Thermal imagery captured in the Long Wave Infrared (LWIR) spectrum has long-played a vital role in thermal physiology. Signs of stress and inflammation which are unseen in the visible spectrum, can be detected in LWIR due to principles of blackbody radiation. As a result, thermal facial imagery provides a unique modality for physiological assessment of states such as chronic pain. In this presentation, I will provide a presentation of my research into image registration to align visible-thermal images that serve as a prerequisite for image- to-image translation using conditional GANs and Diffusion Models. I will share recent work leading research with the National Institutes of Health applying this research in a real-world setting on cancer patients suffering from chronic pain.

Dr. Catherine Ordun is a Vice President at Booz Allen Hamilton, leading AI Rapid Prototyping and Tech Transfer solutions for mission-critical problems for the Federal Government. She drives AI rapid prototyping to support mission-critical proof-of-concepts across multiple AI domains, in addition to AI tech transfer to support algorithm reuse and consumption. She also leads multimodal AI research supporting the National Cancer Institute for chronic cancer pain detection. Dr. Ordun is a Ph.D. graduate of the UMBC Department of Information Systems advised by Drs. Sanjay Purushotham and Edward Raff, and obtained her bachelors degree from Georgia Tech, masters from Emory, and an MBA from GWU Business School. She also has an appointment at UMBC as Adjunct Research Assistant Professor.