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SUMMARY:MICDE / MIDAS Seminar: Ivo Dinov\, Professor\, Nursing\, Computational Medicine & Bioinformatics
DESCRIPTION:Bio: Dr. Ivo D. Dinov directs the Statistics Online Computational Resource (SOCR)\, co-directs the multi-institutional Probability Distributome Project\, and is an associate director for education of the Michigan Institute for Data Science (MIDAS). \nDr. Dinov is an expert in mathematical modeling\, statistical analysis\, computational processing and visualization of Big Data. He is involved in longitudinal morphometric studies of human development (e.g.\, Autism\, Schizophrenia)\, maturation (e.g.\, depression\, pain) and aging (e.g.\, Alzheimer’s and Parkinson’s diseases). Dr. Dinov is developing\, validating and disseminating novel technology-enhanced pedagogical approaches for scientific education and active learning. \nDATA SCIENCE\, TIME COMPLEXITY\, AND SPACEKIME ANALYTICS \nMany observable processes demand managing\, harmonizing\, modeling\, analyzing\, interpreting\, and visualizing of large and complex information. There is a substantial need to develop\, validate\, productize\, and support novel mathematical techniques\, advanced statistical computing algorithms\, transdisciplinary tools\, and effective artificial intelligence applications. Spacekime analytics is a new technique for modeling high-dimensional longitudinal data. This approach relies on extending the notions of time\, events\, particles\, and wavefunctions to complex-time (kime)\, complex-events (kevents)\, data\, and inference-functions. We will illustrate how the kime-magnitude (longitudinal time order) and kime-direction (phase) affect the subsequent predictive analytics and the induced scientific inference. \nThe mathematical foundation of spacekime calculus reveal various statistical implications including inferential uncertainty and a Bayesian formulation of spacekime analytics. Complexifying time allows the lifting of all commonly observed processes from the classical 4D Minkowski spacetime to a 5D spacekime manifold\, where a number of interesting mathematical problems arise. Direct data science applications of spacekime analytics will be demonstrated using simulated data and clinical observations (e.g.\, structural and functional MRI). \n\nThe MICDE Fall 2020 and Winter 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nWatch the recorded webinar. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-ivo-dinov-professor-nursing-and-computational-medicine-bioinformatics-university-of-michigan/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/09/Ivo-Dinov.png
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DTSTART;TZID=America/Detroit:20210209T160000
DTEND;TZID=America/Detroit:20210209T170000
DTSTAMP:20260607T011227
CREATED:20230905T171258Z
LAST-MODIFIED:20230905T171258Z
UID:10000408-1612886400-1612890000@micde.umich.edu
SUMMARY:MICDE / Mechanical Engineering Seminar: Ceila Reina\, Assistant Professor\, Mechanical Engineering and Applied Mechanics\, University of Pennsylvania
DESCRIPTION:Bio:  Celia Reina is the William K. Gemmill Term Assistant Professor in Mechanical Engineering and Applied Mechanics at the University of Pennsylvania. She joined in 2014 after holding the Lawrence Postdoctoral Fellowship at Lawrence Livermore National Laboratory and the HCM postdoctoral Fellowship at the Hausdorff Center of Mathematics in Bonn\, Germany. Dr. Reina received her PhD from the California Institute of Technology in Aerospace Engineering in 2011\, under the supervision of Prof. Michael Ortiz\, following a B.S. in Mechanical Engineering from the University of Seville in Spain\, and a Master in Structural Dynamics from Ecole Centrale Paris in France. She is the 2017 recipient of the Eshelby Mechanics Award for Young Faculty\, she is a member of the TTA on Nanotechnology and Lower Scale Phenomena at the USACM\, and she currently serves as the recording secretary for the Applied Mechanics Division of the ASME. \nCONTINUUM MECHANICS OF NON-EQUILIBRIUM PHENOMENA: A JOURNEY THROUGH SPACE AND TIME SCALES:  The fascinating diversity of material behavior at the macroscopic scale can only emerge from the underlying atomistic or particle behavior. Yet\, the direct connection between these two scales remains an extremely challenging quest\, particularly in the context of non-equilibrium phenomena. In this talk\, we will discuss several advances in this direction\, in the context of plasticity\, thermoelasticity\, diffusion and viscous dissipation. In all these cases\, the importance of fluctuations in the effective response will become apparent. More precisely\, these will provide crucial information for the material description and evolution at the continuum scale\, where the behavior is modeled as deterministic and free of fluctuations. \n\nThe MICDE Winter 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nThis event will be a joint seminar with the University of Michigan College of Engineering’s Mechanical Engineering department. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-mechanical-engineering-seminar-ceila-reina-assistant-professor-mechanical-engineering-and-applied-mechanics-university-of-pennsylvania/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/09/Celia-Reina.png
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DTSTART;TZID=America/Detroit:20210216T150000
DTEND;TZID=America/Detroit:20210216T160000
DTSTAMP:20260607T011227
CREATED:20230905T171258Z
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SUMMARY:MICDE Seminar: Emma Lejeune\, Assistant Professor\, Mechanical Engineering\, Boston University
DESCRIPTION:Bio: Emma Lejeune is an Assistant Professor in the Mechanical Engineering Department at Boston University. She received her PhD from Stanford University in September 2018\, and was a Peter O’Donnell\, Jr. postdoctoral research fellow at the Oden Institute at the University of Texas at Austin until 2020 when she joined the faculty at BU. At BU\, Emma has received the David R. Dalton Career Development Professorship\, a Computational Science and Engineering Junior Faculty Fellowship\, and the Haythornthwaite Research Initiation Grant from the ASME Applied Mechanics Division. Current areas of research involve integrating data-driven and physics based computational models\, and characterizing and predicting the mechanical behavior of heterogeneous materials and biological systems. \nMODELING HETEROGENEOUS MATERIALS: BENCHMARK DATASETS\, METAMODELS\, AND EXPERIMENTAL CHARACTERIZATION: \nBiological systems are spatially heterogeneous across scales. To effectively model biological materials we need new tools to quantify and capture this heterogeneity. In this talk\, we will first discuss our recent work on simulating spatially heterogeneous materials. Specifically\, we will discuss our recent work in developing and exploring benchmark datasets of spatially heterogeneous materials simulated with the finite element method. These datasets are useful primarily for constructing metamodels\, or computationally cheap models of models\, that map defined model inputs to defined model outputs. By nature\, a given metamodel will be tailored to a specific dataset. However\, the most pragmatic metamodel type and structure will often be general to larger classes of problems. At present\, the most pragmatic metamodel selection for predicting the mechanical behavior of spatially heterogeneous materials — specifically simulations of heterogenous materials — has not been thoroughly explored. Drawing inspiration from the benchmark datasets available to the computer vision research community\, we introduce a benchmark data set (Mechanical MNIST https://open.bu.edu/handle/2144/39371) for constructing metamodels of heterogeneous material undergoing large deformation. We then show a few examples of problems that we have explored thus far with this dataset. Looking forward\, we anticipate that disseminating benchmark datasets will enable the broader community of researchers to develop improved metamodeling techniques for capturing the behavior of spatially heterogeneous materials that will surpass the baseline performance that we show here. Finally\, to conclude the talk\, we will change gears and briefly discuss some of our recent work on creating new tools for characterizing cell behavior using concepts from kinematics and spatial statistics. Looking forward\, we are interested in the natural synergy between advances in methods for both simulating and characterizing heterogeneous materials. \n\nThe MICDE Winter 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nDr. Lejeune will be hosted by Professor Krishna Garikipati\, MICDE Director. \nWatch the full webinar. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-emma-lejeune-assistant-professor-mechanical-engineering-boston-university/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/11/Emma-Lejeune.png
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