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DTSTART;TZID=America/Detroit:20210325T160000
DTEND;TZID=America/Detroit:20210325T170000
DTSTAMP:20260604T231212
CREATED:20230905T171443Z
LAST-MODIFIED:20260403T173114Z
UID:10000463-1616688000-1616691600@micde.umich.edu
SUMMARY:PhD Seminar: Chanese Forte and Hyeon Joo
DESCRIPTION:CHANESE FORTE\, GRADUATE STUDENT\, ENVIRONMENTAL HEALTH SCIENCES & SCIENTIFIC COMPUTING \nBio: Chanese is a Dual PhD student pursuing a degree in the Environmental Health Sciences and Scientific Computing. Chanese’s research interests lie in chemical exposure in agriculture workers and cellular alteration. \nASCERTAINING PESTICIDE EXPOSURE AND BIOACTIVITY USING OPEN SOURCE DATA: Pesticides are known to be harmful chemicals to human health\, however\, they are still heavily used in agriculture. Using large publicly available datasets\, this study aims to quantify pesticide exposure levels of the US general population in comparison to farmworkers. The National Health and Nutrition Examination Survey (NHANES) is a cross-sectional study representative of the US population. NHANES was used to quantify pesticide exposure among US farmworkers and the general population who responded to NHANES. It compares and analyzes\, using regression\, the US pesticide exposure levels to the bioactivity of these same pesticides within the human body. By comparing population-level data with toxicological assay data in future projects\, we hope to create a more overarching idea of how pesticides may be affecting the body and the human population level. \n  \nHYEON JOO\, GRADUATE STUDENT\, HEALTH INFRASTRUCTURES AND LEARNING SYSTEMS & SCIENTIFIC COMPUTING \nBio: Hyeon Joo is a second year PhD student in the Health Infrastructures and Learning Systems program of the Department of Health Learning Systems (Michigan Medical School). He completed his MS in Computer Science and Engineering\, and Master of Health Informatics from the University of Michigan\, Ann Arbor. His research focuses on developing and implementing computational data-driven algorithms\, systems or tools to help users identify gaps and make informed decisions. He loves working in the field of health care as a data scientist and a software engineer. \nEARLY PREDICTION OF HEART FAILURE USING ATTENTION MODELS USING EHR DATA: Heart Failure (HF) is a severe and progressive chronic condition affecting over 5.8 million patients with a 5-year mortality rate of 45-60% in the United States. Despite significant efforts and advanced HF management\, diagnosing HF in the early stages remains challenging due to its syndromic nature and non-specific disease presentation. In this seminar\, I will present a single attention recurrent network and a hierarchical attention convolutional neural networks to detect the early stage of HF at a tertiary hospital. I will also describe various methods of feature selection to reduce the computation time and improve the performance of the models. Lastly\, I will present the challenges of adopting models in clinical practice which leads to my next research steps. \n\nRegister via Zoom to immediately receive login information. Note: You may register and join after the event has started. \nThis event is part of MICDE’s Winter 2021 seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/phd-seminar-chanese-forte-and-hyeon-joo/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210324T130000
DTEND;TZID=America/Detroit:20210324T150000
DTSTAMP:20260604T231212
CREATED:20230905T171443Z
LAST-MODIFIED:20230905T171443Z
UID:10000440-1616590800-1616598000@micde.umich.edu
SUMMARY:Software Development For Research: Team-Based Programming Practices
DESCRIPTION:Software development and computer programming is increasingly a major part of scientific research. When small or large teams are involved in coding the same project\, it’s a good idea to adopt team-based practices\, such as “pair programming” or “code review” meetings\, to ensure quality is maintained in the code. This hands-on workshop will provide examples of these topics in action\, and attendees will leave prepared to use these skills in their own work groups. \nThis is part of a series of workshops focused on software and coding from a research perspective.
URL:https://micde.umich.edu/event/software-development-for-research-team-based-programming-practices/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210319T150000
DTEND;TZID=America/Detroit:20210319T160000
DTSTAMP:20260604T231212
CREATED:20230905T171444Z
LAST-MODIFIED:20230905T171444Z
UID:10000464-1616166000-1616169600@micde.umich.edu
SUMMARY:AIM/MICDE Seminar: Daniel Lecoanet\, Postdoctoral Fellow\, Princeton Center for Theoretical Science\, Astrophysical Sciences\, Princeton University
DESCRIPTION:Bio: Dr. Lecoanet earned a Bachelor of Science degree in Mathematics from the University of Wisconsin at Madison\, a Master’s degree in Applied Mathematics from the University of Cambridge\, and a PhD in Physics from the University of California\, Berkeley. He currently holds a joint postdoc position at the Princeton Center for Theoretical Science and as a Lyman Spitzer\, Jr. fellow at the Department of Astrophysical Sciences. Dr. Lecoanet works primarily on Astrophysical and Geophysical Fluid Dynamics. He is a core developer for Dedalus. \nPROBING THE CORES OF MASSIVE STARS THROUGH THEIR SURFACE: Stars are opaque\, which makes it difficult to study their interiors. Recent space-based telescopes have led to the new field of asteroseismology: by measuring global oscillation modes of a star\, you can infer its interior properties. Massive stars have convection in their cores which can generate waves\, which might be detectable at the surface. In the first part of this talk\, I will describe a heuristic way of estimating wave generation by convection\, and compare it to high-resolution numerical simulations in Cartesian geometry. To make quantitative predictions to compare with observations\, one must run simulations in spherical geometry. In the second part of my talk\, I will present a new spectral algorithm for solving nearly arbitrary\, tensorial PDEs in spherical coordinates. The challenge is to devise bases which respect regularity conditions at r=0\, which depend on the rank of the tensor. The algorithm can be easily applied to the problem of wave generation by convection in stars\, as well as a wide range of other problems in stellar astrophysics\, core geophysics\, and planetary sciences. \n\nThis seminar is co-presented by Applied and Interdisciplinary Mathematics program\, and the Michigan Institute for Computational Discovery & Engineering. Dr. Lecoanet will be hosted by Professor Charlie Doering\, the Nicholas D. Kazarinoff Collegiate Professor of Complex Systems\, Mathematics and Physics\, and Director of the Center for the Study of Complex Systems. \nRegister for this event to receive Zoom login information. \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. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-daniel-lecoanet-postdoctoral-fellow-princeton-center-for-theoretical-science-astrophysical-sciences-princeton-university/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2021/03/Daniel-Lecoanet.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210318T160000
DTEND;TZID=America/Detroit:20210318T170000
DTSTAMP:20260604T231212
CREATED:20230905T171300Z
LAST-MODIFIED:20230905T171300Z
UID:10000461-1616083200-1616086800@micde.umich.edu
SUMMARY:PhD Seminar: Vishwas Goel and Benjamin Yang
DESCRIPTION:VISHWAS GOEL\, GRADUATE STUDENT\, MATERIALS SCIENCE AND ENGINEERING & SCIENTIFIC COMPUTING \nBio:  Vishwas is a third year Ph.D. student in the Thornton group\, Department of Materials Science and Engineering. His research involves the simulations of the continuum level or microstructure level electrochemical dynamics of energy conversion/storage devices such as batteries\, fuel cells\, etc. \nSIMULATION OF EIS IN SOFC CATHODES USING SMOOTHED BOUNDARY METHOD:  Electrochemical impedance spectroscopy is the most commonly used technique for the in-situ characterization of solid oxide fuel cells (SOFC). In this presentation\, I will discuss about a method for simulating the impedance behavior of a mixed conducting SOFC cathode with an experimentally determined microstructure. I will also share the key insights that we generated through our work. \n  \n  \nBENJAMIN YANG\, GRADUATE STUDENT\, BIOMEDICAL ENGINEERING & SCIENTIFIC COMPUTING \nBio:  Ben is a 4th year PhD student in Dr. Carlos Aguilar’s Lab. His research explores the molecular mechanisms that regulate cellular fate plasticity using microfluidics\, cell-cell fusion\, and single-cell sequencing techniques. \nDECONSTRUCTING METASTATIC REGULATORS USING INTERSPECIES HETEROKARYONS:  Tumor metastasis\, the spread of cancer cells to sites beyond the primary tumor\, is the primary contributor to morbidity in cancer patients. While each step of the metastatic cascade is well characterized\, the molecular mechanisms responsible for initiating the cascade remain unclear\, inhibiting the efficacy of therapeutic modalities. We revisit a century-old hypothesis that changes in metastatic potential are conferred to tumor cells through fusion with neighboring stromal cells by fusing human breast cancer cells with brain-resident mouse microglia and astrocytes. Our main objectives are to assess how aberrant fusion between malignant cells and stromal cells overrides transcriptional safeguards against metastatic progression and to explore how fusion modifies the mechanical phenotype of tumor hybrids. Achieving these goals will advance our understanding of the biological significance of fusion events in metastasis and delineate markers that can serve as therapeutic targets. \n\nRegister via Zoom to immediately receive login information. Note: You may register and join after the event has started. \nThis event is part of MICDE’s Winter 2021 seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/phd-seminar-vishwas-goel-and-benjamin-yang/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210318T110000
DTEND;TZID=America/Detroit:20210318T120000
DTSTAMP:20260604T231212
CREATED:20230905T171300Z
LAST-MODIFIED:20230905T171300Z
UID:10000462-1616065200-1616068800@micde.umich.edu
SUMMARY:MICDE Seminar: Udo von Toussaint\, PD\, Group Leader at the Max-Planck-Institute for Plasmaphysics in Garching\, Divison Numerical Methods for Plasmaphysics
DESCRIPTION:WATCH THE RECORDING HERE. \nBio: Dr. Udo v. Toussaint earned his PhD in Physics at the University of Bayreuth in 2000. He then worked as a Postdoctoral Researcher at NASA Ames (RIACS)\, in Mountain View\, CA from 2000-2002.  Since 2003\, Dr. von Toussaint has been a Scientist at the Max-Planck Institute for Plasmaphysics in Garching. Dr. von Toussaint is also editor of the ‘Entropy’ journal. \nBesides plasma-wall interaction\, his research interests are focussed on the design of optimal analysis and measurement strategies (Bayesian experimental design) for computer- and physics experiments. This encompasses modern concepts of uncertainty quantification (UQ) of complex computer codes (e.g. Plasma-wall simulations) as well as active-learning systems\, which dynamically decide which action (e.g. measurement of a specific spectral line) might yield the most informative data based on the results from previous actions. This is addressed with Machine Learning techniques\, e.g. Hidden Markov Models (HMM)\, neutral networks or bayesian acyclic graphs and complemented by numerical methods like Markov Chain Monte Carlo (MCMC)\, sequential optimization or polynomial chaos expansion. \nA BAYESIAN APPROACH TO ARTIFICIAL NEURAL NETWORKS:  Artificial Neural networks (ANN) are famous for their advantageous flexibility for problems when there is insufficient knowledge to set up a proper model. On the other hand\, this flexibility can cause overfitting and can hamper the generalization and stability of ANNs. Many approaches to regularize ANNs have been suggested (e.g. L1- or L2-norm based regularization) but most of them are based on ad hoc arguments. Employing the principle of transformation invariance\, a general prior for feed-forward networks can be derived. This regularization prior not only favours cell and layer pruning but enable also a consistent Bayesian approach: Relying on Occam’s razor we demonstrate (as a proof of concept) how an ANN can be applied even in the >absence< of available training data. The relation to the concept of automatic relevance detection will be discussed. \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. von Toussaint will be hosted by Professor Xun Huan\, Assistant Professor of Mechanical Engineering. \nRegister for this event via Zoom to receive an email with the link and passcode to connect. Note: You may register after the event has started. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-udo-von-toussaint-pd-group-leader-at-the-max-planck-institute-for-plasmaphysics-in-garching-divison-numerical-methods-for-plasmaphysics/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2021/03/Udo-von-Toussaint.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210317T150000
DTEND;TZID=America/Detroit:20210317T163000
DTSTAMP:20260604T231212
CREATED:20230905T171300Z
LAST-MODIFIED:20230905T171300Z
UID:10000460-1615993200-1615998600@micde.umich.edu
SUMMARY:GIS Fundamentals – VI (Map visualization)
DESCRIPTION:This is the sixth workshop in a series of workshops we are offering this semester on the fundamentals of GIS. Each workshop covers one or two key elements of GIS and is self-contained. The focus is on conceptual details that can provide sufficient preparation for applications\, but we will also touch upon the technical aspects. \n\nThis workshop will cover basic concepts and tools available in QGIS and R for visualizing vector spatial data as single and bi-variate static choropleth maps. We will focus on basic cartography principles for map-making and explore the functionalities of R and QGIS for making production-quality maps. \n\nParticipants should have some familiarity with R\, but exposure to QGIS is not required.
URL:https://micde.umich.edu/event/gis-fundamentals-vi-map-visualization/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210316T100000
DTEND;TZID=America/Detroit:20210316T120000
DTSTAMP:20260604T231212
CREATED:20230905T171300Z
LAST-MODIFIED:20230905T171300Z
UID:10000431-1615888800-1615896000@micde.umich.edu
SUMMARY:Introduction to Deep Neural Networks with Keras/TensorFlow
DESCRIPTION:Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level\, Python interface running on top of multiple neural network libraries\, including the popular library TensorFlow. In this workshop\, participants will learn how to quickly use the Keras interface to perform nonlinear regression and classification with standard fully-connected DNNs\, as well as image classification using Convolutional Neural Networks (CNNs). We will also look at regularization techniques and how to deal with under- and over-fitting. All examples will use Python; some familiarity with Python is recommended. The workshop will be done online via Zoom. We will run the models using Google Colab\, which requires a Google account.
URL:https://micde.umich.edu/event/introduction-to-deep-neural-networks-with-keras-tensorflow-10/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210311T160000
DTEND;TZID=America/Detroit:20210311T170000
DTSTAMP:20260604T231212
CREATED:20230905T171300Z
LAST-MODIFIED:20260403T173218Z
UID:10000459-1615478400-1615482000@micde.umich.edu
SUMMARY:PhD Seminar: Anna Redgrave and Agnit Mukhopadhyay
DESCRIPTION:ANNA REDGRAVE\, GRADUATE STUDENT\, ECOLOGY AND EVOLUTIONARY BIOLOGY & SCIENTIFIC COMPUTING \nBio: Anna Redgrave began her science career as an undergrad\, master’s student\, and lab technician studying developmental biology in zebrafish. She became fascinated by how complicated developmental systems are\, and joined the Wittkopp lab at U-M for her PhD to investigate one mechanism of complicating developmental systems: gene duplication. \nREGULATORY DIVERGENCE OF DUPLICATED GENES: Gene duplication has long been studied as a mechanism of evolution at the genetic level. Duplicated genes introduce redundant protein-coding sequence\, allowing duplicates to acquire novel functions while preserving existing functions. Gene duplication\, however\, also provides a substrate for non-protein coding\, regulatory sequence evolution. Genes are duplicated with varying levels of their native regulatory sequence intact. This prompts the question: how does the degree to which duplication preserves native regulatory sequence affect future evolutionary paths? Here\, I investigate this question by comparing the expression profiles of duplicate genes across many environments in two diverging species of yeast. \n  \nAGNIT MUKHOPADHYAY\, GRADUATE STUDENT\, CLIMATE AND SPACE SCIENCES AND ENGINEERING & SCIENTIFIC COMPUTING \nBio: Agnit is a NASA Earth & Space Sciences Fellow at the Climate and Space Sciences and Engineering department at the University of Michigan\, with a background in Aerospace Engineering. He is co-advised by Drs. Michael Liemohn and Daniel Welling to quantify the nonlinear coupling between the Earth’s atmosphere and it’s near-plasma environment. He loves working with numerical models to assess and predict the impact of extreme natural events on life and technology. \nQUANTIFYING THE IMPACT OF THE AURORA ON SPACE WEATHER: Conjuring a captivating vista of a colourful nightsky\, the aurora borealis (Northern Lights) and australis (Southern Lights) are a byproduct of upper atmospheric ionization by charged particles (plasma) of solar origin. The near-constant drizzling of auroral plasma particles from outer space are excellent drivers of space weather activity caused by solar disruptions like flares and coronal mass ejections that can adversely affect man-made technology like GPS satellites\, electrical power grids and oil pipelines. Using a combination of physics-based models\, data regression tools\, in-situ satellite and ground-based telemetry\, we figure out what forms and drives the aurora\, how these drivers modify the aurora’s electro-chemical atmospheric modification\, and how this system could be predicted during extreme natural events. \n  \n\nRegister via Zoom to immediately receive login information. Note: You may register and join after the event has started. \nThis event is part of MICDE’s Winter 2021 seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/phd-seminar-anna-redgrave-and-agnit-mukhopadhyay/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210311T140000
DTEND;TZID=America/Detroit:20210311T150000
DTSTAMP:20260604T231212
CREATED:20230905T171300Z
LAST-MODIFIED:20230905T171300Z
UID:10000457-1615471200-1615474800@micde.umich.edu
SUMMARY:MICDE Seminar: Warren B. Mori\, Professor\, Physics and Astronomy\, Electrical and Computer Engineering\, University of California\, Los Angeles
DESCRIPTION:WATCH THE RECORDING HERE. \nBio: Warren B. Mori is a Distinguished Professor in the departments of Physics and Astronomy and of Electrical and Computer Engineering a UCLA. He received his BS from UC Berkeley in 1981\, and his M.S. and Ph.D. from UCLA in 1984 and 1987\, respectively. He has been at UCLA from 1981 until today. He served as the Director of the UCLA Institute for Digital Research and Education from 2006 until 2021. His current research interests are in advanced computing\, particle-in-cell simulations of plasmas\, basic plasma physics\, high intensity laser and beam plasma interactions\, plasma based accelerators and light sources\, nonlinear optics of plasmas\, inertial fusion science\, and high energy density science. He is the coauthor of more than 400 publications on a variety of topics in plasma and computational physics. He is a fellow of both APS (1997) and IEEE (2009) and is a current member of both societies. In 1987 he received the International Center for Theoretical Physics Medal for Excellence in Nonlinear Plasma Physics by a Young Researcher was a recipient of the Advanced Accelerator Concepts Prize in 2016 for\, “ his leadership and pioneering contributions in theory and particle-in-cell code simulations of plasma based particle acceleration.” In 2020 he received the APS James Clerk Maxwell prize for\, “leadership in and pioneering contributions to the theory and kinetic simulations of nonlinear processes in plasma-based acceleration and relativistically intense laser and beam plasma interactions. \nPLASMA BASED ACCELERATION AND THE ROLE OF HIGH FIDELITY SIMULATIONS IN ITS DEVELOPMENT\nParticle accelerators are critical components of high energy physics colliders and x-ray free electron lasers (XFELs)\, which are complex and expensive tools for scientific discovery. To reduce the size and cost of these tools there is active research aimed at finding new technologies for compact accelerators. One such possibility is the use of plasma waves which phase velocities near the speed of light that can be excited as wakefields behind intense lasers and particle beams as they traverse tenuous plasmas. These ideas are the basis for the field of plasma based acceleration (PBA). In this talk I will describe how PBA works\, and how high fidelity computer simulations have and are playing a critical role in its development. I will also describe the simulation methods and their associated algorithms. Last\, I will offer some perspectives for the future of plasma based acceleration and the simulation methods that will critical role in this future. Work supported by DOE and NSF.\n \n\nThis seminar is co-presented by the Michigan Institute for Computational Discovery & Engineering and the Michigan Institute for Plasma Science and Engineering. Dr. Mori will be hosted by Professor Alec Thomas\, Professor of Nuclear Engineering and Radiological Sciences\, Electrical Engineering and Computer Science\, and Physics. \nRegister for this event via Zoom to receive an email with the link and passcode to connect. Note: You may register after the event has started. \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. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-warren-mori-professor-physics-and-astronomy-electrical-and-computer-engineering-university-of-california-los-angeles/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2021/02/Warren-Mori.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210310T130000
DTEND;TZID=America/Detroit:20210310T150000
DTSTAMP:20260604T231212
CREATED:20230905T171300Z
LAST-MODIFIED:20230905T171300Z
UID:10000439-1615381200-1615388400@micde.umich.edu
SUMMARY:Software Development For Research: Version Control Principles
DESCRIPTION:Software development and computer programming is increasingly a major part of scientific research. Projects can quickly grow\, and it can be difficult to manage changes\, especially if multiple programmers are editing the same project at once! This workshop will cover Git\, a commonly-used tool for managing coding projects with multiple users\, with features to make or remove edits\, and track information related to those changes. After completing the workshop attendees will have a good understanding of Git workflow and will know how to perform the most common Git operations via the command line. \nThis is part of a series of workshops focused on software and coding from a research perspective.
URL:https://micde.umich.edu/event/software-development-for-research-version-control-principles/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210305T153000
DTEND;TZID=America/Detroit:20210305T170000
DTSTAMP:20260604T231212
CREATED:20230905T171300Z
LAST-MODIFIED:20230905T171300Z
UID:10000456-1614958200-1614963600@micde.umich.edu
SUMMARY:GIS Fundamentals – V (Spatial Database - PostGIS)
DESCRIPTION:This is the fifth workshop in a series of workshops we are offering this semester on the fundamentals of GIS. Each workshop covers one or two key elements of GIS and is somewhat self-contained. The focus is on conceptual details that can provide sufficient preparation for applications\, but we will also touch upon the technical aspects. \n\nIn this workshop we will cover the basic concepts of spatial databases and learn about setting up and using PostGIS\, an open source spatial database built on top of PostgreSQL\, along with R for vector data analysis. We will also touch upon topics such as spatial indexing\, query processing and the capabilities of PostGIS for other data models such as the network and raster data model. This is a hands-on workshop and the instructor will use a Mac machine. If you intend to use a Windows or Linux machine please get in touch with the instructor before the workshop at manishve@umich.edu.
URL:https://micde.umich.edu/event/gis-fundamentals-v-spatial-database-postgis/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210304T160000
DTEND;TZID=America/Detroit:20210304T170000
DTSTAMP:20260604T231212
CREATED:20230905T171259Z
LAST-MODIFIED:20260403T173300Z
UID:10000458-1614873600-1614877200@micde.umich.edu
SUMMARY:PhD Seminar: K G & Ryan Sandberg
DESCRIPTION:K G\, PSYCHOLOGY & SCIENTIFIC COMPUTING \nBio: K is a 4th year PhD candidate in Psychology and Scientific Computing. He has a Bachelors and a Masters degree in Biomedical Engineering and a Masters in Psychology. He works in the multisensory perception lab with Dr. David Brang and studies how multisensory integration occurs in the human brain and their mechanisms. \nEFFECTS OF VISUAL SPEECH ON AUDITORY SPEECH PERCEPTION: For quite some time now\, the notion of different regions in the brain being highly interconnected instead of being segregated into modules has been widely discussed. There are numerous studies that provide evidence for such an effect where distinct regions in the brain responsible for different functionalities work together to create a unified sense of reality. A case in point would be audio-visual integration\, where a person’s auditory stimuli/input is modulated by visual stimuli. One such example is the McGurk effect where the auditory component of one sound\, paired with the visual component of another sound leads to the perception of a third sound. How does this effect happen and what are the ways in which the brain handles integration of these different senses? My research explores questions such as whether the brain integrates information from two different senses in a third\, unrelated region of the brain or whether the sense of integration is just an illusion created by the modulatory effect of one sense on another. In this talk\, I would provide evidence indicating a modulatory effect of visual stimuli on auditory speech perception. Results from complimentary data obtained using two different imaging modalities including intracranial electrocortocographic recordings and functional magnetic resonance imaging would be discussed. \n  \nRYAN SANDBERG\, GRADUATE STUDENT\, APPLIED AND INTERDISCIPLINARY MATHEMATICS & SCIENTIFIC COMPUTING \nBio: I work with Robert Krasny in math and Alec Thomas in NERS on numerical methods in plasma physics\, incorporating tree codes and particle methods in plasma simulation. I also study plasma-based electron and photon acceleration. \nFARRSIGHT: A FORWARD ADAPTIVELY REFINED AND REGULARIZED SEMI-LAGRANGIAN INTEGRAL GPU- AND HEIRARCHICAL TREECODE-ACCELERATED METHOD FOR THE VLASOV-POISSON SYSTEM: We present a new forward semi-Lagrangian particle method for the Vlasov-Poisson (VP) system. Recently developed methods for the VP system include deformable particles and high-order or discontinuous-Galerkin Eulerian methods. In contrast to these\, we do not use any operator splitting and obtain the electric field by summing regularized pairwise particle interactions using a GPU-accelerated tree-code. We remesh and use adaptive mesh refinement to maintain an efficient representation of phase space. We benchmark on several standard test cases including Landau damping and the two-stream instability. We also compare the multi-threaded and single-GPU performance of the method. \n\nThis event is part of MICDE’s Winter 2021 seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nRegister via Zoom to immediately receive login details for this event. Note: You may register and join after the event has started. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/phd-seminar-kg-ryan-sandberg/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210301T130000
DTEND;TZID=America/Detroit:20210301T140000
DTSTAMP:20260604T231212
CREATED:20230905T171259Z
LAST-MODIFIED:20230905T171259Z
UID:10000450-1614603600-1614607200@micde.umich.edu
SUMMARY:MICDE Seminar: Santo Fortunato\, Director of the Indiana University Network Science Institute (IUNI)\, Professor\, School of Informatics\, Computing\, and Engineering (SICE)\, Indiana University at Bloomington
DESCRIPTION:About Dr. Fortunato: Santo Fortunato is the Director of the Indiana University Network Science Institute (IUNI) and a faculty at Luddy School of Informatics\, Computing and Engineering. Previously he was professor of complex systems at the Department of Computer Science of Aalto University\, Finland. Prof. Fortunato got his PhD in Theoretical Particle Physics at the University of Bielefeld In Germany. He then moved to the field of complex systems\, via a postdoctoral appointment at Luddy School of Informatics\, Computing and Engineering of Indiana University. His current focus areas are network science\, especially community detection in graphs\, computational social science\, science of science\, climate change. His research has been published in leading journals\, including Nature\, Science\, PNAS\, Physical Review Letters\, Reviews of Modern Physics\, Physics Reports and has collected over 33\,000 citations (Google Scholar). His review article Community detection in graphs (Physics Reports 486\, 75-174\, 2010) is one of the best known and most cited papers in network science. He received the Young Scientist Award for Socio- and Econophysics 2011\, a prize given by the German Physical Society\, for his outstanding contributions to the physics of social systems. He is the Founding Chair of the International Conference on Computational Social Science (IC2S2) and Chair of Networks 2021\, the first merger of the NetSci and the Sunbelt conferences\, possibly the largest ever event in network science. \nCOMMUNITY DETECTION IN NETWORKS: Complex systems typically display a modular structure\, as modules are easier to assemble than the individual units of the system\, and more resilient to failures. In the network representation of complex systems\, modules\, or communities\, appear as subgraphs whose nodes have an appreciably larger probability to get connected to each other than to other nodes of the network. In this talk I will discuss three main issues in this area. I will address the limits of the most popular class of clustering algorithms\, those based on the optimization of a global quality function\, like modularity maximization. Testing algorithms is probably the single most important issue of network community detection\, as it implicitly involves the concept of community\, which is ill-defined. I will discuss the importance of using realistic benchmark graphs with built-in community structure. Finally\, I will introduce an increasingly popular post-processing technique that allows to “average” the results of stochastic clustering algorithms\, improving their quality: consensus clustering. \n\nWatch the full webinar recording. \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. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-santo-fortunato-director-of-the-indiana-university-network-science-institute-iuni-professor-school-of-informatics-computing-and-engineering-sice-indiana-university-at-blooming/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2021/01/Santo-Fortunato.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210226T140000
DTEND;TZID=America/Detroit:20210226T153000
DTSTAMP:20260604T231212
CREATED:20230905T171259Z
LAST-MODIFIED:20230905T171259Z
UID:10000435-1614348000-1614353400@micde.umich.edu
SUMMARY:Introduction to Stata: Data Manipulation
DESCRIPTION:This is a series of workshops designed to introduce participants to the Stata software. No prior experience with Stata is required. The sections are:\n\nSection 1: The Basics of Stata – Interacting with Stata and working with data sets. (2/22 2-3:30)\nSection 2: Data Management – The basics of maintaining and exploring a data set. (2/24 2-3:30)\nSection 3: Data Manipulation – Creating and modifying variables and other ways of manipulating your data. (2/26 2-3:30)\n\nYou do not need to attend all sessions; however\, the sessions build on each other and it will be assumed you are familiar with the material in earlier sessions. The workshop materials can be found at https://cscar.github.io/workshop-stata-intro/ for review.\n\nIt is strongly encouraged that you have Stata available on your local computer\, though not required. You may access Stata through midesktop (https://midesktop.umich.edu/) if needed.
URL:https://micde.umich.edu/event/introduction-to-stata-data-manipulation/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210225T160000
DTEND;TZID=America/Detroit:20210225T170000
DTSTAMP:20260604T231212
CREATED:20230905T171259Z
LAST-MODIFIED:20230905T171259Z
UID:10000453-1614268800-1614272400@micde.umich.edu
SUMMARY:Ph.D. Seminar: Anil Yildirim & Jiale Tan
DESCRIPTION:ANIL YILDIRIM\, GRADUATE STUDENT\, AEROSPACE ENGINEERING & SCIENTIFIC COMPUTING \nBio: Anil Yildirim is a PhD candidate in Aerospace Engineering and Scientific Computing. His research focuses on the development and application of robust computational tools in the context of multidisciplinary design optimization for aircraft configurations. \nROBUST AND HIGH-PERFORMANCE TOOLS FOR MULTIDISCIPLINARY DESIGN OPTIMIZATION: The development of future sustainable aircraft heavily relies on the design and integration of advanced propulsion systems. However\, the design of these systems are challenging due to the tightly coupled interactions between the aerodynamic and the propulsion disciplines. My research focuses on enabling these advanced technologies using aeropropulsive design optimization\, in which the aerodynamic and propulsion system designs are optimized in a coupled manner. In this process\, I use multiple robust and high-performance computational tools including the computational fluid dynamics (CFD) solver we have been developing in the MDO Lab at the University of Michigan. In this talk\, I will cover some recent advancements in the field of CFD-based aeropropulsive design optimization and the computational methodologies we have been using for this work. \n  \nJIALE TAN\, GRADUATE STUDENT\, EPIDEMIOLOGY & SCIENTIFIC COMPUTING \nBio: Jiale is a second year Phd student working with Prof. Rafael Meza in Epidemiology. His interest is to apply computational skills to public health challenges so that he can develop and apply modeling techniques for infectious and noninfectious diseases\, including for viral infections like HIV and HCV\, and eventually use them for modeling non-communicable diseases that disproportionately affect global health like cancer. \nMARKOV MULTISTATE TRANSITION MODEL ON ELECTRONIC NICOTINE DELIVERY SYSTEMS AND TRADITIONAL CIGARETTES: Electronic nicotine delivery systems (ENDS) have dramatically changed the landscape of tobacco products patterns in the USA since 2011. The impact of ENDS use on traditional cigarettes smoking remains a topic of considerable debate. A Markov multistate transition model was used to estimate transition rates (Hazard rate) between ENDS and cigarette use states (25 use states); never user\, non-current experimental user\, non-current regular user\, current experimental user\, and current regular user for each product. A 25×25 transition matrix was generated from this model. Parallel computations using 150 processors was used to estimate the transition rates. The Population Assessment of Tobacco and Health study\, which includes longitudinal data from 11\,475 youth of ages 12 to 24 years from 2013-2018 was used to calibrate the model. The hazard estimates show the patterns of ENDS and cigarette use experimentation and transition to regular use. Next steps will assess the impact of different sociodemographic covariates (age\, sex\, race\, education\, household income) on the estimated transition rates. \n\nThis event is part of MICDE’s Winter 2021 seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nThis webinar was not recorded for public distribution. \nQuestions? Email MICDE-events@umich.edu \n\nAdditional research image from Anil Yildirim.
URL:https://micde.umich.edu/event/ph-d-seminar-anil-yildirim-jiale-tan/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,hpc-events,MICDE PhD Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210225T160000
DTEND;TZID=America/Detroit:20210225T170000
DTSTAMP:20260604T231212
CREATED:20230905T171259Z
LAST-MODIFIED:20230905T171259Z
UID:10000455-1614268800-1614272400@micde.umich.edu
SUMMARY:CoreLogic property data
DESCRIPTION:The University of Michigan library system has licensed a large data set containing real estate transactions\, deeds\, and property tax records for the United States.  The data were collected by the commercial vendor CoreLogic\, and our license allows UM researchers to use the data for research purposes.  These data are of potential interest to researchers in many fields\, as they capture spatial and temporal real estate market conditions\, taxing practices\, and the physical states of millions of residential structures in the US.\n\n \nIn this workshop\, participants will learn to create geographical subsets of the data\, seamlessly integrate it in workflow\, and see examples of research questions where the data can be useful. Participants should know Python and R.
URL:https://micde.umich.edu/event/corelogic-property-data-2/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210224T140000
DTEND;TZID=America/Detroit:20210224T170000
DTSTAMP:20260604T231212
CREATED:20230905T171259Z
LAST-MODIFIED:20230905T171259Z
UID:10000016-1614175200-1614186000@micde.umich.edu
SUMMARY:Using GPUs with Python
DESCRIPTION:Python is the Lingua Franca of Data today and is being increasingly used in scientific computations. This workshop introduces Python GPU tools for porting and writing code that runs on GPUs. The primary tools\, Numba and CuPy\, are presented with examples. This workshop is presented by Kristopher Keipert of NVIDIA.\nThis event is open to students\, faculty\, and staff within the University of Michigan community. A Jupyter notebook is used along with a set of lecture slides. The workshop will use online tools\, so there is no need to install any software ahead of time.\nThis event is brought to you by the Michigan Institute for Computational Discovery and Engineering\, and Consulting for Statistics\, Computing & Analytics Research at the University of Michigan in partnership with NVIDIA.\nSpace is limited\, register today!
URL:https://micde.umich.edu/event/using-gpus-with-python-3-2/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210224T140000
DTEND;TZID=America/Detroit:20210224T170000
DTSTAMP:20260604T231212
CREATED:20230905T171259Z
LAST-MODIFIED:20230905T171259Z
UID:10000454-1614175200-1614186000@micde.umich.edu
SUMMARY:Using GPUs with Python
DESCRIPTION:Python is the Lingua Franca of Data today and is being increasingly used in scientific computations. This workshop introduces Python GPU tools for porting and writing code that runs on GPUs. The primary tools\, Numba and CuPy\, are presented with examples. Back by popular demand\, this workshop is presented by Kristopher Keipert of NVIDIA. \nThis event is open to students\, faculty\, and staff within the University of Michigan community. A Jupyter notebook is used along with a set of lecture slides. The workshop will use online tools\, so there is no need to install any software ahead of time. \nThis event is brought to you by the Michigan Institute for Computational Discovery and Engineering\, and Consulting for Statistics\, Computing & Analytics Research at the University of Michigan in partnership with NVIDIA. \nSpace is limited\, register today!
URL:https://micde.umich.edu/event/using-gpus-with-python-4/
LOCATION:Your Desktop
CATEGORIES:Featured Events,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210224T140000
DTEND;TZID=America/Detroit:20210224T153000
DTSTAMP:20260604T231212
CREATED:20230905T171259Z
LAST-MODIFIED:20230905T171259Z
UID:10000436-1614175200-1614180600@micde.umich.edu
SUMMARY:Introduction to Stata: Data Management
DESCRIPTION:This is a series of workshops designed to introduce participants to the Stata software. No prior experience with Stata is required. The sections are:\n\nSection 1: The Basics of Stata – Interacting with Stata and working with data sets. (2/22 2-3:30)\nSection 2: Data Management – The basics of maintaining and exploring a data set. (2/24 2-3:30)\nSection 3: Data Manipulation – Creating and modifying variables and other ways of manipulating your data. (2/26 2-3:30)\n\nYou do not need to attend all sessions; however\, the sessions build on each other and it will be assumed you are familiar with the material in earlier sessions. The workshop materials can be found at https://cscar.github.io/workshop-stata-intro/ for review.\n\nIt is strongly encouraged that you have Stata available on your local computer\, though not required. You may access Stata through midesktop (https://midesktop.umich.edu/) if needed.
URL:https://micde.umich.edu/event/introduction-to-stata-data-management/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210224T130000
DTEND;TZID=America/Detroit:20210224T150000
DTSTAMP:20260604T231212
CREATED:20230905T171300Z
LAST-MODIFIED:20230905T171300Z
UID:10000438-1614171600-1614178800@micde.umich.edu
SUMMARY:Software Development For Research: Best Practices for Coding Styles
DESCRIPTION:Software development and computer programming is increasingly a major part of scientific research. Having a consistent coding style and following basic best practices used in the industry can help make your code easier to read and manage\, both internally in your teams and for public code projects available to other researchers. This workshop will cover some general guidelines and suggestions to clean up your coding style. Attendees will learn helpful tips for computer coding and how to make their code readable to other collaborators. \nThis is part of a series of workshops focused on software and coding from a research perspective.
URL:https://micde.umich.edu/event/software-development-for-research-best-practices-for-coding-styles/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210223T100000
DTEND;TZID=America/Detroit:20210223T120000
DTSTAMP:20260604T231212
CREATED:20230905T171258Z
LAST-MODIFIED:20230905T171258Z
UID:10000430-1614074400-1614081600@micde.umich.edu
SUMMARY:Image Segmentation using Deep Learning with FastAI
DESCRIPTION:Like many image processing problems\, deep learning has brought many effective solutions to the task of image segmentation. This workshop will introduce you to the methods used in image segmentation\, demonstrate how to prepare your own segmentation masks using Matlab\, and guide you through performing image segmentation using the FastAI [fast.ai] Python library\, which is built on the deep learning library PyTorch. Some familiarity with Python is expected\, but no previous experience with FastAI or PyTorch is needed. The workshop will be done online via Zoom. We will run the code using Google Colab (with free-to-use GPUs)\, which requires a Google account.
URL:https://micde.umich.edu/event/image-segmentation-using-deep-learning-with-fastai-2/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210222T140000
DTEND;TZID=America/Detroit:20210222T153000
DTSTAMP:20260604T231212
CREATED:20230905T171258Z
LAST-MODIFIED:20230905T171258Z
UID:10000434-1614002400-1614007800@micde.umich.edu
SUMMARY:Introduction to Stata: The Basics of Stata
DESCRIPTION:This is a series of workshops designed to introduce participants to the Stata software. No prior experience with Stata is required. The sections are: \nSection 1: The Basics of Stata – Interacting with Stata and working with data sets. (2/22 2-3:30)\nSection 2: Data Management – The basics of maintaining and exploring a data set. (2/24 2-3:30)\nSection 3: Data Manipulation – Creating and modifying variables and other ways of manipulating your data. (2/26 2-3:30) \nYou do not need to attend all sessions; however\, the sessions build on each other and it will be assumed you are familiar with the material in earlier sessions. The workshop materials can be found at https://cscar.github.io/workshop-stata-intro/ for review. \nIt is strongly encouraged that you have Stata available on your local computer\, though not required. You may access Stata through midesktop (https://midesktop.umich.edu/) if needed.
URL:https://micde.umich.edu/event/introduction-to-stata-the-basics-of-stata/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210218T160000
DTEND;TZID=America/Detroit:20210218T170000
DTSTAMP:20260604T231212
CREATED:20230905T171258Z
LAST-MODIFIED:20230905T171258Z
UID:10000452-1613664000-1613667600@micde.umich.edu
SUMMARY:Ph.D Seminar: Matthew Duschenes & Yi Zhu
DESCRIPTION:MATTHEW DUSCHENES\, GRADUATE STUDENT\, APPLIED PHYSICS & SCIENTIFIC COMPUTING \nBio: I am in my third year of the Applied Physics & Scientific Computing Ph.D. programs\, after completing a master’s in theoretical physics in my home country of Canada. As a member of Dr. Krishna Garikipati’s Computational Physics group\, I am currently working on data driven modelling and am collaborating with several groups on applying these graph theoretic approaches to various systems of interest. \nGRAPH THEORETIC APPROACHES FOR PHYSICAL SYSTEMS: Numerical analyses of physical systems are conventionally performed using direct numerical simulations\, that have proven highly successful\, yielding high fidelity solutions to very high dimensional problems\, such as boundary value problems with upwards of tens of millions of degrees of freedom. However\, there is always a balance to be met between the desire for higher accuracy and additional physics to be modeled\, and the complexity\, interpret-ability and ease of representation of such solutions. To aid in this dilemma\, I will be introducing a novel graph theoretic approach\, allowing for lower dimensional\, reduced order models to be produced\, given small amounts of high fidelity data. In this talk I will explain how such an approach allows for an intuitive representation of the states of a systems\, and how it is possible to use a non-local calculus\, allowing for rigorous operators and equations to be defined on the graph. I will then be discussing some implementation details\, and convey the generality\, validity\, and future applications of this framework through some example results from collaborations. \nYI ZHU\, GRADUATE STUDENT\, CIVIL AND ENVIRONMENTAL ENGINEERING & SCIENTIFIC COMPUTING \n \nBio: Yi is a 3rd year PhD candidate in Civil and Environmental Engineering & Scientific Computation. His research focuses on simulation\, design\, and fabrication of active origami systems for engineering devices\, and is particularly focused on micro-scale shape morphing systems inspired by origami. \nSIMULATION AND DESIGN OF MICRO-ORIGAMI SYSTEMS: In this talk\, we will introduce some recent advancement in the simulation and the design of micro-origami systems. We will discuss the micro-origami structures we fabricated and the rapid simulation framework we developed to capture the behaviors of these active origami. We will focus on the simulation framework and demonstrate how we can capture the thermo-mechanically coupled folding behavior and contacts between origami panels effectively and rapidly. Finally\, we will introduce some ongoing work on extracting origami design principle with interpretable machine learning\, which demonstrates how we can use the simulation framework to create better origami design. \n  \n  \n\nThis event is part of MICDE’s Winter 2021 seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/ph-d-seminar-matthew-duschenes-yi-zhu/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210216T150000
DTEND;TZID=America/Detroit:20210216T160000
DTSTAMP:20260604T231212
CREATED:20230905T171258Z
LAST-MODIFIED:20230905T171258Z
UID:10000428-1613487600-1613491200@micde.umich.edu
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
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210212T150000
DTEND;TZID=America/Detroit:20210212T163000
DTSTAMP:20260604T231212
CREATED:20230905T171258Z
LAST-MODIFIED:20230905T171258Z
UID:10000448-1613142000-1613147400@micde.umich.edu
SUMMARY:GIS Fundamentals – IV (Digitization)
DESCRIPTION:This is the fourth workshop in a series of workshops we are offering this semester on the fundamentals of GIS. Each workshop covers one or two key elements of GIS and is self-contained. The focus is on conceptual details that can provide sufficient preparation for applications\, but we will also touch upon the technical aspects. Most workshops will have at least one hands-on exercise. Typically\, each workshop is divided into one hour of lecture-style presentation and half an hour of hands-on exercises. Unless mentioned otherwise\, we will use R. \nIn many fields old paper maps and images provide historical and time series information and need to be digitized with spatially explicit coordinates. In this workshop we will develop a basic understanding of how to efficiently digitize paper maps and images that contain spatial information. We will use ArcGIS and R for the hands-on part.
URL:https://micde.umich.edu/event/gis-fundamentals-iv-digitization/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210211T160000
DTEND;TZID=America/Detroit:20210211T163000
DTSTAMP:20260604T231212
CREATED:20230905T171258Z
LAST-MODIFIED:20230905T171258Z
UID:10000451-1613059200-1613061000@micde.umich.edu
SUMMARY:Ph.D Seminar: Saibal De\, Applied and Interdisciplinary Mathematics & Scientific Computing
DESCRIPTION:Bio: Saibal De is a 5th year PhD candidate in Applied and Interdisciplinary Mathematics. His research involves using high-performance computing and novel algorithms for accelerating physics-based simulation frameworks\, and developing faithful reduced-order models of black-box high-fidelity simulations. \nTENSOR METHODS FOR DATA COMPRESSION: With the advancement of computing software and hardware\, physics-based simulations have gained notoriety in many scientific and industrial applications due to their highly accurate prediction capabilities. However\, in addition to being computationally expensive\, even a single of these high-fidelity simulations produce massive amounts of data. Storing and processing all these data thus requires novel approaches. In this talk\, I will present how we can use tensor factorization methods for compressing scientific data\, leading to dramatic savings in disk-space usage. Towards the end of the talk\, I’ll also touch upon how we can potentially construct reduced-order models out of these compressed datasets. \n\nThis event is part of MICDE’s Winter 2021 seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/ph-d-seminar-saibal-de-applied-and-interdisciplinary-mathematics-scientific-computing/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/Headshot-Saibal-De.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210210T100000
DTEND;TZID=America/Detroit:20210210T120000
DTSTAMP:20260604T231212
CREATED:20230905T171258Z
LAST-MODIFIED:20230905T171258Z
UID:10000444-1612951200-1612958400@micde.umich.edu
SUMMARY:Introduction to SPSS: Basic Statistical Analysis
DESCRIPTION:Each section will go over one chapter from the materials at https://cscar.github.io/workshop-spss/ \nSection 1: Basics of SPSS (1/20\, 10am – 12pm) \nSection 2: Variables (1/27\, 10am – 12pm) \nSection 3: Data Management (2/3\, 10am – 12pm) \nSection 4: Basic Statistical Analysis (2/10\, 10am – 12pm) \nIt is strongly encouraged to have SPSS installed on your machine. If you are accessing SPSS through AppsAnywhere on Virtual Sites\, then you will need to set up a link to your Google Drive\, Box\, or Dropbox storage.
URL:https://micde.umich.edu/event/introduction-to-spss-basic-statistical-analysis/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210209T160000
DTEND;TZID=America/Detroit:20210209T170000
DTSTAMP:20260604T231212
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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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210204T110000
DTEND;TZID=America/Detroit:20210204T120000
DTSTAMP:20260604T231212
CREATED:20230905T171258Z
LAST-MODIFIED:20230905T171258Z
UID:10000407-1612436400-1612440000@micde.umich.edu
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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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210203T153000
DTEND;TZID=America/Detroit:20210203T170000
DTSTAMP:20260604T231212
CREATED:20230905T171258Z
LAST-MODIFIED:20230905T171258Z
UID:10000447-1612366200-1612371600@micde.umich.edu
SUMMARY:GIS Fundamentals – III (Geocoding)
DESCRIPTION:This is the third workshop in a series of workshops we are offering this semester on the fundamentals of GIS. Each workshop covers one or two key elements of GIS and is self-contained. The focus is on conceptual details that can provide sufficient preparation for applications\, but we will also touch upon the technical aspects. Most workshops will have at least one hands-on exercise. Typically\, each workshop is divided into one hour of lecture-style presentation and half an hour of hands-on exercises. Unless mentioned otherwise\, we will use R. \n\nGeocoding (or sometimes reverse geocoding) is often a very first step in many geospatial analyses. There are many options available for geocoding with different degrees of accuracy. A basic understanding of the process helps you in choosing the best option. We will use R and ArcGIS for exercises
URL:https://micde.umich.edu/event/gis-fundamentals-iii-geocoding/
LOCATION:Your Desktop
CATEGORIES:Workshops
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