Michigan Institute for Computational Discovery and Engineering

Sliding into Slurm: An early look at U-M's new high-performance computing environment
2019-04-25 13:00 - 16:00, 2019-04-17 13:00 - 16:00, 2019-04-03 13:00 - 16:00 (America/Detroit) | Modern Languages Building (MLB), Room 2001A
This workshop will provide a brief overview of the the new HPC environment and is intended for current Flux and Armis users. We will use the temporary Beta HPC cluster to demonstrate how jobs will be submitted and managed under the new Great Lakes, Armis2, and Lighthouse clusters available later this year.
There are many differences between the familiar Flux environment and that of the new HPC clusters, including a new batch scheduling system, a new interactive batch job environment, a new HPC web portal, a new module environment, and a new on-demand-only job accounting system.
We will cover these differences in the workshop, and provide hands-on training in creating and running job submission scripts in the new HPC environment. Students are expected to be conversant with the Linux command line and have experience in creating, submitting, and troubleshooting PBS batch scripts.

Hands-on session with Python Statsmodels
2019-04-23 14:00 - 16:00 | Rackham Building, Earl Lewis Room, 3rd Floor East, 915 E. Washington St., Ann Arbor, MI, 48109, United States
This semester, a series of seven workshops was offered by CSCAR illustrating various approaches to statistical analysis using the Python Statsmodels package. In this session, we will provide an open forum for people to get hands-on assistance in this environment. Several data sets and suggested analysis goals will be provided, but participants are also welcome to come with their own data.
Attendance at previous workshops in this series is not required. The room for this meeting will not have computers, so participants must bring their own laptop. If desired, the instructor can assist with installation of the relevant packages (all of which are free and open source).

MICDE Seminar: Guy A. E. Vandenbosch, Electrical Engineering, KU Leuven
2019-04-17 16:00 - 17:00 | 1008 EECS, 1301 Beal Ave., Ann Arbor, MI, 48109, United States
Bio: Guy A. E. Vandenbosch is a Professor of Electrical Engineering at the Katholieke Universiteit Leuven in Leuven, Belgium. He received the M.S. and Ph.D. degrees in Electrical Engineering from KU Leuven in 1985 and 1991, respectively.
He was a research and teaching assistant from 1985 to 1991 with the Telecommunications and Microwaves section of the Katholieke Universiteit Leuven, where he worked on the modeling of microstrip antennas with the integral equation technique. From 1991 to 1993, he held a postdoctoral research position, in 1993 he became a Lecturer, and since 2005 he’s been a Full Professor at the same university. Guy Vandenbosch has taught or teaches courses on “Electromagnetic Waves”, “Antennas”, “Electromagnetic Compatibility”, “Fundamentals of Communication and Information Theory”, “Electrical Engineering, Electronics, and Electrical Energy”, and ”Digital Steer- and Measuring Techniques in Physics”.
Prof. Vandenbosch’s research interests are in the area of electromagnetic theory, computational electromagnetics, planar antennas and circuits, nano-electromagnetics, EM radiation, EMC, and bio-electromagnetics. His work has been published in over 300 papers in international journals and has led to over 370 papers at international conferences. He was a member of the Management Committees‘ of the consecutive European COST actions on antennas between 1993 and 2017, where he was leading the working group on modeling and software for antennas.
On a Boundary Integral Equation Approach Modeling the Interaction of Light with Nanostructured Metallic Objects
Computational Electromagnetics (CEM) is the technology modeling the interaction of electromagnetic waves (EM waves) with physical objects and their surroundings. This technology has been demonstrated to be a key element in the design of, e.g., modern antennas, waveguiding/shaping devices, etc..It has been playing a pivotal role in forging modern communication systems, and therefore was, is and will be greatly impacting peoples’ daily life. However, despite of all these successes, very recent experiments on the interaction of light (EM waves at optical frequencies) with deep-nanoscale metallic structures suggest the need of a paradigm shift in the classic CEM algorithms, where a more refined material model is required. As the very first step in this direction, we combine the dynamics of classical EM waves with the semi-classical hydrodynamic motion of free electrons in metals. The problem is formulated in the framework of Boundary Integral Equations (BIEs) and subsequently solved by the Method of Moments (MoM) algorithm. This research contributes to potentially bridging the computational gap between the classical macroscopic world and the quantum mechanical microscopic world, and provides an essential tool for chemists and physicists to understand new physics in the nanoscopic world.
Prof. Vandenbosch is being hosted by Prof. Michielssen (Electrical Engineering). If you would like to meet with him during his visit, please send an email to micde-events@umich.edu. If you are a student or postdoc and would like to join him for lunch on Thurs., April 18, please RSVP here by April 16.

Statistical analysis with missing data in Python
2019-04-16 14:00 - 16:00 | Rackham Building, Earl Lewis Room, 3rd Floor East, 915 E. Washington St., Ann Arbor, MI, 48109, United States
Missing data arise in many fields of research, and a large body of statistical tools has been developed to facilitate statistical analysis in the presence of missing data. Here we focus mainly on multiple imputation, which is a broadly-applicable approach for working with missing data. We will illustrate through several case studies how multiple imputation allows certain types of missing data to be rigorously accounted for, while preserving the flexibility to use a variety of familiar statistical tools to account for other aspects of the data.
The analyses presented in this workshop will be performed in Python using the Statsmodels package. All software tools covered in this workshop are free and open source.

Web Scraping with Python
2019-04-16 09:30 - 12:00 | Modern Languages Building (MLB), Room 2001A
This workshop will provide an overview of how to scrape data from html pages and website APIs using Python. This will mostly be accomplished using the requests, beautifulsoup, retry modules and the browser developer tools. The workshop is intended for users with basic Python knowledge. Anaconda Python 3.5 will be used.

Open Source GIS and Geometric Network Analysis
2019-04-12 13:30 - 17:00 | Rackham Building, Earl Lewis Room, 3rd Floor East, 915 E. Washington St., Ann Arbor, MI, 48109, United States
This workshop will cover GIS concepts and techniques for analyzing geometric networks embedded in geographical space. We will mainly focus on road network, but the ideas and techniques apply to similar network such as water and electric distribution and gas pipelines. We will primarily use open source tools in R and QGIS, but will also touch upon the functionalities in ArcGIS.
You should know the introductory concepts and tools in GIS and should be familiar with R and QGIS.

The 2019 MICDE Symposium
2019-04-10 08:00 - 17:00 | Michigan League, 911 N. University, Ann Arbor, MI, 48104, United States
The Michigan Institute for Computational Discovery and Engineering 2019 Symposium will feature eminent scientists from around the world and the U-M campus.

SPEAKERS

Marsha Berger
Professor, Computer Science and Mathematics
New York University Courant Institute of Mathematical Sciences

Marisa Eisenberg
Associate Professor, Epidemiology and Mathematics
University of Michigan

Carla Gomes
Professor and Director, Institute for Computational Sustainability
Cornell University

Jan Hesthaven
Dean, School of Basic Sciences
EPFL, Switzerland

Necmiye Ozay
Assistant Professor, Electrical Engineering and Computer Science
University of Michigan

Stephen Wolfram
Founder and CEO, Wolfram Research
Creator of Mathematica

A poster competition will be held, open to post-docs and graduate students.
More information will be posted here as it becomes available. Also see micde.umich.edu/symposium19[/vc_column_text][/vc_column][/vc_row]

Mediation analysis in Python
2019-04-09 14:00 - 16:00 | Rackham Building, Earl Lewis Room, 3rd Floor East, 915 E. Washington St., Ann Arbor, MI, 48109, United States
Mediation analysis is a set of tools for exploring hypotheses about causal pathways, with a special focus on differentiating “direct” from “mediated” associations between an exposure and an outcome. Many approaches to mediation analysis are based on regression analysis.
In this workshop, we will cover some of the basic ideas behind regression-based mediation analysis, and show how this type of analysis can be performed in Python using the Statsmodels package. All software tools covered in this workshop are free and open source.

MICDE Seminar: Prith Banerjee, Chief Technology Officer, ANSYS, Inc.
2019-04-04 12:00 - 13:00 | 1005 EECS, 1301 Beal Ave, Ann Arbor, MI, 48109, United States
Bio: Prith Banerjee is the Chief Technology Officer of ANSYS where he is responsible for leading the evolution of ANSYS’ Technology strategy and champion the company’s next phase of innovation and growth. He also serves on the Board of Directors of Cray, Inc. and Cubic Corporation. Previously he used to be Senior Client Partner at Korn Ferry where he was responsible for IOT and Digital Transformation in the Global Industrial Practice. Formerly, he was Executive Vice President, Chief Technology Officer of Schneider Electric. Previously, he was Managing Director of Global Technology Research and Development at Accenture. Formerly, he was Chief Technology Officer and Executive Vice President of ABB. Earlier, he was Senior Vice President of Research at HP and Director of HP Labs. Formerly, he was Dean of the College of Engineering at the University of Illinois at Chicago. Formerly, he was the Walter P. Murphy Professor and Chairman of Electrical and Computer Engineering at Northwestern University. Prior to that, he was Professor of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. In 2000, he founded AccelChip, a developer of products for electronic design automation, which was acquired by Xilinx Inc. in 2006. During 2005-2011, he was Founder, Chairman and Chief Scientist of BINACHIP Inc., a developer of products in electronic design automation. He was listed in the FastCompany list of 100 top business leaders in 2009. He is a Fellow of the AAAS, ACM and IEEE, and a recipient of the 1996 ASEE Terman Award and the 1987 NSF Presidential Young Investigator Award. He received a B.Tech. in electronics engineering from the Indian Institute of Technology, Kharagpur, and an M.S. and Ph.D. in electrical engineering from the University of Illinois, Urbana.
FUTURE OF SIMULATION-BASED PRODUCT INNOVATION IN THE DIGITAL WORLD
Digital transformation refers to the use of digital technologies such as cloud, IOT, AI/ML, to transform the way business is executed. Digital transformation is impacting every industry – automotive, agriculture, logistics, healthcare and manufacturing. In this talk we will discuss how Digital Transformation is disrupting the manufacturing industry. In the past, engineered products were designed with mechanical and electrical CAD tools, simulated and validated for correctness with CAE tools, prototypes were fabricated and tested, and products were then manufactured at scale in factories. This process required long product cycles often requiring years to build a new product. Today, one can use unlimited computing and storage available from the cloud to do generative design to explore 10,000 design choices in near real-time, verify these products accurately through simulation (eliminating the need to build physical prototypes) and manufacture the products using additive manufacturing and factory automation (Industrie 4.0). In the past, simulation tools were used to model specific physics such as mechanical structures, or fluid dynamics, or electromagnetic interactions by solving second order partial differential equations using numerical methods. Today the simulation tools are being used to solve multi-physics problems (fluid-structure-electromagnetics interactions) at scale using the most complex solvers. These products once built are connected using IOT so that manufacturers have 24/7 connectivity to all these products, and can monitor how customers are using these product; this helps the manufacturers design future generations of products even faster. The connectivity also allows them to monitor the products for failures using predictive analytics, and service these products remotely. In this talk I will discuss how the ANSYS Pervasive Simulation Platform allows hardware and software developers to work together in all phases of a product development lifecycle including Ideation, Design Manufacturing, and Operations. Simulation tools are increasingly being used in the ideation phase by designers to get real-time simulation of the parts as soon as they are being conceptualized. This has resulted in shorter, agile product cycles even for hardware products allowing innovative products to be designed and produced in months and days. Companies are increasingly using model-based systems engineering concepts to take high level requirements of products, and manage the complexity of product design using concepts of Digital Threads, Digital Twins, and Digital Continuity. We will touch upon some future directions of simulation-based product innovation around AI/Machine Learning, Multi-physics Platforms, Hyperscale Simulation, and the convergence of the Digital and Physical worlds using IOT and Augmented Reality/Virtual Reality.

Go for data processing 1/2/3
2019-04-02 14:00 - 16:00, 2019-03-26 14:00 - 16:00, 2019-03-19 14:00 - 16:00 | Rackham Building, Earl Lewis Room, 3rd Floor East, 915 E. Washington St., Ann Arbor, MI, 48109, United States
This is a three-session workshop on the use of Go for data processing. Go is an open source language developed for general-purpose programming. It is not more difficult to learn and use than a high-level scripting language like Python, but it is strongly typed, statically compiled, and provides native support for concurrency, leading to much better performance for many common tasks. In this series of workshops, we introduce Go as a tool for data processing. No prior exposure to Go is expected, but participants should have some programming background. Free and open source tools for Go are available for all common platforms.
Participants should bring a laptop if they want to work with the examples during the presentation, but this is optional.
Session 1: March 19, 2:00pm – 4:00pm
Session 2: March 26, 2:00pm – 4:00pm
Session 3: April 2, 2:00pm – 4:00pm
Note: Interested participants only need to register with the 1st session.

Understanding How the Brain Processes Music Through the Bach Trio Sonatas
2019-04-01 15:30 - 17:00 | Hill Auditorium, 825 N University Ave, Ann Arbor, MI 48109, Ann Arbor, MI, 48104, United States
This event is open to the public.
Daniel Forger, Professor of Mathematics and Computational Medicine and Bioinformatics
James Kibbie, Professor of Music and Chair of the Organ Department, University Organist
Caleb Mayer, Graduate Student Research Assistant (Mathematics)
Sarah Simko, Graduate Student Research Assistant (Organ Performance)
With support from the Data Science for Music Challenge Initiative through MIDAS, the team is taking a big data approach to understanding the patterns and principles of music. The project is developing and analyzing a library of digitized performances of the Trio Sonatas for organ by Johann Sebastian Bach, applying novel algorithms to study the music structure from a data science perspective. Organ students from the School of Music, Theatre & Dance will demonstrate how the Frieze Memorial Organ in Hill Auditorium is used to create big data files of live performances. The team will discuss how its analysis compares different performances to determine features that make performances artistic, as well as the common mistakes performers make. The digitized performances will be shared with researchers and will enable research and pedagogy in many disciplines, including data science, music performance, mathematics and music psychology.

Introduction to Stata
2019-03-22 09:30 - 16:00 | Modern Languages Building (MLB), Room 2001A
Topics:

By the end of the workshop, participants will be able to:

Work with Stata, including using Do-files and using the help system.
Get data into Stata and manage your data files
Establish familiarity with your data
Clean the data to prepare it for analysis
Check for basic errors in the data
Generate new variables or manipulate existing variables
Merge or reshape the data.
Produce summary tables and descriptive statistics.

Note: This is a full day workshop. To get the most out of it, please plan to stay for the entire class.

(Topics subject to change)

Doing more with RStudio
2019-03-20 15:30 - 17:00 | Modern Languages Building (MLB), Room 2001A
This talk will serve as an demonstration of what RStudio can offer for those that do not use it, as well as a showcase for more advanced use for those who use it only for scripting purposes.
Topics include but are not limited to:

Scripting shortcuts
Customization
Using Projects
Document generation
Addins
Package Development
Debugging and Profiling
Version Control

While this is more of a demo than a workshop, attendees are encouraged to try some things out and explore as we go along.
If you have questions about this workshop, please send an email to micl@umich.edu

Introduction to Deep Neural Networks with Keras/TensorFlow
2019-03-19 10:00 - 12:00, 2019-02-26 10:00 - 12:00 | Modern Languages Building (MLB), Room 2001A
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 Pyt hon is recommended. Computers will be available to complete exercises.

Intro to Web Applications using Flask and Python
2019-03-15 09:30 - 12:00 | Modern Languages Building (MLB), Room 2001A
Ever want to build your own web application? Do you want to do it using Python? Well then, Flask is the answer you are looking for. Its a micro web framework for Python to help you build your first web app. Come learn how to get started building, testing and deploying your first app to the web.
Attendees should be familiar with HTML, CSS and Python or RShiny. Anaconda Python 3.6 will be used.

MICDE Seminar: Narayana R. Aluru, Professor, Department of Mechanical Science and Engineering, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign
2019-03-14 15:00 - 16:00 | 1005 EECS, 1301 Beal Ave, Ann Arbor, MI, 48109, United States
Bio: Professor Aluru studies problems at the crossroads of mechanical engineering, electrical engineering, materials science and chemical engineering. His work in the area of microelectromechanical systems (MEMS) and nanoelectromechanical systems (NEMS) revealed previously unknown nonlinear dynamic phenomena, such as complex oscillations, period doubling bifurcation to chaos, and U-sequence. These insights led him to perform fundamental studies on thermoelastic damping in MEMS and to develop a new model to predict thermoelastic damping for complex nonlinear oscillations encountered in NEMS.
In another effort, he developed the first bio-MEMS and microfluidics models for the analysis and design of lab-on-a-chip applications, as well as mathematical models for pH- and electric field-responsive hydrogels-materials with potential applications in small-scale sensing and actuation.
Professor Aluru also studies the unique physics that occur at the nanometer level. He discovered several new physical phenomena through nanofluidics research, including charge inversion, flow reversal, anomalously immobilized water, asymmetric dependence of fluid and ion transport on surface charge, and enhanced conductivity in nanopores. His recent investigations of surface diffusion demonstrated that liquid molecules move as much as 30 times faster over a solid surface when that surfaced is only partially covered by such molecules, and that larger molecules move faster on a partially covered surface than shorter ones do. His other work in nanofluidics includes the multiscale modeling of the transport of water and other ions through membranes, studying the function of biological channels in the membranes of living cells, investigating the use of carbon nanotubes to filter pathogens and other toxins out of water, and exploring the use of carbon and boron nanotubes to speed the removal of salt from water during reverse osmosis.
COMPUTATIONAL NANOSCALE HYDRODYNAMICS
Many applications in biology, engineering and science rely on efficient hydrodynamic transport through nanometer scale pores and channels. For example, channels and pores in cellular membranes regulate the functionality of the cell by selectively and efficiently exchanging water and ions between extra and intra cellular environments. Selective pores in ultrathin membranes have been shown to be highly efficient for water desalination and power generation. Classical theories often fail to describe fluid physics at nanometer scale. For example, density layering, size dependent fluid properties, restricted translational and rotational motions, charge inversion, flow reversal and several other important phenomena have been observed at nanometer scale. The focus of this talk is to develop efficient theories and computational approaches to accurately describe fluid physics at nanometer scales. First, we will introduce an empirical potential-based quasi-continuum theory (EQT) to accurately predict the structure of confined fluids. We show that the density layering from EQT matches well with molecular dynamics (MD) and EQT is many orders of magnitude faster compared to MD. Next, we show that the EQT framework can be combined with the generalized Langevin theory to compute diffusion of confined fluids and with the classical Navier-Stokes equations to compute the transport of confined fluids. We will show several examples to demonstrate the accuracy and efficiency of the quasi-continuum theory for confined fluids.
Prof. Aluru is being hosted Professors Krishna Garikipati and Eric Michielssen. If you would like to meet Prof. Aluru, please send an email to micde-events@umich.edu. If you are an MICDE student or fellow, or a post-doc, and would like to join Prof. Aluru for lunch, please RSVP here.

Open Source GIS
2019-03-14 13:00 - 16:30 | Rackham Building, Earl Lewis Room, 3rd Floor East, 915 E. Washington St., Ann Arbor, MI, 48109, United States
This workshop will cover introductory GIS concepts and techniques using open source tools. We will use QGIS and R and learn the basics of GIS by solving a number of different problems. You will also learn to generate production quality maps. Some exposure to R will be helpful.
The workshop is meant for students and researchers who want to have a quick and simple exposure to GIS concepts and tools.

PySpark
2019-03-13 14:00 - 16:30 | Modern Languages Building (MLB), Room 2001A
Apache Spark is a powerful open source processing engine built around speed, ease of use, and sophisticated analytics. Industry has quickly adopted Spark and deployed it at scale for processing big data. Its main advantage include in-memory processing and a rich set of operations for wrangling data using DataFrames. In this workshop, we’ll introduce attendees to SparkSQL and DataFrames for basic data manipulation, file I/O and SQL querying. Spark has language bindings to R, Python, Scala and Java. We’ll be using PySpark (the Python API) in our workshop.
The workshop is intended for users with INTERMEDIATE knowledge of R, Python, or comparable language. Attendees should be familiar with DataFrames in Python (pandas) or R (dplyr). Attendees will NEED to have a Cavium account beforehand to participate. http://myumi.ch/6pn5d

Latent Variable Modeling
2019-03-06 14:00 - 17:00 | Modern Languages Building (MLB), Room 2001A
Part of the Structural Equation Modeling (SEM) series. This workshop will help participants develop skills in understanding and conducting latent variable models, particularly from the perspective of structural equation modeling. After a conceptual overview, a broad view of matrix factorization techniques will be provided along with specific examples (e.g. PCA, ‘factor analysis’). In addition, measurement error issues, reliability, and scale development will be discussed (e.g. ‘confirmatory’ factor analysis).
Prerequisites: One should have a firm understanding of basic regression. R will be the program of choice, but nothing beyond very basic skill is assumed (e.g. import data, run a regression). Demonstration will be conducted with R, and the psych and lavaan packages in particular.

Statistical Analysis with R
2019-03-05 08:30 - 15:00, 2019-03-04 08:30 - 15:00 | Modern Languages Building (MLB), Room 2001A
This is a two day workshop (March 4 and 5) in R which is a free and open source environment for data analysis and statistical computing. While R contains many built-in statistical procedures, a powerful feature of R is the facility for users to extend these procedures to suit their own needs. Excellent graphing capability is another reason R is gaining wide popularity.

How to Obtain R
Help Tools
Importing / Exporting Data
Data Management
Descriptive and Exploratory Statistics
Common Statistical Analyses (t-test, Regression Modeling, ANOVA, etc.)
Graphics
Creating Functions

Geospatial Analysis with Google Earth Engine
2019-02-27 14:00 - 17:30 | Rackham Building, Earl Lewis Room, 3rd Floor East, 915 E. Washington St., Ann Arbor, MI, 48109, United States
Google Earth Engine combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. This hands-on workshop will help you understand the power (and limitation) of GEE for carrying out an end-to-end analysis.
You should have some exposure to GEE and remote sensing. We will focus on contemporary environmental issues and learn how to carry out more advanced analysis and visualization in GEE. We will use the web-based IDE for the Earth Engine JavaScript API.

Introduction to the campus Hadoop cluster
2019-02-21 11:00 - 12:00, 2019-02-20 16:00 - 17:00 | East Hall B254, 530 Church St., Ann Arbor, MI, 48109, United States
This course will cover 4 areas:

Logging into the cluster
How to upload your data
How to run a job
How to get your data from the cluster

Prerequisites: Workshop participants should take the “Introduction to the Linux Command Line” workshop, and view the following videos:
https://youtu.be/4Gfl0WuONMY
https://www.youtube.com/watch?v=bcjSe0xCHbE
Click here for more information on The Cavium ThunderX Cluster
Click here to fill out an account request form
Note: 3 business days are needed for creation of accounts
Students should fill in “Workshop” in the “Advisor” section.
It is recommended that students get an account at Kaggle ( https://www.kaggle.com/ ) as this is where we will source our data sets.
Campus VPN access is required for off-campus access but not from on campus. An SSH client, and Duo will be required during the workshop.

If you have questions about this workshop, please send an email to smeyer@umich.edu

Generalized Additive Models
2019-02-20 15:30 - 17:30 | Modern Languages Building (MLB), Room 2001A
Nonlinear relationships abound in nature, though typical statistical models ignore this in favor of simplicity, often at a cost of both predictive capabilities and better understanding of the underlying phenomenon of interest. One means to explore such relationships is through generalized additive models (GAM).
This workshop will introduce participants to GAMs as a means to extend their efforts beyond the usual GLM setting. In addition, extensions and connections to other models will be noted (e.g. mixed and spatial). Demonstration will be conducted with R, and the mgcv package in particular.
Link: https://m-clark.github.io/generalized-additive-models/
