Mark Hauschild

Mark Hauschild is an Associate Professor in the Department of Computer Science within the College of Arts and Sciences at the University of Missouri-St. Louis. He holds a Ph.D. in Applied Mathematics from the University of Missouri-St. Louis, awarded in 2013, and maintains active teaching responsibilities with documented office hours for Spring 2025.

His educational background includes:

• Ph.D. in Applied Mathematics, University of Missouri-St. Louis, 2013

Dr. Hauschild's research centers on evolutionary computation, with particular emphasis on estimation of distribution algorithms (EDAs), genetic algorithms, and Bayesian optimization techniques. His work investigates how prior knowledge and transfer learning can enhance evolutionary algorithm performance, especially for complex decomposable problems requiring sophisticated linkage modeling.

Analysis of his publication history reveals a strong theoretical focus on model-directed optimization frameworks, where distance-based bias mechanisms and hierarchical structures consistently improve solution quality across NK landscapes and deceptive problem domains. His methodological innovations bridge probabilistic modeling with evolutionary search paradigms.

No scientific awards or major honors are documented in available sources.

While his teaching responsibilities are evident through scheduled office hours, specific details regarding graduate student advising, research grants, or laboratory direction are not provided in current documentation.

His research activities show no explicit affiliation with dedicated laboratories or collaborative research teams in the available institutional records.