was an Instructor at Harvard Medical School, a research scientist at IBM Research, and an Assistant Professor at the University of Pennsylvania. His research in medical image analysis has received several awards, including in 2014 the “Creative and Novel Ideas in HIV Research Award”. Kilian is currently the principal investigator of several NIH funded projects, including a U24 and a R01s In addition, thirteen of his mentees hold faculty appointments at other universities.

Dr Ulas Bagci is a Professor (with tenure) at the Northwestern University’s Radiology at Chicago, and courtesy Professor at BME and ECE departments of Northwestern, and CRCV of University of Central Florida. His research interests are artificial intelligence, machine learning and their applications in biomedical and clinical imaging. Dr. Bagci has more than 400 peer-reviewed articles on these topics. Previously, he was a staff scientist and lab co-manager at the National Institutes of Health’s radiology and imaging sciences department, center for infectious disease imaging. Dr. Bagci holds three NIH R01 grants (as Principal Investigator), one NIH U01 grant and serves as a steering committee member of AIR (artificial intelligence resource) at the NIH. Dr. Bagci also serves as an area chair for MICCAI for several years and he is an associate editor of top-tier journals in his fields such as IEEE Trans. on Medical Imaging, Medical Physics, and Medical Image Analysis. Prof. Bagci teaches machine learning, advanced deep learning methods, computer and robot vision, and medical imaging courses. He has several international and national recognitions including best paper and reviewer awards.

Dr. Qingyu Zhao is an Assistant Professor in the Department of Radiology at Weill Cornell Medicine. He is working at the intersection between machine learning and translational research based on neuroimaging applications. His research focuses on machine-learning-based computational analysis of neuroimaging and neuropsychological data to explain brain-behavior relationships and determine biomedical phenotypes of neurological diseases. His research received K99 Pathway to Independence Award from NIH, NARSAD Young Investigator Award from BBRF, and Innovator Grant Award and Chairman’s Award for Advancing Science from Stanford Psychiatry. Before joining Cornell, he received his PhD in Computer Science from UNC Chapel Hill and was a faculty member in the Department of Psychiatry and Behavioral Sciences at Stanford School of Medicine. His broad interest lies in image analysis and statistical learning for the detection, diagnosis and treatment of diseases.