Daniel Forger is a Professor in the Department of Mathematics. He is devoted to understanding biological clocks. He uses techniques from many fields, including computer simulation, detailed mathematical modeling and mathematical analysis, to understand biological timekeeping. His research aims to generate predictions that can be experimentally verified.
Professor Grosh research spans various aspects of structural acoustics, mechanics, biomechanics and linear/nonlinear vibrations. Current research involves Cochlear mechanics (experiments and modeling of the mechanics of soft tissue and tissue growth), electroacoustic transducers, and computational and analytic methods for solving interior viscous fluid-structure interaction problems.
Professor Qi’s research fields are investigations of the mechanical and chemical properties of materials by applying theoretical and computational tools, including first-principles calculations, atomistic simulations and multiscale modeling. His major research interests are quantitative understanding of the intrinsic electronic/atomistic mechanisms for the mechanical deformation, phase transformation and chemical degradation (corrosion/oxidation) of advanced alloys and other structural/functional materials. Currently he is focusing on the studies of deformation defects and interfaces in materials under extreme conditions, such as high stress and/or chemically active environment, where the materials behaviors and properties can be dramatically different than those predicted by classical theories and models. He is also developing the numerical methods to integrate these electronic/atomistic results with large-scale simulations and experimental characterizations in order to design materials with improved mechanical performances and chemical stabilities.
Michael Cafarella is an Associate Professor in the Department of Electrical Engineering and Computer Science, Computer Science Division. He was appointed the Morris Wellman Faculty Development Assistant Professor of Computer Science and Engineering, and a Sloan Research Fellow (2016). Prof. Cafarella studies databases, information extraction, data integration, and data mining. His projects span several areas of data management including systems and algorithms for “messy” data management, novel data-intensive applications, and data systems infrastructure.
Eric Michielssen is the Louise Ganiard Johnson Professor of Electrical Engineering and Computer Science – Electrical and Computer Engineering Division.
His research interests include all aspects of theoretical, applied, and computational electromagnetics, with emphasis on the development of fast (primarily) integral-equation-based techniques for analyzing electromagnetic phenomena. His group studies fast multipole methods for analyzing static and high frequency electronic and optical devices, fast direct solvers for scattering analysis, and butterfly algorithms for compressing matrices that arise in the integral equation solution of large-scale electromagnetic problems.
Furthermore, the group works on plane-wave-time-domain algorithms that extend fast multipole concepts to the time domain, and develop time-domain versions of pre-corrected FFT/adaptive integral methods. Collectively, these algorithms allow the integral equation analysis of time-harmonic and transient electromagnetic phenomena in large-scale linear and nonlinear surface scatterers, antennas, and circuits.
Recently, the group developed powerful Calderon multiplicative preconditioners for accelerating time domain integral equation solvers applied to the analysis of multiscale phenomena, and used the above analysis techniques to develop new closed-loop and multi-objective optimization tools for synthesizing electromagnetic devices, as well as to assist in uncertainty quantification studies relating to electromagnetic compatibility and bioelectromagnetic problems.
Barzan Mozafari is an Associate Professor of Electrical Engineering and Computer Science at the University of Michigan (Ann Arbor), where he is a member of the Michigan Database Group and the Software Systems Lab. Prior to that, he was a postdoctoral associate at Massachusetts Institute of Technology. He earned his Ph.D. in Computer Science from the University of California at Los Angeles. He is passionate about building large-scale data-intensive systems, with a particular interest in database-as-a-service clouds, distributed systems, and crowdsourcing. In his research, he draws on advanced mathematical models to deliver practical database solutions. He has won several awards and fellowships, including SIGMOD 2012 and EuroSys 2013’s best paper awards.
His major current project is the creation an new third-order accurate CFD method called the Active Flux method, with many original features, sponsored by NASA under the Revolutionary Computational Aerodynamics program. Linked with this is joint work with Chris Fidkowski on entropy-based mesh adaptation. Another current interest is the design of improved Lagrangian hydrocodes that avoid “mesh imprinting” by emphasis on symmetry properties of the discretization, including the preservation of discrete vorticity.
Most of his research and teaching involves parallel computing of some form: design of scalable algorithms and data structures; applications to numerous scientific problems such as a large multidisciplinary team modeling space weather or a small interdisciplinary group doing imputation on datasets of social preferences; and performance analysis, both experimental and analytical. These projects have used a variety of computer architectures, ranging from tens to hundreds of thousands of cores. He also works on algorithms for abstract fine-grain parallel computer models motivated by concerns such as time/number-of-processors/peak-power tradeoffs and the constraints imposed by the fact that computation is done in 2- or 3-dimensional space. Further, he develops serial algorithms for optimizing adaptive sampling problems such as adaptive clinical trials, algorithms for isotonic regression, and various other computer science problems.
Divakar Viswanath is a Professor in the Department of Mathematics. His research is at the interface of scientific computation and nonlinear dynamics. The incompressible Navier-Stokes equations are a major point of current interest. Turbulent dynamics is locally unstable and bounded in phase space. In such scenarios, dynamical systems theory predicts the existence of periodic solutions (modulo symmetries). Professor Viswanath has developed algorithms to extract periodic solutions and traveling waves from turbulent dynamics. One goal of current research is to derive, implement, and demonstrate algorithms that simulate turbulent flows at higher Reynolds numbers than is currently possible. It appears that this goal will be met shortly. Professor Viswanath has a general interest in foundational numerical analysis ranging from interpolation theory to the solution of differential equations.
Professor Ziff carries out computational and theoretical studies of various physical problems, most notably percolation but also catalysis modeling and several reaction/diffusion systems. For percolation, he has developed various algorithms that have allowed substantial increases in performance, for the study of threshold behavior, crossing probability, etc. He also studies algorithms for efficiently simulating rare-event simulations such as chemical reactions and diffusion-limited aggregation.