Dr. Shen is a professor in the department of computer & information science, the University of Michigan-Dearborn, USA. He is a fellow of ASME & IET, and the editor-in-chief of the International Journal of Modelling and Simulation (CiteScore 2018: 1.03), which is an EI-indexed, peer-reviewed research journal published through UK-based Taylor & Francis Group both in print and online. Professor Shen has published over 130 technical papers, 3 books, and organized many international conferences/workshops. His research areas include Modeling and Simulation, Machine Learning and Artificial Intelligence, Numerical Analysis and Optimization, Robotics, Data Science, Sensor Technology, Data Fusion, and Computational Materials Science. Dr. Shen is an innovator who is the creator of two software tools: (a) UM GeoModifier and (b) UM MatDiagnoser. He also contributed to the development of the well-known software OptiStruct.
Dr. Avestruz is a computational cosmologist. She uses simulations to model, predict, and interpret observed large-scale cosmic structures. Her primary focus is to understand the evolution of galaxy clusters. These are the most massive gravitationally collapsed structures in our universe, comprised of hundreds to thousands of galaxies. Other aspects of her work prepare for the next decade of observations, which will produce unprecedented volumes of data. In particular, she is leading software development efforts within the clusters working group of the Large Synoptic Survey Telescope to calibrate galaxy cluster masses from simulation data. Dr. Avestruz also incorporates big data methods, including machine learning, to extract gravitational lensing signatures that probe the mass distribution of massive galaxies and galaxy clusters.
Trachette L. Jackson is Full Professor in the Mathematics Department, who specializes in Computational Cancer Research or Mathematical Oncology. A focus of Dr. Jackson’s research has been achieving a unified understanding of how signaling molecules, cells, and micro-environmental structures coordinate to control blood vessel generation, morphology and functionality during tumor growth. Her work aims to biochemically and biomechanically characterize the collective motion vascular endothelial cells, one of most important cell types involved in cancer development due to their role in angiogenesis.
With an eye toward addressing critical challenges associated with targeted molecular therapeutics, for example determining which drugs are the best candidates for clinical trials, Dr. Jackson also develops multiscale mathematical models that are designed to optimize the use of targeted drug treatment strategies. These mathematical models connect the molecular events associated with tumor growth and angiogenesis with the temporal changes in tumor cell and endothelial cell proliferation, migration and survival, and link these dynamics to tumor growth, vascular composition, and therapeutic outcome.
Yue Fan is an Assistant Professor in the Department of Mechanical Engineering. The primary research interest in his group is to provide a substantive knowledge on the mechanics and micro-structural evolution in complex materials systems under extreme environments via predictive modeling. In particular, they focus on describing highly disordered systems (such as glasses, grain boundaries, etc) from the perspective of potential energy landscape (PEL), and correlating materials properties with their underlying PEL structures. The ultimate goal is to facilitate the development of new science-based high performance materials with novel functions and unprecedented strength, durability, and resistance to traditional degradation and failure.
Evgueni Filipov is an Assistant Professor in the Department of Civil and Environmental Engineering. His research interests lie in the field of deployable and reconfigurable structural systems. Folding and adaptable structures based on the principles of origami can have practical applications ranging in scale and discipline from biomedical robotics to deployable architecture.
His research is focused on developing computational tools that can simulate mechanical and multi-physical phenomena of deployable structures. The analytical models incorporate folding kinematics along with local and global phenomenological behaviors. Prof. Filipov uses finite element and constitutive modeling to better understand how geometry affects elastic deformations and other physical properties of the deployable and adaptable structures. He is interested in optimization of such systems and large scale parametric studies to explore the design space and potential applications of the systems.
Ricky Rood is a Professor of Climate and Space Sciences and Engineering. His current research and teaching focus is on climate change and its repercussions in society. His research history includes numerical modeling of trace constituents and atmospheric dynamics. He was director of NASA’s Center for Computational Science at Goddard Space Flight Center. He is currently consulting with NOAA on the Next Generation Global Prediction System.
Professor Rood is an active member of the climate science community, working on strategic approaches to the climate-change problem solving. He writes blogs for Wunderground.com and Climatepolicy.org and he is a main contributor of The Climate Workspace project, glisaclimate.org, a site that supports an online community of people working to address climate change questions and problems.
Ming Xu is an Associate Professor in the School for Environment and Sustainability, and in the Department of Civil and Environmental Engineering. The focus of his research is to understand the interaction between industrial systems and the biophysical environment. His goal is to provide an understanding of driving forces of environmental pressures and to help find an alternative pathway to reduce these pressures. Prof. Xu inherently interdisciplinary research combines data science, complex systems modeling and industrial ecology.
Heather Mayes is an Assistant Professor in the Department of Chemical Engineering. Her research group uses multi-scale modeling to discover protein-sugar interactions and to harness them for renewable energy and improved health. The study of carbohydrate-protein interactions is an important step to create renewable fuels and chemicals from non-food biomass, and the results can be applied to several human diseases, including cancer and autoimmune disorders. Prof. Mayes uses computational tools in her research, including quantum mechanics, molecular dynamics, and rare-event sampling methods. She collaborates with experimental groups to understand past and guide future wet-lab studies to advance renewable chemicals and fuels, as well as disease understanding.
Phani Motamarri is an Assistant Research Scientist in the department of Mechanical Engineering. His research interests lie in the broad scope of computational materials science with emphasis on computational nano-science leading to applications in the areas of mechanics of materials and energy. His research is strongly multidisciplinary, drawing ideas from applied mathematics, data science, quantum-mechanics, solid-mechanics, materials science and scientific computing.
The current research focus lies in developing systematically improvable real-space computational methodologies and associated mathematical techniques for conducting large-scale electronic-structure (ab-initio) calculations -via- density functional theory (DFT). Massively parallel and scalable numerical algorithms using finite-elements (DFT-FE) are developed as a part of this research effort, which enabled large-scale DFT calculations on tens of thousands of atoms for the first time using finite-element basis. These computational methods will aid fundamental studies on defects in materials, molecular and nanoscale systems which otherwise would have been difficult to study with the existing state of the art computational methods. Current areas of application include — (a) first-principles modelling of energetics of point defects and dislocations in Al, Mg and its alloys which are popular in light-weighting applications to provide useful inputs to meso-scale and continuum models, (b) providing all-electron DFT input to advanced electronic structure approaches like the GW method for accurate prediction of electronic properties in semiconductor-materials.