Saman Khamesian

I am a Ph.D. researcher at Arizona State University, specializing in Artificial Intelligence for health applications. As a Graduate Research Assistant in the EMIL Lab under Dr. Hassan Ghasemzadeh, I focus on developing machine learning systems for Type 1 diabetes management, including personalized glucose forecasting and decision-support tools for insulin delivery.

I lead the development of GLIMMER, a modular prediction framework with a custom loss function for prioritizing safety during glycemic events. I am also building a reinforcement learning framework for adaptive therapy planning. In collaboration with Mayo Clinic Arizona, I co-developed ExActHealth, a mobile and wearable-based app for real-time food and activity tracking, validated in a pilot study with T1D participants.

My academic background includes a master’s degree in Artificial Intelligence and a bachelor’s degree in Computer Engineering from Shahid Beheshti University in Tehran, Iran. Before my Ph.D., I worked as a Machine Learning Engineer at Mofid Securities, where I developed predictive models and spoof detection systems for financial applications.

With over five years of experience in Python, machine learning, and data-driven system design, I enjoy bridging research and real-world impact. I’m currently collaborating with researchers at the University of Texas at Austin on reinforcement learning projects aimed at behavior change and long-term health improvement.