Matthias K. Gobbert

Matthias K. Gobbert is a Professor of Mathematics at the University of Maryland, Baltimore County (UMBC), affiliated with the Department of Mathematics and Statistics. His research focuses on scientific computing, parallel algorithms, machine learning, and numerical methods for applications in medicine, engineering, and biology. He has received the University System of Maryland Board of Regents' Faculty Award for Excellence in Mentoring in 2010.

Education:

• Ph.D. in Mathematics, Arizona State University (1996)
• Postdoctoral Associate at the University of Minnesota’s Institute for Mathematics and its Applications (1996–1997)

Research Interests:

• Parallel computing for large-scale simulations
• Multiscale modeling of chemically reactive flows
• Numerical methods for partial differential equations
• Applications in medical physics (e.g., proton therapy, prompt gamma imaging)
• Machine learning for big data in science and engineering

Teaching:

• Develops courses using flipped classrooms, active learning, and technology integration (e.g., tablet laptops, Blackboard)
• Teaches Math 441 (Numerical Analysis), Math 447/627 (Parallel Computing), and software-focused courses like Math 426 (MATLAB).
• Incorporates entrepreneurship training into curricula, linking computational methods to commercialization opportunities.

Grants & Collaborations:

• Co-director of NSF-funded CyberTraining: Big Data + HPC + Atmospheric Physics.
• International collaborations with the University of Kassel (Germany) on parallel computing and HPC.
• Advisor to REU programs in big data analytics and high-performance computing.

Labs & Teams:

• UMBC High Performance Computing Facility (HPCF)
• Center for Interdisciplinary Research and Consulting (CIRC)