The College of Engineering and Computing (CEC) 3-Minute Thesis (3MT) competition challenges graduate students to present their research concisely and compellingly to a non-specialist audience within three minutes. Paras Parani participated in this prestigious competition, showcasing his innovative research on utilizing Large Language Models (LLMs) and Vision Transformers (ViTs) for epileptic seizure prediction. His latest findings demonstrate the potential of transformer-based architectures to achieve significant accuracy while maintaining computational efficiency for real-time applications. Out of 13 participants, Paras was selected among the top two and has been nominated by the college to represent CEC at the university-wide competition in January.