William Hsu is a Professor of Radiological Sciences, Bioinformatics, and Bioengineering at the University of California, Los Angeles. He is a biomedical informatician focused on maximizing the utility of multimodal data to detect and treat cancers earlier. His lab harnesses artificial intelligence/machine learning techniques to integrate and transform multimodal data into actionable knowledge. He serves as principal investigator on grants from the National Institutes of Health, National Science Foundation, Agency for Healthcare Research and Quality, and the V Foundation. He is a deputy editor of Radiology: Artificial Intelligence. Pitt HexAI's podcast Jordan Gass-Poore' speaks with William about his career and interests, his work at UCLA, emerging applications of AI in radiology, advances in the field, explainable AI and interpretability, bioengineering and other subjects. For students interested in learning about imaging informatics training at UCLA, they can head over to https://mii.ucla.edu/training/ and https://mii.ucla.edu/applying-to-mii/.

Jason Fries is a research scientist with the Shah Lab at Stanford University. In this episode Jason speaks with Pitt HexAI’s podcast host Jordan Gass-Poore’ about his early interests in computational pathology and his current work at Stanford and interests in foundational models and data-centric AI. Jordan and Jason also discuss lab research papers, explainable AI, the DC-Check initiative and the lab's unique vantage point being based in the heart of Silicon Valley.

Sriraam Natarajan is a Professor of Computer Science and Director of the Center for Machine Learning at The University of Texas at Dallas. In this episode Dr. Natarajan speaks with Pitt HexAI’s podcast host Jordan Gass-Poore’ about his background and interests in artificial intelligence and machine learning with a focus on healthcare and biomedical applications. Sriraam and Jordan discuss work being carried out at the University of Texas, advice Dr. Natarajan commonly offers students, his being chosen to chair the Association for the Advancement of Artificial Intelligence’s upcoming AAAI-24 conference and his views on explainable AI.

Peter Shen is Vice President of Digital and Automation at Siemens Healthineers and an industry expert on medical imaging and artificial intelligence. In this episode Peter speaks with Jamie Gramz about vivo and in vitro diagnostic testing, the evolution of medical imaging and how X-ray, computed tomography and magnetic resonance imaging technologies work; real-world use cases of how AI is being used in healthcare today; the impact data quality has on enabling trustworthy AI, generalization and avoiding bias; the importance of integrating AI within workflows; the need for explainable AI and transparency through performance metrics; and the importance of close collaboration between industry, academia and providers to enable the evolution from acceptance to early adoption to routine use within the delivery of patient care.

Claudia von Vacano, the Executive Director of the D-Lab and the Digital Humanities at the University of California, Berkeley, speaks with Mythili Tirumalasetty about Berkeley’s new, forward looking College of Computing, Data Science and Society and about the D-Lab, it’s mission and its training initiatives supporting research in data intensive social sciences. Mythili and Claudia touch on Berkeley’s unique culture and how the D-Lab is keeping pace with explosive growth around generative AI and helping ensure researchers can overcome technical barriers to accelerate and improve their research projects leveraging artificial intelligence and machine learning including in the fields of health informatics and explainable AI.