Dr. Antonio Bolufé-Röhler is an Associate Professor at the University of Prince Edward Island, specializing in machine learning, metaheuristics, and global optimization. His research explores the integration of data-driven learning with heuristic search, with contributions spanning reinforcement learning-based hybrids, surrogate-assisted strategies, and adaptive parameter control. He has co-authored numerous works on evolutionary computation, algorithm configuration, and high-dimensional optimization, with applications in bio-informatics and logistics. Dr. Bolufé-Röhler is particularly focused on developing intelligent optimization frameworks that balance theoretical foundations with practical deployment across real-world problem domains.

Dr. Dania Tamayo-Vera is an Assistant Professor at the University of Prince Edward Island, where she specializes in machine learning, optimization, and explainable artificial intelligence (XAI). Her research focuses on developing trustworthy and interpretable ML systems through multi-objective model selection, explanation stability metrics, and optimization-driven interpretability. She has also contributed to applied domains such as sustainable agriculture and atmospheric modeling. Dr. Tamayo-Vera is particularly interested in bridging the gap between high-performance algorithm design and actionable, stakeholder-aligned explanations for real-world decision-making.