Biography: Ulas Bagci is a principal investigator at the Department of Computer Science, UCF, Orlando. His research interests are artificial intelligence, machine learning and their applications in biomedical and clinical imaging. Previously, he was a staff scientist at the NIH's Center for Infectious Disease Imaging (CIDI) Lab, Department of Radiology and Imaging Sciences (RAD&IS). He had also been the leading scientist (image analyst) in biosafety/bioterrorism project initiated jointly by NIAID and IRF. He is a senior member of IEEE and RSNA, and member of scientific organizations such as SNMMI, ASA, RSS, AAAS, and MICCAI. He is the recipient of many awards including NIH's FARE award (twice), RSNA Merit Awards (more than five times), best paper awards, poster prizes, and highlights in journal covers and the media. He was co-chair of Image Processing Track of SPIE Medical Imaging Conference, 2017, and technical committee member of MICCAI for several years. More recently, he develops explainable and human-in-the loop machine learning algorithms for high-risk applications such as cancer diagnosis and risk assessment in several diseases using imaging informatics.

Biography: Lee Cooper received a PhD in Electrical and Computer Engineering from Ohio State University in 2009. He was an Assistant Professor of Biomedical Informatics at Emory University prior to joining Northwestern in 2019. His lab develops machine-learning algorithms and software tools for analyzing histology imaging and genomic data. His research has been funded by the US National Institutes of Health including the NLM, NCI, NIBIB, NINDS, NIDDK, as well as industry sources.

Biography: Jayashree Kalpathy-Cramer is an Associate Professor of Radiology at MGH/Harvard Medical School who works at the intersection of computer science and medicine. She is an electrical engineer by training, having received a B.Tech in EE from IIT Bombay and a PhD in EE from Rensselaer Polytechnic Institute. She returned to academia after a number of years in the semiconductor industry with a research pivot towards healthcare. Her lab is currently focused on the applications of artificial intelligence in medicine. She is a Scientific Director at the MGH/BWH Center for Clinical Data Science and a Senior Scientist at the American College of Radiology Data Science Institute. She is a Deputy Editor for the Radiology-AI journal, a new journal from the Radiological Society of North America focused on the applications of AI in Radiology.

Biography: Thomas C. Booth is a Senior Lecturer in Neuroimaging in the School of Biomedical Engineering & Imaging Sciences at King’s College London, UK. He is also an Honorary Consultant Neuroradiologist at King’s College Hospital, London, UK. He first started to enjoy machine learning during his PhD at the University of Cambridge, UK. Here, his focus was on brain tumor treatment response assessment using brain tumor MRI structural images – something he continues to research many years later as he is reminded continuously how important neuro-oncology diagnostics are when presenting patients at the neuro-oncology multi-disciplinary team meetings in a busy London teaching hospital. He sits on the National Cancer Research Institute Brain Tumor Committee and the Royal College of Radiologists Academic Committee. He was an awardee of the inaugural Royal College of Radiologists Outstanding Researcher Award.