Portrait of Zhang, Yang

Yang Zhang

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Our research can be summarized in two words: Matter and Machine. On the Matter side, Z lab studies far-from-equilibrium physics. They synergistically combine and push the boundaries of statistical and stochastic thermodynamic theories, accelerated molecular simulations, understandable AI/ML/DS methods, and neutron scattering experiments, with the goal of significantly extending our understanding of a wide range of long timescale phenomena and rare events. Particular emphasis is given to the physics and chemistry of liquids and complex fluids, especially at interfaces, driven away from equilibrium, or under extreme conditions. On the Machine side, leveraging their expertise in materials and modeling, his group advances the development of soft robots and human-compatible machines, swarm robots and collective intelligence, and robots in extreme environments, which can lead to immediate societal impact.

David Brang

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The Multisensory Perception Lab studies how information from one sensory system influences processing in other sensory systems, as well as how this information is integrated in the brain. Specifically, we investigate the mechanisms underlying basic auditory, visual, and tactile interactions, synesthesia, multisensory body image perception, and visual facilitation of speech perception. Our current research examines multisensory processes using a variety of techniques including psychophysical testing and illusions, fMRI and DTI, electrophysiological measures of neural activity (both EEG and iEEG), and lesion mapping in patients with brain tumors.

Our intracranial electroencephalography (iEEG/ECoG/sEEG) recordings are a unique resource that allow us to record neural activity directly from the human brain from clinically implanted electrodes in patients. These recordings are collected while patients perform the same auditory, visual, and tactile tasks that we use in our other behavioral and neuroimaging studies, but iEEG measures have millisecond temporal resolution as well as millimeter spatial precision, providing unparalleled information about the flow of neural activity in the brain.

Estéfan Garcia

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Prof. Garcia’s primary research interests are in the realm of granular materials and granular systems. Granular and particulate materials represent some of the most commonly manipulated materials in our society. A fundamental understanding of their behavior at the scale of individual grains or particles has wide-ranging benefits in several fields including civil engineering, geology, additive manufacturing, and planetary exploration. Prof. Garcia uses advanced numerical modeling techniques that can simulate large-strain behavior while also capturing directly the fundamental discontinuous nature of granular systems. His simulations rely on high-performance computing to simulate the interactions of millions of grains within a particle assemblage as the entire mass undergoes large-strain deformation due to phenomena such as earthquake surface fault rupture and trapdoor displacement. This approach allows us to model phenomena at the near-surface such as liquefaction or larger-scale phenomena such as tectonic deformations. The focus on individual particles elucidates the influence of depositional history and soil fabric on the deformation behavior of soils. This line of research advances understanding of how ground surface deformations can impact infrastructure and ultimately aims to improve the resiliency of infrastructure against geologic hazards.

X-ray tomography scan of an intact naturally deposited shoal sample with individual grains labelled and colorized.

Jeroen Ritsema

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My research involves planetary-scale seismology and geophysics with a focus on seismic imaging of Earth’s mantle, the interpretation of ground-motion recordings curated by IRIS, and the computation of seismic wave fields using spectral-element methods. Current research topics include seismic tomography, reflection seismology of the transition zone, wave attenuation, and earthquake rupture analysis.

Yasser Aboelkassem

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Prof. Aboelkassem’s laboratory uses stochastic multiscale computational models based on Brownian-Langevin dynamics principles to derive a coarse-graining model that can describe the cardiac thin-filament activation process during contraction. The model links atomistic molecular simulations of protein-protein interactions in the thin-filament regulatory unit to sarcomere-level activation dynamics. We first calculate the molecular interaction energy between tropomyosin and actin surface using Brownian dynamics simulations. This energy profile is then generalized to account for the observed tropomyosin transitions between its regulatory stable states. The generalized energy landscape then served as a basis for developing a filament-scale model using Langevin dynamics.

A Stochastic Multiscale Model of Cardiac Thin Filament Activation Using Brownian-Langevin Dynamics

Zhenguang Huang

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Dr. Zhenguang Huang is an assistant research scientist in the department of Climate and Space Sciences and Engineering. His research focus is on 3-D global five- and six-moment multi-fluid simulations, and 3-D global multi-ion MHD simulations of the space plasma. He is also one of the main developers of the Block-Adaptive-Tree-Solarwind-Roe-Upwind-Scheme (BATSRUS) and the Space Weather Modeling Framework (SWMF).

Wenhao Sun

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Dr. Sun’s research group is interested in resolving outstanding fundamental scientific problems that impede the computational materials design process. The group uses high-throughput density functional theory, applied thermodynamics, and materials informatics to deepen our fundamental understanding of synthesis-structure-property relationships, while exploring new chemical spaces for functional technological materials. These research interests are driven by the practical goal of the U.S. Materials Genome Initiative to accelerate materials discovery, but whose resolution requires basic fundamental research in synthesis science, inorganic chemistry, and materials thermodynamics.

Lulu Zhao

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Dr. Lulu Zhao is an assistant research scientist in the Climate and Space Sciences and Engineering. Her research focus is the modelling of the acceleration and transport of energetic particles using M-FLAMPA (multiple-field-line-advection-model with particle acceleration). The M-FLAMPA model extract magnetic field lines from the magnetohydrodynamics (MHD) simulations of the background solar wind solution through SWMF (space weather frame work). Along those magnetic field lines, the particle transport and acceleration are modelled by solving the particle transport equations.


Kathryn Luker

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As an expert in molecular imaging of single cell signaling in cancer, I develop integrated systems of molecular, cellular, optical, and custom image processing tools to extract rich data sets for biochemical and behavioral functions in living cells over minutes to days. Data sets composed of thousands to millions of cells enable us to develop predictive models of cellular function through a variety of computational approaches, including ODE, ABM, and IRL modeling.

Walter Mebane

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My primary project, election forensics, concerns using statistical analysis to try to determine whether election results are accurate. Election forensics methods use data about voters and votes that are as highly disaggregated as possible. Typically this means polling station (precinct) data, sometimes ballot box data. Data can comprises hundreds of thousands or millions of observations. Geographic information is used, with geographic structure being relevant. Estimation involves complex statistical models. Frontiers include: distinguishing frauds from effects of strategic behavior; estimating frauds probabilities for individual observations (e.g., polling stations); adjoining nonvoting data such as from in-person election observations.