Faculty Mentors
Jason Bazil
Assistant Professor, Department of Physiology
Our lab uses dynamical models to study physiological systems with a focus on cardiac energetics in both health and disease. Our models are built using mass action and enzyme kinetics to describe and characterize the molecular processes that govern cardiac tissue response to I/R injury. The level of detail of our models spans from the biophysical behavior of single enzymes to entire metabolic networks.
Research Project
jnbazil@msu.edu
Min Chen
Assistant Professor, Department of Earth & Envionmental Sciences
Department of Computational Mathematics, Science & Engineering
Min Chen is a computational seismologist. Her research interests lie in developing and applying numerical tools that harness the power of high performance computing for seismic full waveform inversion, imaging, and interpretation. Her research aims to better understand plate tectonic processes and earthquake rupture processes using high-resolution seismic images.
Research Project
chenmi22@msu.edu
Sean Couch
Assistant Professor, Department of Physics and Astronomy
Department of Computational Mathematics, Science & Engineering
Sean Couch is a theoretical astrophysicist specializing in the study of the core-collapse supernova mechanism using large-scale numerical simulation. His recent contributions include demonstrating the enormous impact multidimensional stellar progenitor structure has on the supernova mechanism and showing that turbulence is playing a crucial role in aiding successful explosions. Couch is also interested in massive stellar evolution, the origin of the elements, black hole accretion, gamma-ray bursts and radiative transfer. His simulations are run using hundreds of thousands of processing cores in parallel on the world’s fastest supercomputers.
Research Project
couch@pa.msu.edu
Alex Dickson
Assistant Professor, Department of Biochemistry & Molecular Biology
Department of Computational Mathematics, Science & Engineering
Drugs work by binding to molecular receptors in the cell, and achieve a pharmacological effect by altering the behavior of that receptor. Studying how drug binding affects a receptor at the molecular level is difficult, but can have direct impact on the design of new drugs to treat human disease. The Dickson Lab’s core research efforts are directed at studying drug binding pathways, and the effect of drug binding on protein dynamics and stability.
Research Project
alexrd@msu.edu
Tong Gao
Assistant Professor, Department of Mechanical Engineering
Department of Computational Mathematics, Science & Engineering
Our group works in diverse areas in fluid mechanics, biophysics and materials through modeling and simulation. We are particularly interested in fluid-structure interactions in both passive and active systems in the general category of soft matter.
Research Project
gaotong@egr.msu.edu
Matthew Hirn
Assistant Professor, Department of Mathematics
Department of Computational Mathematics, Science & Engineering
My research has a dual focus: The underlying mathematical theory of data science on one hand; and then leveraging this theory to develop state of art algorithms to enable breakthroughs in scientific domains (with particular emphasis on physics, chemistry, materials, and biology). As such, this work is necessarily a mix of theory and practice. A lot of my research is rooted in modern computational harmonic analysis, including interpolation theory, wavelets, and geometric analysis, and relating these concepts to high dimensional data analysis and machine learning.
Research Project
mhirn@msu.edu
Arjun Krishnan
Assistant Professor, Department of Biochemistry & Molecular Biology
Department of Computational Mathematics, Science & Engineering
We develop and apply computationally data-driven approaches for studying complex human traits and diseases. We use statistical models and machine learning algorithms to integrate large-scale multi-dimensional data to build relevant genome-wide models and predictions.
Research Project
arjun@msu.edu, jwang164@msu.edu
Michael Murillo
Professor, Department of Computational Mathematics, Science & Engineering
Our group is involved in the development and application of molecular dynamics of dense Coulomb systems. Our current application areas are ultracold plasmas (plasmas near absolute zero), dusty plasmas (plasmas that can form crystal lattices) and dense plasmas (plasmas that can create fusion energy). To achieve these goals, we develop a range of models and algorithms.
Research Project
murillom@msu.edu
Yue Qi
Associate Professor, Department of Chemical Engineering & Materials Science
Dr. Yue Qi has a PhD in Materials Science with a minor in Computer Science. She directs the Materials Simulation for Clean Energy (MSCE) Lab, where multi-scale simulations methods are developed to investigate materials used for batteries and fuel cells.
Research Project
yueqi@egr.msu.edu
Mark Reimers
Associate Professor, Neuroscience Program
The Reimers group develops methods to analyze and interpret the very large data sets (hundreds GB to TB range) now being generated in neuroscience, especially from the high-throughput technologies developed by the BRAIN initiative. We develop methods to recognize recurrent rapid patterns of brain activity among the fluctuations of a working brain. We work with about a dozen leading experimental labs across the US and around the world, and with MathWorks.
Research Project
reimersm@msu.edu
Jianrong Wang
Assistant Professor, Department of Computational Mathematics, Science & Engineering
We develop and apply computationally data-driven approaches for studying complex human traits and diseases. We use statistical models and machine learning algorithms to integrate large-scale multi-dimensional data to build relevant genome-wide models and predictions.
Research Project
jwang164@msu.edu, arjun@msu.edu
Hui-Chia Yu
Assistant Professor, Department of Chemical Engineering
Department of Computational Mathematics, Science & Engineering
My research focuses on simulating materials phenomena at the microstructure level of energy materials. These types of simulations involve solving coupled governing equations in complex geometries. The knowledge gained from simulations can facilitate us to develop a better design of energy materials.