Matthias K. Gobbert

Medium Bio Sketch

Matthias K. Gobbert is Professor of Mathematics in the Department of Mathematics and Statistics at UMBC and an affiliate Professor in the Department of Computer Science and Electrical Engineering at UMBC. He earned his Ph.D. in Mathematics from Arizona State University in 1996. After one year as post-doc during the year on high performance computing at the Institute for Mathematics and its Applications at the University of Minnesota, he joined the faculty in the Department of Mathematics and Statistics at UMBC.

Dr. Gobbert's research interests include scientific and parallel computing, the numerical solution of partial differential equations, industrial mathematics, and most recently data science, typically in collaboration with application scientists. Dr. Gobbert has a particular track record in the life sciences, with collaborations ranging from numerical simulations of chemically reacting flows in a heart cell to artificial intelligence applied to image reconstruction in cancer treatment. These projects all require the use of high-performance computing as indispensable tool to perform the simulations necessary to draw conclusions for the application areas.

Dr. Gobbert has extensive experience in initiatives. He co-founded the Center for Interdisciplinary Research and Consulting ( in 2003, initiated the UMBC High Performance Computing Facility ( in 2008 with funding from the NSF MRI program (three awards totaling over $1.5M including cost-sharing), directed the REU Site: Interdisciplinary Program in High Performance Computing ( from 2010 to 2017 with funding from NSF, NSA, and DOD (totaling nearly $2.0M), was senior personnel and project mentor in the NSF-funded Interdisciplinary Training for Undergraduates in Biological and Mathematical Sciences program at UMBC (, was co-PI of the NSF initiative CyberTraining: Big Data + HPC + Atmospheric Physics at UMBC (, and is now co-PI and co-director of the REU Site: Online Interdisciplinary Big Data Analytics in Science and Engineering ( Dr. Gobbert also initiated both the departmental and the university partnerships with the University of Kassel in Kassel, Germany.

Dr. Gobbert has been involved with over 200 publications, including over 40 in peer-reviewed journals, 40 in refereed proceedings, and 40 student publications and theses. The journals range from top-tier journals such as the SIAM Journal on Scientific Computing and the Journal of Computational Physics to student publications in high-profile undergraduate research journals such as the UMBC Review and the SIAM Undergraduate Research Online (SIURO).

Dr. Gobbert has to date graduated six Ph.D. students, five M.S. students, and has supervised eleven undergraduate theses for graduating with departmental honors. He is currently working with two Ph.D. students and one undergraduate student and has an extensive track record of involving students of all levels in publications.

Dr. Gobbert has accumulated extensive experience in teaching with state-of-the-art technology. Since participating in the first cohort in the Alternative Delivery Program (ADP) in 2006, he uses hand-writing on tablet laptops for all lectures. These lectures are taped and hosted online for streaming, with the added benefits of allowing for pausing, rewinding, and reviewing. Using the taped lectures for contents delivery, Dr. Gobbert uses a team-based active-learning teaching model, in which students work on problems in learning groups during class. Since 2019, his classes use online comprehension quizzes on the lectures and fully online submission of all assignments, complete with online grading. Since starting online teaching full-time in 2020, the synchronous class meetings are used additionally for student presentations to maximize active student engagement. For the work with a large number of students who were not his own thesis students, Dr. Gobbert received the University System of Maryland Board of Regents' Faculty Award for Excellence in Mentoring in 2010.

For complete details, see his Curriculum Vitae (CV).


All comments on this homepage and the information contained therein are greatly appreciated!
Again, my e-mail address is

Copyright © 2020-2021 by Matthias K. Gobbert. All Rights Reserved.
This page version 1.0, March 2021.