Hermann Eberl

Education and Employment Background

Dr. Eberl received his PhD from the Technical University of Munich, Germany in 1998. He joined the department of Mathematics and Statistics at University of Guelph in 2003 as an Assistant Professor and SHARCNET research chair in Biological Modelling. From 2006 to 2016, Eberl held a Tier-II Canada Research Chair in Computational Biomathematics. He is now a full Professor.

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Research Themes

Eberl’s research is broadly focused on Mathematical Biology and Engineering. His application-driven work focuses on modeling analysis and computer simulation of biological and bio/environmental engineering systems. It involves ordinary or partial differential equations, numerical analysis and scientific computing, and mathematical modelling. Current areas of research include:

1. Mathematical modelling of biofilm structures. Biofilms are cells that are immobilized in an organic polymer matrix of microbial origin. Biofilm researchers are challenged in understanding the relationships between physical, chemical, and biological processes that occur at different spatial and temporal scales. It is apparent that there is a wide variety of biofilm structures, and that these can be impacted by physical and biological factors. Eberl and his team are exploring mathematical models to describe biofilm structure and are experimentally examining how different aspects influence biofilm structure.
2. Anaerobic digestion models. Eberl is also interested in applying mathematical modelling towards understanding microbial communities in the human colon to better understand digestion. Eberl and his team explore the transport, exchange, and metabolic process that occurs within the microbial community in the human colon.
3. Chemostat models. Eberl’s team is also actively exploring mathematical models of bacterial populations in a chemostat setting, which accounts for thermodynamic growth inhibition due to chemical reactions. The team is using elementary mathematical and chemical arguments to explore different kinds of systems.
4. Honeybee disease models. Honeybees are highly social and live in organized, cooperative colonies, with distinct divisions of labour. Honeybee colonies are threatened due to disease pathogens but understanding disease dynamics within the complex colonies is difficult to do in a field setting. Thus, Eberl and his team have leveraged mathematical models and computer simulations to understand the disease dynamics within honeybee colonies, which will help inform effective remediation methods that will help save these important pollinators.

Highlights

• University of Guelph College of Engineering and Physical Sciences, Excellence in Graduate Supervision Award, 2019
• Section Editor Mathematics, Heliyon, 2015-present
• Editorial Board Member, Mathematical and Bioscience and Engineering, 2015-present
• Guest Editor, European Journal of Applied Mathematics, 2018
• Tier II Canada Research Chair, Computational Biomathematics, 2006-2016

Media Coverage

Honeybee disease models

• U of G, College of Engineering and Physical Sciences: Buzzworthy Math
• Greenhouse Canada: U of G using math to study bees
• CEPS Alumni News: Don’t Worry, Bee Happy