IMA/MCIM Industrial Problems Seminar

In collaboration with the University of Minnesota’s School of Mathematics, the Industrial Problems Seminars are a forum for industrial researchers to present their work to an audience of IMA postdocs, visitors, and graduate students, offering a first-hand glimpse into industrial research. The seminar series is often useful for initiating contact with industrial scientists. The IMA’s seminar series is the oldest and longest running seminar series in industrial mathematics.

This year's seminars are organized by Daniel Spirn, School of Mathematics, University of Minnesota.

All seminars are from 1:25pm - 2:25pm unless otherwise noted.
  • Regularization in the Real World

    Eric Voth, St. Jude Medical
    September 19, 2014
    Lind 305 [Map]


    The inverse problem of determining cardiac electrical patterns from measurements on internal or external electrodes has received increasing attention from medical-device companies in recent years. This talk will describe new ideas for regularization methods, simulation and preclinical experiments to evaluate and optimize them, and some of the clinical factors that make reliable solutions more difficult in vivo.
  • What is the Depth Necessary …?

    Benoit Couet, Schlumberger-Doll Research
    October 10, 2014
    Lind 305 [Map]


    The title makes reference to an important part of Schlumberger’s business, mainly the drilling of wells for the production of hydrocarbons. It also alludes to the depth of knowledge in mathematics, for example, one should possess to work in an industrial setting. The presentation will introduce Schlumberger to the audience with some examples of the kind of technology the company is making use of. The second part of the talk will explore in more detail a particular problem, presenting justifications for the techniques being employed and some pertinent results.
  • Algorithms for Signal Matching in Durability Testing

    Juan Garcia, MTS Systems Corporation
    October 31, 2014
    Lind 305 [Map]


    Mechanical durability testing in the automotive, aerospace and other industries presents great challenges. Current techniques typically require iterations to process the data acquired in the field so that it can be accurately simulated in the test lab. This talk will describe the state of the art for durability testing, present real-world examples, and point out some of the areas where development is needed.
  • Uncertainty Quantification in the Composites Industry: Designing Better Materials, Faster

    Paul Patrone, University of Minnesota, Twin Cities
    November 7, 2014
    Lind 305 [Map]


    In the aerospace composites industry, bringing new, high-performance materials to the market is critical to the maintaining an edge over competitors. However, materials development is a painfully slow process, and it can take upwards of 20 years before the discovery of a material and its first appearance in commercial grade applications. In recent years, there is an increasing desire to use atomistic-scale simulations to speed up the development process by rapidly exploring the properties of untested or novel materials. However, this task is complicated by the abundance of commercially available ingredients, and generally speaking, any interesting design space is too large to study by direct simulation In this work, we combine uncertainty quantification tools with reduced order modeling as a method of rapidly exploring the properties of a class of amine-cured epoxies. The key idea is to identify a system and its mechanical properties on the basis of a few graph theoretic properties of its constituent molecular ingredients. Given a limited set of simulated and experimental data points within this low-dimensional framework, we use tools such as Gaussian process regression to approximate the relationship (and uncertainties) between the graph-theoretic and mechanical properties over the entire design space. This so-called response surface then enables the computationalist to (I) perform additional simulations where uncertainties are highest, and (II) identify those materials that are most likely to perform well in experiments.
  • Three Gaps in Business Analytics

    Earl Sun, Target Corporation
    December 5, 2014
    Lind 305 [Map]


    Science and technology have a clear understanding of what math can offer. Business, however, tends to be a bit different. There is always the appetite to improve business and the decision-making process. However, there are challenges in applying advanced math in business. Understanding these challenges, or ‘gaps’, and knowing how to bridge them, can decide project success in the short term, and influence a practitioner’s career in the long term.

    In our discussion, we will explore three gaps:
      1. Gap in the ecosystem between generation and application of an idea
      2. Gap of scale when analyzing business decisions
      3. Gap of the mind when trying to understand customers analytically
  • Navigating Inside the Human Body

    Lev Koyrakh, Medtronic
    March 13, 2015
    Lind 305 [Map]


    Accurate intra-body navigation is used in various surgical and diagnostic procedures. In cardiac ablation procedures catheters are inserted into the heart through various blood vessels and are used for mapping the mechanical geometry and electrical activity of the heart, and also for ablation aimed at stopping arrhythmias. In the lungs, electromagnetic navigation is used for getting the biopsy tools to the lesions while navigating through the bronchial airway tree. Accurate navigation within the human body presents a set of challenging technological and mathematical problems. In this talk I will cover the principles of the intra-body navigation and the main mathematical challenges which have to be overcome in order to make the navigation accurate and useful.
  • Building a Greener Future for Energy Consumption

    Raya Horesh, IBM
    April 10, 2015
    Lind 305 [Map]


    Buildings consume about 40% of the total energy in most countries contributing to a significant amount of greenhouse gas (GHG) emissions and global warming. Therefore, reducing energy consumption in buildings, making buildings more energy efficient and operating buildings in more energy efficient manner are important tasks. Analytics can play an important role in identifying energy saving opportunities in buildings by modeling and analyzing how energy is consumed in buildings and optimizing energy consuming operations of buildings. In this talk I will cover areas ranging from physics based (ODE/PDE models) and data driven modeling to inverse problem for parameter estimation and model predictive control (MPC) framework that optimally determines control profiles of HVAC system given dynamic demand response signal, on-site energy storage system and energy generation system while satisfying thermal comfort of building occupants within the physical limitation of HVAC equipment, on-site energy storage system and on-site energy generator.

Previous Industrial Seminars

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