Faculty Mentors

Ekaterina Rapinchuk

Dr. Ekaterina Rapinchuk is an assistant professor in the math and CMSE departments, whose research focuses on semi-supervised learning, unsupervised learning and image processing. Applications of her research include classification of high-dimensional data, such as hyperspectral data, and segmentation of images, such as grain images in materials science.

Website

Research Project


Liz Munch & Dan Chitwood

Assistant Professor, Department of Computational Mathematics, Science and Engineering; Department of Mathematics

Dr. Liz Munch’s research program focuses in Applied Topology and Topological Data Analysis. Dr. Dan Chitwood’s training is in plant biology, and his research studies the plant form using X-ray Computed Tomography methods. Together, Drs. Munch and Dr. Chitwood are quantifying patterns, architectures, shapes, and forms in the natural world using Topological Data Analysis, applied to volumetric images created using X-ray CT technology.

Munch Website | Chitwood Website 

Research Project


Tong Gao

Assistant Professor,  Department of Computational Mathematics, Science and Engineering; Department of Mechanical Engineering

Dr. Gao is interested in fluid-structure interactions in both passive and active biological and synthetic systems.  He also integrates and develops ad-hoc numerical and theoretical tools to resolve the complex dynamics in fluid/solid systems from discrete particle simulations to continuum models.

Website

Research project


Min Chen

Assistant Professor, Department of Computational Mathematics, Science and Engineering; Department of Earth and Environmental Sciences

Min Chen is a computational seismologist. Her research interests lie in developing and applying numerical tools, harnessing 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.

Website

Research project


Adam Alessio

Adam Alessio’s lab focuses on several translational medical research projects including machine learning for quantitative diagnostics, cardiac perfusion estimation, quantitative PET imaging, radiation dose optimization, and system modeling. 

Website

Research project


Alexei Bazavov

Assistant Professor, Department of Computational Mathematics, Science and Engineering; Department of Physics and Astronomy

Dr. Alexei Bazavov is interested in solving problems in high-energy and nuclear physics that are related to strong interactions. The fundamental theory, called Quantum Chromodynamics, cannot (yet) be solved analytically, however, a lot of progress has been achieved by applying numerical methods. In practice, his work involves the following concepts and tools: Markov Chain Monte Carlo methods, numerical linear algebra, parallel programming, statistical data analysis and many more.

Website

Research project


Shinhan Shiu

Shinhan Shiu's group focuses on computational and evolutionary biology. Core questions addressed by his group focus on which genomic regions are functional, how molecular functions of genes can be predicted, and how to use genotype information to predict phenotype.

Website

Research project


Angela Wilson

Angela Wilson is a theoretical physical chemist with interests in the development and understanding of computational quantum mechanics methodologies, and studies in heavy element chemistry, catalysis, protein modeling, drug design/understanding of disease, metal organic frameworks, green chemistry, and many other areas. One of the great features of theoretical and computational chemistry is that they can be utilized to investigate a broad array of challenges, and the Wilson research group is engaged in areas as diverse as method development and studies of diatomic molecules to protein modeling and studies of the mechanical properties of materials.

Website

Research project


Jason Bazil

The Bazil lab uses dynamical models to study physiological systems with a focus on cardiac (heart) energetics. These models are built using mass action and enzyme kinetics to describe and characterize the molecular processes that govern cardiac tissue response to injury. The level of detail of our models spans from the biophysical behavior of single enzymes to entire metabolic networks.

Website

Research Project


Brian O'Shea

Brian O'Shea is a computational astrophysicist whose research focuses on the study of galaxy formation, astrophysical plasmas, and algorithms for massively parallel and high performance computing. He is also one of the lead developers of the Enzo community code (https://enzo-projec.org).

Website

Research Project