David Hiebeler

David Hiebeler brings a wealth of experience in applied mathematics and computational sciences to his role as a faculty member in the Department of Data Science and Engineering at the University of Maine. With a robust academic background, he earned his Ph.D. in Applied Mathematics from Cornell University, an M.S. in Applied Mathematics from Harvard University, and a B.S. in Computer Science from Rensselaer Polytechnic Institute. Dr. Hiebeler's research is deeply rooted in the exploration of mathematical population ecology and epidemiology. His work often involves the use of computational and mathematical stochastic spatial models to understand complex biological and ecological systems. His interest in cellular automata and complex adaptive systems reflects his commitment to advancing knowledge in these dynamic fields. Throughout his career, Dr. Hiebeler has contributed significantly to the understanding of how populations interact and evolve over time, particularly in the context of ecological and epidemiological systems. His research often bridges the gap between theoretical models and real-world applications, providing insights that are valuable to both the scientific community and policy makers. In addition to his research, Dr. Hiebeler is dedicated to teaching and mentoring students, helping to cultivate the next generation of data scientists and engineers. His courses often emphasize the importance of integrating mathematical theory with practical applications, preparing students to tackle complex challenges in their future careers. Dr. Hiebeler's work has been published in numerous academic journals, and he frequently presents his findings at international conferences. His contributions to the field have been recognized by his peers, and he continues to be an influential figure in the study of mathematical and computational approaches to ecological and epidemiological problems.