Jui-Kai “Ray” Wang, Ph.D.

Jui-Kai (Ray) Wang, Ph.D., is an Assistant Professor in the Department of Ophthalmology. He joined UT Southwestern in 2024, bringing an interdisciplinary background in electrical and computer engineering, ocular image analysis, and ophthalmic research. Before joining UT Southwestern, Dr. Wang held research appointments in the Departments of Ophthalmology and Visual Sciences and Electrical and Computer Engineering at the University of Iowa and conducted research at the Center for the Prevention and Treatment of Visual Loss at the Iowa City VA Health Care System.

Dr. Wang received his Ph.D. in Electrical and Computer Engineering from the University of Iowa, where his dissertation focused on estimating papilledema severity using spectral-domain optical coherence tomography (OCT). In UT Southwestern, his laboratory develops machine learning and deep learning approaches to extract clinically meaningful information from ophthalmic imaging, including OCT, OCT angiography, laser speckle flowgraphy, color fundus photography, and visual fields. His work spans neuro-ophthalmology, glaucoma, retinal disease, and ocular oncology, with applications in disease detection, differential diagnosis, progression modeling, retinal structural and functional analysis, and multimodal imaging. A major focus of his research is developing interpretable artificial intelligence methods that characterize spatial patterns of retinal and optic nerve abnormalities rather than relying solely on conventional summary measurements.

Dr. Wang has an extensive publication record in ophthalmic imaging, artificial intelligence, and biomedical image analysis, with more than 50 peer-reviewed journal and full-length conference papers and more than 50 conference abstracts. His research has addressed a broad range of ophthalmic and neurologic conditions, including papilledema, optic neuritis, non-arteritic anterior ischemic optic neuropathy, glaucoma, age-related macular degeneration, diabetic retinopathy, traumatic brain injury, and ocular blood-flow abnormalities. His current work expands these efforts into multimodal retinal imaging and oculomics, with an emphasis on developing interpretable artificial intelligence methods that integrate information across imaging modalities. He is also applying machine learning and deep learning to ocular oncology, including the differentiation of choroidal melanoma from benign nevi and the noninvasive prediction of clinically important tumor characteristics.

Dr. Wang has served as principal investigator and co-investigator on research supported by UT Southwestern, the Department of Veterans Affairs, and the National Eye Institute. His honors include a 2025 UT Southwestern CTSA Pilot Grant and, as Co-PI, 2026 Hill Prizes Ad Hoc Funding for AI-guided research on lethal ocular melanoma. He also serves on the editorial boards of Scientific Reports and Neuroretina and is actively involved in mentoring research engineers, graduate students, and medical students.