Michigan Institute for Computational Discovery and Engineering

SC2 Machine Learning Collaborative Workshop
2017-11-03 18:00 - 19:00, 2017-10-27 18:00 - 19:00, 2017-10-20 18:00 - 19:00, 2017-10-13 18:00 - 19:00, 2017-10-06 18:00 - 19:00 (America/Detroit) | 1311 EECS, 1301 Beal Ave., Ann Arbor, MI, 48109, United States
Machine Learning (ML) has found it’s way into much of today’s computational landscape and is a powerful tool to extract meaning from the large amounts of data generated by high performance computing. The Scientific Computing Student Club (SC2) has organized this workshop for students, and all interested individuals, with the goal of learning existing ML tools that can be easily integrate in research workflow. Weekly meetings on Fridays @ 6:00 pm, except November 24, 2017. More information…

MICDE Seminar: Thomas Devereaux, Photon Science, Stanford University
2017-11-02 14:00 - 15:00 (America/Detroit) | 4448 East Hall, 530 Church St, Ann Arbor, MI, 48109, United States
Bio: Professor Devereaux received his Ph.D. in Physics from the University of Oregon in 1991, M.S. from University of Oregon in 1988, and B.S from New York University in 1986. Professor Devereaux is currently the Director of the Stanford Institute for Materials and Energy Sciences (SIMES), the Associate Lab Director (ALD) for Photon Science, a professor in the Photon Science Faculty at SLAC National Accelerator Laboratory and Stanford University and a Senior Fellow of the Precourt Institute for Energy. SIMES is a joint institute between Stanford main campus and SLAC, a national laboratory, focusing on scientific foundations related to the energy challenge facing our society. Professor Devereaux was a Post-doctoral Fellow at the Max Planck Institut, Stuttgart, (1991-1993), a Post-doctoral Fellow at the University of California, Davis, CA, (1993-1996), an Assistant Professor at The George Washington University, Washington, DC, (1996-1999), and an Associate Professor (1999-2006) and Professor (2006-2007) at the University of Waterloo, Waterloo, ON, Canada.
His main research interests lie in the areas of theoretical condensed matter physics and computational physics. His research effort focuses on using the tools of computational physics to understand quantum materials. Fortunately, we are poised in an excellent position as the speed and cost of computers have allowed us to tackle heretofore unaddressed problems involving interacting systems. The goal of his research is to understand electron dynamics via a combination of analytical theory and numerical simulations to provide insight into materials of relevance to energy science. His group carries out numerical simulations on SIMES’ high-performance supercomputer, the National Energy Research Scientific Computing Center (NERSC), and other US and Canadian computational facilities. The specific focus of the group is the development of numerical methods and theories of photon-based spectroscopies of strongly correlated materials.
Professor Devereaux’s awards include: U. S. Department of Education Fellowship (1989-1991); Junior Scholar Incentive Award, George Washington University (1998); Research Fellowship of the Alexander von Humboldt Foundation (2002-2006); Premier’s Research Excellence Award, Province of Ontario (2003); Scientist Research Fellowship, Embassy of France (2005); and Fellow of the American Physics Society (2008).
Light controlled topological phase transitions in multi-orbital and frustrated magnetic systems
Spurred by recent progress in melting, enhancement and induction of electronic order out of equilibrium, a tantalizing prospect concerns instead accessing transient Floquet steady states via broad pump pulses, to affect electronic properties. Here, we consider a two-pronged approach to manipulate the topology of a band insulator, as well as topological order in a Mott insulator. We first consider monolayer transition-metal dichalcogenides (TMDCs) [1], and show that their low-energy description as massive 2D relativistic fermions fails to hold for optical pumping. Instead, the added complexity of a realistic materials description leads to a novel mechanism to optically induce topologically-protected chiral edge modes, facilitating optically-switchable conduction channels that are insensitive to disorder. We develop a strategy to understand non-equilibrium Floquet-Bloch bands and topological transitions directly from ab initio calculations, and illustrate for the example of WS2 that control of chiral edge modes can be dictated solely from symmetry principles and is not qualitatively sensitive to microscopic materials details. Second, we extend these ideas to strongly correlated systems and show that pumping frustrated Mott insulators with circularly-polarized light can drive the effective spin system across a phase transition to a chiral spin liquid (CSL) [2]. We show that the transient time evolution of a Kagome lattice Hubbard model is well captured by an effective spin description, where circular polarization promotes a staggered scalar spin chirality Si . (Sj x Sk) directly to the Hamiltonian level. We fingerprint the ensuing phase diagram and find a stable photo-induced CSL in proximity to the equilibrium ground state. The results presented suggest new avenues to marry dynamical symmetry breaking, strong interactions, and ab initio materials modelling, to access elusive phase transitions that are not readily accessible in equilibrium.
References:
[1] M. Claassen et al, Nature Comm. 7, 13074 (2016).
[2] M. Claassen et al, arXiv:1611.07964, to appear in Nature Communications.
This is a joint CM Theory seminar. Prof. Devereaux is being hosted by Prof. Gull (Physics). If you are interested in meeting with him during his visit please send an email to mcteja@umich.edu

MICDE Seminar: Irina Tezaur, Extreme Scales Data Science and Analytics Department, Sandia National Laboratories
2017-10-25 15:00 - 16:00 (America/Detroit) | 1006 H.H. Dow, 2300 Hayward St, Ann Arbor, MI, 48109, United States
Bio: Dr. Irina Tezaur (f.k.a. Dr. Irina Kalashnikova) is a Principal Member of Technical Staff (PMTS) in the Extreme Scales Data Science & Analytics Department (Org. 8759) at Sandia National Laboratories in Livermore, CA. Prior to joining this group, from October 2011 to September 2014, she was SMTS in the Computational Mathematics Department (Org. 1442) at Sandia in Albuquerque, NM. She received her Ph.D. in Computational and Mathematical Engineering (CME) from Stanford University in 2011. Her advisor at Stanford was Professor Charbel Farhat and I was a member of the Farhat Research Group (FRG). Her Bachelors and Masters degrees are in pure mathematics, awarded by the University of Pennsylvania in 2006. Dr. Tezaur’s research interests are numerical solution to PDEs, mixed/hybrid finite element methods, stability and convergence properties of numerical methods, Reduced Order Modeling (ROM) and simulation-based analysis of fluid-structure interaction that she currently applies to climate modeling.
Next-generation modeling & simulation of large-scale ice sheets towards probabilistic sea-level change projections
Recent observations show that both the Greenland and Antarctic ice sheets are losing mass at increasingly rapid rates [1]. In its fourth assessment report (AR4), the Intergovernmental Panel on Climate Change (IPCC) declined to include estimates of future sea-level change from dynamics of the polar ice sheets due to the inability of ice sheet models to mimic or explain observed dynamic behaviors, such as the acceleration and thinning then occurring on several of Greenland’s large outlet glaciers [2]. In recent years, there has been a push to develop “next generation” land-ice models and codes for integration into global Earth System Models (ESMs). Unlike their predecessors, these codes: (1) are able to perform realistic, high-resolution, continental scale simulations, (2) are robust, efficient and scalable on next-generation hybrid systems (multi-core, many-core, GPU, Intel Xeon Phi), and (3) possess built-in advanced analysis capabilities (e.g., sensitivity analysis, optimization, uncertainty quantification). This talk will give an overview of the Albany/FELIX (Finite Elements for Land Ice eXperiments) [3] next-generation land-ice dynamical core (dycore) that is under development at Sandia National Laboratories as a part of a Department of Energy (DOE) SciDAC-funded project aimed at providing probabilistic sea-level projections from extreme-scale ice sheet and earth system models. This dycore is currently being integrated in to the DOE’s Acelerated Climate Model for Energy (ACME), which will be used to calculate anticipated 21st sea-level change projections, including uncertainty bounds. It is widely accepted that land-ice behaves like a very viscous, shear-thinning, non-Newtonian fluid, similar to lava flow. Typically, ice sheets are modeled using a quasi-static model in which a steady momentum-balance system for the ice velocities is coupled to dynamic equations for the ice thickness and temperature. The Albany/FELIX dycore is based on the so-called “First-Order Stokes” equations for the ice momentum balance [4], an attractive alternative to the more expensive “Full Stokes” model because of its reduced computational cost. Following an overview of our land-ice model and project, I will describe some of the algorithms and software we have developed as a part of this project that have contributed to our dycore’s robustness and scalability. These include: robust automatic-differentiation-based nonlinear solvers, scalable algebraic-multigrid-based iterative linear solvers [5], adaptive mesh refinement capabilities, and stable semi-implicit First-Order Stokes-thickness coupling methods. I will also discuss some of the advanced analysis capabilities in Albany/FELIX, namely a large-scale inversion approach we have developed for obtaining optimal ice initial conditions [6], our workflow towards quantifying uncertainties in land-ice models, and performance-portability of the Albany/FELIX code to new and emerging architectures using the Kokkos library [7]. I will show results which demonstrate that the Albany/FELIX dycore is scalable, fast and robust for production-scale land-ice problems on state-of-the-art HPC machines. I will also discuss results from a recent validation study in which Albany/FELIX was used to simulate the Greenland ice sheet during the period 1991-2013 with realistic climate forcing, and the simulation data were compared with observational data collected by NASA satellites [8].
This work was done in collaboration with Irina Demeshko, Mike Eldred, Matt Hoffman, John Jakeman, Mauro Perego, Steve Price, Andy Salinger, Ray Tuminaro and Jerry Watkins.
Dr. Tezaur is being hosted by Prof. Garikipati (Mechanical Engineering). If you would like to meet her please email mcteja@umich.edu
[1] I. Velicogna. Increasing rates of ice mass loss from the Greenland and Antarctic ice sheets revealed by GRACE. Geophysical Research Letters, 36 (19) L19503, 2009.
[2] S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K. Averyt, M. Tignor, H. Miller. Climate change 2007: The physical science basis, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge Univ. Press, Cambridge, UK, 2007.
[3] I. Tezaur, M. Perego, A. Salinger, R. Tuminaro, S. Price. Albany/FELIX: A Parallel, Scalable and Robust Finite Element Higher-Order Stokes Ice Sheet Solver Built for Advanced Analysis, Geosci. Model Develop. 8 (2015) 1-24.
[4] J.K. Dukowicz, S.F. Price, W. Lipscomb. Consistent approximations and boundary conditions for ice-sheet dynamics from a principle of least action. J. Glaciol., 56 (197) (2010) 480-496.
[5] R. Tuminaro, M. Perego, I. Tezaur, A. Salinger, S. Price. A matrix dependent/algebraic multigrid approach for extruded meshes with applications to ice sheet modeling, SIAM J. Sci. Comput. 38 (5) (2016) C504-C532.
[6] M. Perego, S. Price, G. Stadler. Optimal initial conditions for coupling ice sheet models to earth system models, J. Geophys. Res., 119 (2014) 1894-1917.
[7] H.C. Edwards, C.R. Trott, D. Sunderland. Kokkos: Enabling manycore performance portability through polymorphic memory access patterns. J. Par. and Distr. Comput., 74 (12) 3202–3216, 2014.
[8] S. Price, M. Hoffman, J. Bonin, T. Neumann, I. Howat, J. Guerber, I. Tezaur, J. Saba, J. Lanaerts, D. Chambers, W. Lipscomb, M. Perego, A. Salinger, R. Tuminaro. An ice sheet model validation framework for the Greenland ice sheet, Geosci. Model Dev. 10 (2017) 255-270

MICDE Seminar: Panos Papadopoulos, Department of Mechanical Engineering, University of California, Berkeley
2017-10-19 15:30 - 16:30 (America/Detroit) | Johnson Rooms, Lurie Engineering Center, 3rd Floor LEC 3213ABC, 1221 Beal Ave., Ann Arbor, MI, United States
Bio: Panos Papadopoulos is a Professor of Mechanical Engineering at the University of California, Berkeley, and director of the Computational Solid Mechanics Laboratory. After obtaining his Diploma in Civil Engineering from the Aristotle University, Greece, he moved to California to pursue his graduate studies. He obtained his M. Sc. and Ph.D. in Civil Engineering from UC Berkeley. His research involves experimental, analytical and computational studies of several mechanics systems. Prof. Papadopoulus develops and applied the finite element method to problems in biomechanics, dynamics of pseudo-rigid bodies, mechanics of continues media, plasticity, materials science and contact mechanics.
Multiscale Modeling in Continuum Mechanics: A connection to the Irving-Kirkwood procedure
This talk describes a method for extending the classical Irving-Kirkwood procedure used in statistical mechanics for extracting local fluxes to the problem of continuum-on-continuum multiscale modeling. Expressions for stress and heat flux derived here are contrasted to those obtained using the standard Hill-Mandel approach. The polar nature of the macroscopic solid and the role of multiscale invariance are also addressed in the context of this method. Applications are explored within the finite element-based homogenization of solids.
Prof. Papadopoulos is being hosted by Prof. Garikipati (Mechanical Engineering). If you would like to meet with him please send an email to mcteja@umich.edu

Mechanical Engineering Seminar: Mark Owkes, Department of Mechanical and Industrial Engineering, Montana State University
2017-10-19 12:00 - 13:30 (America/Detroit) | 1012 EECS, 1301 Beal Ave, Ann Arbor, MI, 48104, United States
Bio: Mark Owkes is an Assistant Professor in the department of Mechanical and Industrial Engineering at Montana State University. He earned a BS in Mechanical Engineering from Clarkson University in 2008. He subsequently attained an MS in Mechanical Engineering from the University of Colorado at Boulder in 2011 under the direction of Prof. Olivier Desjardins. He continued his work under Prof. Desjardins at Cornell University where he earned his Ph.D. in May 2014. Mark’s research interests include the development of numerical methods for capturing gas-liquid interfaces in multiphase flow simulations. His simulations of primary atomization provide insight into the physical phenomena important in the break-up of a liquid jet into droplets. Notably, he has developed both a level set and a volume-of-fluid interface capturing schemes and multiple approaches to compute the curvature of a gas-liquid interface which is important for accurate surface tension forces.
Gas-Liquid Flows: Numerical Methods through Simulations on Supercomputers
Gas-liquid flows exist within many engineering devices including fuel injectors, wave energy extraction devices, fire suppression systems, and PEM fuel cells. Many of these flows are challenging to explore experimentally and computational fluid dynamics (CFD) simulations offer an alternative and useful approach to advance our understanding. For example, the breakup of liquid fuel into droplets via atomization has a direct effect on combustion efficiency and pollutant formation, yet a fundamental understanding of the complex process is absent. Laboratory experiments are inherently difficult to conduct because atomizing jets produce a large number of opaque droplets that hinder optical access to the breakup dynamics. With increasing computational resources and advancements in numerical methods, computational fluid dynamics (CFD) has emerged as a promising tool to investigate the fundamental nature of atomization. In this presentation, I will present an overview of difficulties arising due to the discontinuities that exist at the gas-liquid interface and recent advances in numerical methods that overcome these challenges. Then I will discuss efforts to improve the the usefulness of the very large data-sets that result from CFD simulations. Details on computing the curvature of a gas-liquid interface, implementing contact line dynamics, performing physics extraction, and coupling gas-liquid flow calculations with uncertainty quantification we be discussed.

[MICDE] 1st Workshop on Computational Neuroscience
2017-10-16 09:00 - 13:00 (America/Detroit) | Space 2435 North Quad, 105 S. State St., Ann Arbor, MI, 48109, United States
MICDE and the Graduate Program in Neuroscience have organized the first Computational Neuroscience Workshop. The goal of the event is to bring together the U-M community of neuroscientists who use computational methods in their research, and to start building new bridges across disciplines and departments. For more information and to register…

MICDE Seminar: Margaret Cheung, Department of Physics, University of Houston
2017-10-03 16:00 - 17:00 (America/Detroit) | CHEM 1640, 930 N University, Ann Arbor, MI, 48109, United States
Bio: Margaret Cheung is an Associate Professor of Physics at the University of Houston. She graduated from the National Taiwan University with a bachelor’s degree in chemistry and received her Ph.D. in physics from the University of California, San Diego. She carried out theoretical biological physics and bioinformatics research as a Sloan Postdoctoral Fellow at the University of Maryland and started her lab at the University of Houston in 2006. Professor Cheung’s research is in the field of protein folding inside a cell, calmodulin dependent calcium signaling, and quantum efficiency in artificial photosynthetic materials. She is particularly interested in developing coarse-grained models for protein dynamics in crowded systems, creating multi-physics models that bridge dynamics across wide temporal and spatial scales, and designing computational algorithms that effectively integrate novel high-performance resources. These systems can then be applied for understanding of biological function and for developing therapeutic strategies. She is a fellow of the American Physical Society and a Senior Scientist at the Center for Theoretical Biological Physics at Rice University.
Molecular Underpinning of Postsynaptic Calmodulin-dependent Calcium Signaling
Calcium (Ca2+) is exquisitely utilized by a cell for transducing external stimuli through its gradient of extracellular (~1000 μM) and intracellular (~0.1 μM) concentration. A broad spectrum of Ca2+ signals are encoded by protein calmodulin (CaM) through specific binding with various targets regulating CaM-dependent Ca2+ signaling pathways in neurons. I will focus on binding between CaM and two specific targets, Ca2+/CaM-dependent protein kinase II (CaMKII) and neurogranin (Ng), as they antagonistically regulate CaM-dependent Ca2+ signaling pathways in neurons. I will show the impact of bound calmodulin (CaM)-target compound structure on the affinity of calcium (Ca2+) by integrating coarse-grained models and all-atomistic simulations with non-equilibrium physics. We discovered the molecular underpinnings of lowered affinity of Ca2+ for CaM in the presence of Ng by showing that the N-terminal acidic region of Ng peptide pries open the β-sheet structure between the Ca2+ binding loops particularly at C-domain of CaM, enabling Ca2+ release. In contrast, CaMKII peptide increases Ca2+ affinity for the C-domain of CaM by stabilizing the two Ca2+ binding loops. Through distinctive structural differences in the bound complexes of apoCaM-Ng13-49 and holoCaM-CaMKII, CaM’s affinity for Ca2+ is delineated by its progressive mechanism of target binding. I will discuss them in the context of evolution and in the crowded environment.
Prof. Cheung is being hosted by Prof. Geva (Chemistry)

Graduate Studies in Computational & Data Sciences Info Session - Central Campus
2017-09-25 17:00 - 18:00 UTC | 2001 LSA Building, 500 State St., Ann Arbor, MI, 48109, United States
Learn about graduate programs that will prepare you for success in computationally intensive fields — pizza and pop provided

The Ph.D. in Scientific Computing is open to all Ph.D. students who will make extensive use of large-scale computation, computational methods, or algorithms for advanced computer architectures in their studies. It is a joint degree program, with students earning a Ph.D. from their current departments, “… and Scientific Computing” — for example, “Ph.D. in Aerospace Engineering and Scientific Computing.”
The Graduate Certificate in Computational Discovery and Engineering trains graduate students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments. The certificate is open to all students currently pursuing Master’s or Ph.D. degrees at the University of Michigan.
The Graduate Certificate in Data Science is focused on developing core proficiencies in data analytics:
1) Modeling — Understanding of core data science principles, assumptions and applications;
2) Technology — Knowledge of basic protocols for data management, processing, computation, information extraction, and visualization;
3) Practice — Hands-on experience with real data, modeling tools, and technology resources.

MIDAS Seminar: Jimmy Soni & Rob Goodman, authors of "A Mind at Play: How Claude Shannon Invented the Information Age"
2017-09-22 17:00 - 18:00 (America/Detroit) | Rackham Building, 4th Floor, 915 E. Washington, Ann Arbor, MI, 48109, United States
Authors Jimmy Soni and Rob Goodman will talk about their new book on U-M alum Claude Shannon: “A Mind at Play: How Claude Shannon Invented the Information Age.”
The talk will be followed by a book signing.
Jimmy Soni is an author and editor. He has worked as an editor at The New York Observer and The Washington Examiner. He has worked as a speechwriter, and his writing and commentary have appeared in Slate, The Atlantic, and CNN. He is a graduate of Duke University and was named to the Forbes 30 Under 30. With Rob Goodman, he is the coauthor of Rome’s Last Citizen: The Life and Legacy of Cato, Mortal Enemy of Caesar and A Mind at Play: How Claude Shannon Invented the Information Age.
Rob Goodman is a doctoral candidate at Columbia University and a former congressional speechwriter. He has written for Slate, The Atlantic, Politico Magazine, and The Chronicle of Higher Education. His scholarly work has appeared in History of Political Thought, the Kennedy Institute of Ethics Journal, and The Journal of Medicine and Philosophy. With Jimmy Soni, he is the coauthor of Rome’s Last Citizen: The Life and Legacy of Cato, Mortal Enemy of Caesar and A Mind at Play: How Claude Shannon Invented the Information Age.

Graduate Studies in Computational & Data Sciences Info Session - North Campus
2017-09-21 17:00 - 18:00 UTC | Johnson Rooms, Lurie Engineering Center, 3rd Floor, 1221 Beal Ave., Ann Arbor, MI, United States

Symposium: Advances on Turbulence Modeling
2017-07-13 09:00 - 17:30, 2017-07-12 09:00 - 17:30, 2017-07-11 09:00 - 17:30 (America/Detroit) | MI
The Center for Data-Driven Computational Physics and NASA are sponsoring the event to discuss the state of the art in turbulence modeling from an academic and an industrial perspective, and place some of the newer developments in RANS modeling (such as uncertainty quantification, data-driven modeling, etc.) in the context of mainstream turbulence modeling.
Speakers include:

Florian Menter, Ansys
Suad Jakirlic, TU Darmstadt
Robert Moser, U. Texas

For more details and to register go to http://turbgate.engin.umich.edu/symposium/

ARC-TS Town Hall on Next Generation HPC Cluster
2017-06-28 14:00 - 15:00 (America/Detroit) | Room 3114, Med Sci I, 1301 Catherine St., Ann Arbor, MI, United States
The University of Michigan is beginning the process of building our next generation HPC platform, “Big House.” Flux, the shared HPC cluster, has reached the end of its useful life. Flux has served us well for more than five years, but as we move forward with replacement, we want to make sure we’re meeting the needs of the research community.
ARC-TS will be holding a series of town halls to take input from faculty and researchers on the next HPC platform to be built by the University. These town halls are open to anyone.
Your input will help to ensure that U-M is on course for providing HPC, so we hope you will make time to attend one of these sessions. If you cannot attend, please email hpc-support@umich.edu with any input you want to share.

ARC-TS Town Hall on Next Generation HPC Cluster
2017-06-27 10:00 - 11:00 (America/Detroit) | MI

ARC-TS Town Hall on Next Generation HPC Cluster
2017-06-21 11:00 - 12:00 (America/Detroit) | NCRC Building 300, Room 376, 1600 Huron Parkway, Ann Arbor, MI, United States

ARC-TS Town Hall on Next Generation HPC Cluster
2017-06-20 09:00 - 10:00 (America/Detroit) | Johnson Rooms, Lurie Engineering Center, 3rd Floor LEC 3213ABC, 1221 Beal Ave., Ann Arbor, MI, United States

Symposium of the Center for Network and Storage-Enabled Collaborative Computational Science
2017-05-18 13:00 - 2017-05-19 17:00 (America/Detroit) | Space 2435 North Quad, 105 S. State St., Ann Arbor, MI, 48109, United States
The Center for Network and Storage Enabled Collaborative Computational Science is hosting a 1.5 day symposium at the University of Michigan exploring the themes the Center was founded on. The Center seeks to address the challenges of extracting scientific results collaboratively from large, distributed or diverse data. For more information please visit https://live-umor-micde.pantheonsite.io/centers/cnseccs/2017-symposium/

MIDAS Working Group on NSF solicitation for Big Data Spokes
2017-04-24 11:00 - 13:00 (America/Detroit) | MIDAS – SPH I, Suite 7625, 1415 Washington Heights, Ann Arbor, MI, 48109-2029, United States
This working group is organized by MIDAS to respond to the NSF Big Data Spokes funding solicitation (BD Spokes).
Agenda:

A brief presentation about the funding opportunity and the background of the regional BD Hubs (Midwest, Northeast, South and West) and existing Spokes
Discussion of ideas of new Spokes and forming collaborative teams (within and outside of UM)
Discussion on aligning and working with regional BD hubs

The BD Spokes will work with regional BD hubs and existing spokes to accelerate progress towards societal grand challenges in regional and national priority areas, help automate the Big Data lifecycle, enable access to and increase the use of important data sets, and contribute to education and training. The focus areas specified by NSF include: Education; Data Intensive Research in the Social, Behavioral, and Economic Sciences; Data-driven Research in Chemistry; Neuroscience; Data Analytics for Security; Replicability and Reproducibility in Data Science. All researchers interested in proposing or collaborating on new BD Spokes are welcome to our working group.
Important Dates:

May 17, 2017: University of Michigan internal deadline for declaring intent. NSF allows only one proposal from each university as the lead institution

Sept. 18, 2017: full proposal due to NSF

Please RSVP. For questions, please contact Jing Liu, MIDAS research specialist (ljing@umich.edu; 734-764-2750).

2017 MICDE Annual Symposium
2017-04-18 08:30 - 17:00 (America/Detroit) | Rackham Building, 4th Floor, 915 E. Washington, Ann Arbor, MI, 48109, United States
Please join us for the Michigan Institute for Computational Discovery and Engineering 2017 Symposium. The event features eminent scientists from around the world and the U-M campus. The symposium this year focuses on the “New Era of Data-Enabled Computational Science.”
Speakers:

Frederica Darema — Director, Air Force Office of Scientific Research
George Karniadakis — Professor of Applied Mathematics, Brown University
Tinsley Oden — Director of the Institute for Computational Engineering and Sciences, V.P. for Research, University of Texas at Austin
Karen Willcox — Professor of Aerospace and Aeronautics, Massachusetts Institute of Technology, co-Director of MIT Center for Computational Engineering
Jacqueline H. Chen — Distinguished Member of Technical Staff at the Combustion Research Facility, Sandia National Laboratories
Laura Balzano — Assistant Professor, Electrical Engineering and Computer Science, U-M
Emanuel Gull — Assistant Professor, Physics

The symposium features a poster competition and more. For more information and to register go to https://live-umor-micde.pantheonsite.io/symposium17/
Past Symposia
2016 MICDE Annual Symposium
Research Computing Symposium Fall 2014

MICDE Seminar: Yongjie Jessica Zhang, Mechanical Engineering and Biomedical Engineering, Carnegie Mellon University
2017-03-17 11:00 - 12:00 (America/Detroit) | 1200 EECS, 1301 Beal Ave., Ann Arbor, MI, 48109, United States
Bio: Yongjie Jessica Zhang is a Professor in Mechanical Engineering at Carnegie Mellon University with a courtesy appointment in Biomedical Engineering. She received her B.Eng. in Automotive Engineering, and M.Eng. in Engineering Mechanics from Tsinghua University, China; and M.Eng. in Aerospace Engineering and Engineering Mechanics and Ph.D. in Computational Engineering and Sciences from Institute for Computational Engineering and Sciences (ICES), The University of Texas at Austin. After staying two years at ICES as a postdoctoral fellow, she joined CMU in 2007 as an assistant professor, and then was promoted to an associate professor in 2012 and a full professor in 2016. Her research interests include computational geometry, mesh generation, computer graphics, visualization, finite element method, isogeometric analysis and their application in computational biomedicine, material sciences and engineering. She has co-authored over 140 publications in peer-reviewed journals and conference proceedings, and received the Autodesk Best Paper Award 1st Place in SIAM Conference on Solid and Physical Modeling 2015, the Best Paper Award in CompIMAGE’16 conference and one of the 5 Most Highly Cited Papers Published in Computer-Aided Design during 2014-2016. She recently published a book entitled “Geometric Modeling and Mesh Generation from Scanned Images” with CRC Press, Taylor & Francis Group. She is the recipient of Presidential Early Career Award for Scientists and Engineers, NSF CAREER Award, Office of Naval Research Young Investigator Award, USACM Gallagher Young Investigator Award, Clarence H. Adamson Career Faculty Fellow in Mechanical Engineering, George Tallman Ladd Research Award, and Donald L. & Rhonda Struminger Faculty Fellow.
Image-Based Mesh Generation and Volumetric T-Spline Modeling for Isogeometric Analysis with Engineering Applications
With finite element method and scanning technology seeing increased use in many research areas, there is an emerging need for high-fidelity geometric modeling and mesh generation of spatially realistic domains. This talk will highlight research in three areas: image-based mesh generation for complicated domains, trivariate spline modeling for isogeometric analysis, as well as biomedical, material sciences and engineering applications. First Prof. Zhang will present advances and challenges in image-based geometric modeling and meshing along with a comprehensive computational framework, which integrates image processing, geometric modeling, mesh generation and quality improvement with multi-scale analysis at molecular, cellular, tissue and organ scales. Different from other existing methods, the presented framework supports five unique features: high-fidelity meshing for heterogeneous domains with topology ambiguity resolved; multiscale geometric modeling for biomolecular complexes; automatic all-hexahedral mesh generation with sharp feature preservation; robust quality improvement for non-manifold meshes; and guaranteed-quality meshing. These unique capabilities enable accurate, stable, and efficient mechanics calculation for many biomedicine, materials science and engineering applications. As a new advancement of traditional finite element method, isogeometric analysis (IGA) was proposed to integrate design and analysis. In the second part of this talk, she will present her latest research on volumetric T-spline parameterization for IGA applications. For arbitrary-topology objects, we first build a polycube whose topology is equivalent to the input geometry and it serves as the parametric domain for the following trivariate T-spline construction. Boolean operations, geometry skeleton and centroidal Voronoi tessellation based surface segmentation are used to preserve surface features. A parametric mapping is then used to build a one-to-one correspondence between the input geometry and the polycube boundary. After that, we choose the deformed octree subdivision of the polycube as the initial T-mesh, and make it valid through pillowing, quality improvement, and applying templates or truncated subdivision schemes to handle extraordinary nodes. Weighted and truncated T-spline basis functions are derived to enable analysis-suitability, including partition of unity and linear independence. The developed pipelines have been incorporated into commercial software such as Rhino and Abaqus.
Prof. Zhang is being hosted by Prof. Garikipati (Mechanical Engineering)

SC2/MICDE Seminar: Eric Jankowski, Materials Science and Engineering, Boise State University
2017-03-08 14:00 - 15:00 (America/Detroit) | 2540 G.G. Brown (2350 Hayward St.), 2300 Hayward St, Ann Arbor, MI, 48109, United States
Bio: Eric Jankowski is an assistant professor of Materials Science and Engineering at Boise State University. He earned his PhD in Chemical Engineering from the University of Michigan in 2012, where he developed computational tools to study the self-assembly of nanoparticles. These tools leveraged graphics processors to accelerate computations and provided insight into systems of both theoretical and practical importance. Dr. Jankowski began focusing on renewable energy generation during his postdoctoral positions at the University of Colorado and the National Renewable Energy Laboratory. At these postdocs, Dr. Jankowski applied techniques he developed during his thesis to understand factors that determine the ordering of molecules in organic solar cells.
This is a joint seminar of the Scientific Computing Student Club and MICDE, sponsored in part by U-M Rackham Graduate School.

Cobbling together computational components to engineer inexpensive plastic solar panels
In order to meet projected global energy demands over the next 25 years, the equivalent of building a 1GW power plant each day is needed. Existing clean power generation technologies can meet this demand in principle, but their relatively large short-term costs have limited widespread adoption. In this work we explain manufacturing strategies for organic (plastic) solar panels that overcome economic barriers to adoption by optimizing the structure of the organic active layer responsible for generating electricity. We perform coarse-grained molecular dynamics simulations accelerated with graphics processing units to determine the thermodynamically stable morphologies for a variety of candidate ingredients. Using these morphologies we perform kinetic Monte Carlo charge transport simulations to determine which morphologies are better candidates for solar devices. The simulation pipeline developed here combines computational tools developed for solving unrelated problems, and we discuss the evolving landscape of scientific computing education and how it overlaps with this work.

MICDE Seminar: Michael Eldred, Computation, Computers, Information, and Mathematics Center, Sandia National Laboratories
2017-03-07 16:00 - 17:00 (America/Detroit) | 1008 FXB, 1320 Beal Ave, Ann Arbor, MI, 48109
Bio: Michael Eldred is a Distinguished Member of the Technical Staff in the Optimization and Uncertainty Quantification Department within the Computation, Computers, Information, and Mathematics Center at Sandia National Laboratories. He received his B.S. in Aerospace Engineering from Virginia Tech in 1989, his M.S.E. and Ph.D. in Aerospace Engineering from the University of Michigan in 1990 and 1993. Mike led the DAKOTA project, a “… toolkit that provides a flexible, extensible interface between analysis codes and iterative systems analysis methods…”, for 15 years (1994-2009) and now leads algorithm research and development activities related to DAKOTA. Mike’s research interests include uncertainty quantification, design under uncertainty, surrogate-based optimization, and high-performance computing, with application to stockpile stewardship and energy initiatives through the NNSA ASC, DOE ASCR, and DOE SciDAC programs.
Mike is an Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA) and a member of the Society for Industrial and Applied Mathematics (SIAM), the International Society for Structural and Multidisciplinary Optimization (ISSMO), and the United States Association for Computational Mechanics (USACM). He currently serves as a member of the AIAA Nondeterministic Approaches Technical Committee and on the editorial board for the International Journal for Uncertainty Quantification. A number of his publications are available on the DAKOTA web site.
Title: Multilevel-Multifidelity Approaches for Uncertainty Quantification and Design
In the simulation of complex physics, multiple model forms of varying fidelity and resolution are commonly available. In computational fluid dynamics, for example, common model fidelities include potential flow, inviscid Euler, Reynolds-averaged Navier-Stokes, and large eddy simulation, which may be further augmented by subgrid-scale model selections and spatio-temporal discretization levels. In this presentation, we focus on novel algorithms that simultaneously exploit multiple model forms and multiple resolutions, both for uncertainty quantification (UQ) and for optimization under uncertainty (OUU). These hybrid methods exploit multifidelity methods across the model form hierarchy in combination with multilevel accelerators across an associated discretization hierarchy, manifesting as multilevel control variate Monte Carlo and multilevel polynomial expansion methods in the UQ case and recursive trust-region and multigrid optimization in the OUU case. These techniques will be demonstrated for both model problems and engineered systems, and will be placed within the broader context of algorithm research and development within the Dakota project at Sandia.
Dr. Eldred is being hosted by Prof. Duraisamy (Aerospace Engineering)

Jose Perea, PhD, Michigan State University - MIDAS Seminar Series
2017-02-24 16:00 - 17:00 (America/Detroit) | Gerald Ford Library, 1000 Beal Avenue, Ann Arbor, MI, 48109, United States
Jose Perea, PhD
Assistant Professor
Departments of Mathematics and
Computational Mathematics, Science and Engineering
Michigan State University
Bio: My research focus lies at the intersection of algebraic topology, data analysis and computational methods. My main interest consists in the application and adaptation of ideas from algebraic and geometric topology to the study of high-dimensional and complex data. Other interests include computer vision and computational biology.
For more information on MIDAS or the Seminar Series, please contact midas-contact@umich.edu. MIDAS gratefully acknowledges Northrop Grumman Corporation for its generous support of the MIDAS Seminar Series.

Carol Flannagan, PhD, University of Michigan - MIDAS Seminar Series
2017-02-17 16:00 - 17:00 (America/Detroit) | Forum Hall, Palmer Commons, 100 Washtenaw Ave, Ann Arbor, MI, 48109, United States
Carol A. C. Flannagan, PhD
Research Associate Professor
University of Michigan Transportation Research Institute
University of Michigan
Bio: Carol A. C. Flannagan is a research associate professor in UMTRI’s Biosciences Group, and director of CMISST. She joined UMTRI in 1991 after completing her Ph.D. in mathematical and experimental psychology at the University of Michigan (U-M). She also holds an M.A. in applied statistics from U-M and a B.A. in psychology from St. Lawrence University.
Dr. Flannagan has over 20 years of experience conducting data analysis and research on injury risk related to motor vehicle crashes and was responsible for the development of a model of injury outcome that allows side-by-side comparison of public health, vehicle, roadway and post-crash interventions. She has also applied statistical methods to understanding of the potential benefits of crash-avoidance technologies, and works to develop novel applications of statistics to improve understanding of transporation safety. Dr. Flannagan’s current work with CMISST involves the fusion and analysis of large state-level crash databases, which are useful in analyzing the effect of a variety of countermeasures on crash involvement and injury risk. In addition, her group is working to make data available to researchers to expand the community of experts in transportation data analysis.
For more information on MIDAS or the Seminar Series, please contact midas-contact@umich.edu. MIDAS gratefully acknowledges Northrop Grumman Corporation for its generous support of the MIDAS Seminar Series.

[SC2] U-M 3D Lab Tour
2017-02-16 17:00 - 18:00 (America/Detroit) | MI
The 3D Lab will give a brief tour and presentation of the 3D visualization resources available to students and all researchers at U-M. If you are thinking of registering to the Visualization Challenge, this is a good opportunity to see many of the 3D options you have to present your data. Space is limited to 20 people: register here
