Shayan Shams, Ph.D. is an Assistant Professor at UTHealth School of Biomedical Informatics (SBMI) and a member of the Center for Secure Artificial intelligence For hEalthcare (SAFE).

Dr. Shams' primary research interests are  1) Artificial Intelligence (AI), and unsupervised and semi-supervised deep learning and machine learning in computer vision with applications in healthcare, 2) statistical analysis of complex data especially within the area of healthcare, and 3) big data, High-Performance Computing (HPC), distributed computing and hardware accelerator devices (GPU, FPGA) programming.

As an expert in data science and big data, Dr. Shams is interested in the integration of AI, HPC and big data techniques to develop actionable health care models, bringing AI models to edge devices for personalized medicine, telemedicine, and telerehabilitation. His extensive experience and background in deep learning and machine learning with expertise in unsupervised, semi-supervised, and transfer learning has led to the development of AI models in various domains from Radiology, Pathology, Biology to Social Sciences.

Education & Training

PhD, Computer Science

Louisiana State University

MEng, Robotic and Mechatronics

University of Malaya

BS, Electrical Engineering,

Sadjad University of Technology

Artificial Intelligence

Deep Learning & Machine Learning

Big Data

Edge and High-Performance Computing