Michael Caiola, Ph.D., is a Senior Biomedical AI Engineer at Credence, where he helps set research direction across the firm's portfolio of health research programs. His work sits at the intersection of machine learning, neuroscience, and regulatory science, with a career-long focus on movement disorders and on building AI that clinicians can trust. Dr. Caiola earned his Ph.D. in Mathematics from Rensselaer Polytechnic Institute, where he modeled the circuit dynamics of Parkinson's disease, and completed a postdoctoral fellowship in experimental neuroscience at the Emory National Primate Research Center. At the FDA's Center for Devices and Radiological Health, he developed interpretable ML methods to detect traumatic brain injury and stroke from EEG and served as software lead and FDA co-lead for WearGait-PD, a multi-site wearable-sensor study of Parkinson's gait. He has also served as an AI subject-matter expert in the national security sector, establishing rigorous methodologies for AI test and evaluation. His current projects include interpretable, sensor-based gait analysis and multimodal data fusion for health applications.