Shahriar Shahram is a PhD candidate in Electrical and Computer Engineering at the University of Central Florida, with a focus on control, optimization, and machine learning for networked vehicles. He is particularly interested in reinforcement learning and its applications in vehicular technology. Shahriar has led multiple projects, including collaborations with the Honda Research Institute, resulting in two patents and several publications. He aims to leverage his expertise as a Data Scientist to drive innovative solutions across various industries.

Shahriar holds an M.S. in Electrical Engineering from the University of Central Florida and a B.S. in Electrical Engineering from Sharif University of Technology. As a Research Assistant at UCF, he has contributed significantly to the field of vehicular communication technologies. In addition, Shahriar has served as a Teaching Assistant, developing course materials and supervising laboratory sessions. His technical skills include proficiency in MATLAB, Python, Java, and C, as well as experience with TensorFlow, PyTorch, CARLA, and ROS2. He is fluent in English and a native Farsi speaker.