Yin Lu (Julie) Young is a Professor in the department of Naval Architecture and Marine Engineering. Her research focuses on the dynamic fluid-structure interaction response and stability of smart/adaptive multi-functional marine structures such as marine propulsors, turbines and control surfaces. One of her research focus is the fluid-structure interaction response and stability of marine and coastal structures. She is the current director of the Aaron Friedman Marine Hydrodynamics Laboratory. Her research has been supported by the Office of Naval Research (ONR), the Naval Surface Warfare Center (NSWC), and the National Science Foundation (NSF).
Shasha Zou is an Associate Professor of Climate and Space Science and Engineering. Her general research interest is about studying the dynamic interaction between the Sun’s extended atmosphere, i.e., solar wind, and the near-Earth space environment. In particular, she is interested in the physical processes of formation and evolution of ionospheric structures and their impact on technology, such as global navigation and communication satellite system (GNSS), during space weather disturbances using multi-instrument observations and numerical models. Numerical models often used include magnetohydrodynamic (MHD) model of the global magnetosphere, and physics-based global ionosphere and thermosphere model.
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.
Aaron Towne is an Assistant Professor in the Department of Mechanical Engineering. His research develops simple models that can be used to understand, predict, and control turbulent fluid dynamical systems. His approach focuses on identifying and modeling coherent flow structures, i.e., organized motions within otherwise chaotic flows. These structures provide building blocks for an improved theoretical understanding of turbulence and also contribute significantly to engineering quantities of interest such as drag, heat transfer, and noise emission. Consequently, strategically manipulating coherent structures can potentially lead to vast performance improvements in a wide range of engineering applications. Realizing this potential requires new data mining and analysis methods that can be used to identify and extract these organized motions from the large data sets produced by high fidelity simulations and experiments, as well as new theoretical and computational approaches for modeling and controlling them. Aaron’s research focuses on developing these tools for turbulent flow applications, while also contributing more broadly to the emerging areas of large-scale data mining and machine learning.
Yulin Pan is an Assistant Professor in the department of Naval Architecture & Marine Engineering. He received his Ph.D. in mechanical and ocean engineering from MIT in 2016, with a minor in mathematics. His research is primarily concerned with theoretical and computational hydrodynamics, with applications in ocean engineering and science. He has made original contributions in nonlinear ocean wave mechanics, tidal flows, propeller and bio-inspired foil propulsion. Alongside research, he is also an active writer on popular science of fluid mechanics. His active research topics include:
- Theoretical, computational and experimental investigations to understand the fundamental physics of wave turbulence
- Prediction and understanding of nonlinear ocean and coastal wave phenomenon
- Response of ships and offshore structures in wave field
- Development of computation and optimization methods for propellers and flapping foils
- Propagation of internal waves/tides at geophysical scales
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.
Dr. Mariana Carrasco-Teja received her PhD from the Mathematics Department at the University of British Columbia (UBC) (Vancouver, BC). She was part of the Institute of Applied Mathematics (UBC), an institute established to enhance interdisciplinary teaching and research using applied mathematics as a common language between engineers and scientists. Her dissertation involved modeling and simulating the primary cementing of oil and gas wells, a crucial step to ensure a safe and efficient extraction of oil and gas. After receiving her PhD, she continued her work as a postdoctoral fellow at the Complex Fluids Laboratory in UBC until she moved to Ann Arbor to join the Department of Chemical Engineering at the University of Michigan. Since becoming a member of the Cell Adhesion and Drug Delivery Laboratory, she’s had a chance to work closely with bioengineers while applying her modeling skills into optimizing vascular-targeted drug micro- and nano-carriers.
She was named MICDE Assistant Director in July 2015, and MICDE Associate Director in September 2019.
Dr. Maki works in the field of fluid mechanics, and his central focus is on developing algorithms for numerical computation of high-Reynolds number external flows that contain an air-water interface. Research interests include investigating free-surface hydrodynamics for analysis and design of high-performance naval craft and renewable-energy devices. Theoretical effort is focused on accurate description of the flow about marine vessels. Numerical research employs finite-volume and boundary element techniques to solve equations appropriate to govern the performance of ships maneuvering in waves, and energy devices and structures that operate in the ocean.
His research group develops fast and scalable algorithms for solving differential and integral equations on complex moving geometries. Application areas of current interest include large-scale simulations of blood flow through arbitrary confined geometries, electrohydrodynamics of soft particles and heat flow on time-varying domains.
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.