Martina Cotena, PhD, is a clinical studies specialist with expertise in artificial intelligence, nanoscience, human reproduction, and infertility. She holds a master's degree in biology from Università degli Studi di Napoli Federico II, followed by a PhD from Aix-Marseille Université, France, where her research focused on the effects of nanomaterials and pollutants on reproductive health. This work earned her the Prix de Thèse in 2022 from the Société Française de Toxicologie.
In addition to her academic success, Martina has worked as a clinical affairs consultant and clinical studies specialist engineer, contributing to the launch of AI-powered medical devices. Her skillset includes research protocol development, clinical study coordination, and collaboration with key opinion leaders (KOLs). She is also an accomplished communicator, having published extensively and presented at international conferences. Fluent in Italian, Spanish, French, and English, Martina is passionate about interdisciplinary collaboration, teaching, and scientific outreach.
Brent D. Weinberg is a neuroradiologist. He holds a bachelor’s degree in engineering science from the University of Tennessee (1997–2001). He then finished his combined MD/Ph.D. program at Case Western Reserve University (2001–2009). Brent D. Weinberg is now an associate professor and Division Director at the Department of Radiology and Imaging Sciences, Emory University School of Medicine. His research focuses on creating new cancer treatments and the imaging tools needed to assess them. He is also interested in other areas, including physician education and practice quality improvement.
Peter D. Chang is a co-director of the Center for Artificial Intelligence in Diagnostic Medicine (CAIDM), University of California Irvine, where he leads the healthcare AI curriculum that trains the next generation of physician scientists in understanding and developing cutting-edge AI tools. Peter D. Chang also serves as an associate professor for the Departments of Radiological Sciences and Computer Science at the same school. He graduated with an MD degree from the Northwestern University Feinberg School of Medicine. He then completed his residency training in diagnostic radiology at the Columbia University/New York Presbyterian Hospital and a fellowship in neuroradiology/T32 research at the University of California, San Francisco. His research interests include algorithm development, validation, clinical deployment, and standardizing and evaluating high-quality data sets (e.g., sourcing, annotation, curation, and quality requirements).
Daniel S. Chow is a director of Advanced Analytics and Artificial Intelligence (A3), a unit under the UCI Institute for Precision Health (IPH). He is also a co-director of the Center for Artificial Intelligence in Diagnostic Medicine (CAIDM). Daniel S. Chow holds his medical degree from the University of California, Los Angeles, David Geffen School of Medicine (2010). He completed his residency training in diagnostic radiology at Columbia University/New York Presbyterian Hospital (2015) and his fellowship in the Department of Radiology & Biomedical Imaging, University of California, San Francisco (2016). Moreover, in 2021, Daniel S. Chow obtained his MBA from the University of California, Irvine, Paul Merage School of Business. He now also serves as the section chief of the Division of Neuroradiology and the vice chair of innovation and entrepreneurship in the Department of Radiological Sciences at UCI Health. His research focuses on operationalizing new digital health technologies, including the use of artificial intelligence and advanced analytics for intracranial hemorrhage triage, brain tumor imaging evaluation and COVID-19.
