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2015 MRS Fall Meeting Logo2015 MRS Fall Meeting & Exhibit

November 29-December 4, 2015 | Boston
Meeting Chairs: T. John Balk, Ram Devanathan, George G. Malliaras, Larry A. Nagahara, Luisa Torsi

Symposium AAA—Big Data and Data Analytics in Materials Science

Recent developments in experimental and simulation tools have converged with advances in raw computing resources, necessitating the development of new algorithms for analyzing the data generated. The ability to collect more digital data at faster speeds with multiple signals, length scales and viewing angles, does not lead to improved materials characterization or modeling without the ability to process and understand the data. This is becoming increasingly apparent as sensors are capturing data at a rate which cannot effectively be analyzed by a human. Indeed, when Materials Science is viewed as a "Big Data" problem, it becomes immediately apparent that our field presents problems unique to Materials Science and that, because of the highly complex and non-linear relationships known to exist, a simple correlation is usually dissatisfying. Robust analytical methods for extraction of quantitative physical information from raw data, and not just correlations, are needed. This type of analysis is inaccessible by traditional methods, either due to massive data volumes or, conversely, missing data.

From an experimental perspective, all measurements become inverse problems: the end result of the interaction of a beam with a material is all that is observed and the material structure/composition which gave produced the result needs to be found. Similarly, computational design of materials to meet property targets can be framed as an inverse problem, using physics based models as forward models in the inversion. Experiments, by their very nature, have limitations such as indirect measurements, inefficient detectors, restricted field of view, sample damage, and noise. This makes for ambiguous interpretation from a machine's point of view- i.e. the inversion is ill-posed and the results from traditional analysis methods give uninterpretable or physically unrealistic results.

This symposium will cover advances in methods for data analytics, for both experimentally and computationally generated data, specifically as they have been applied to materials science problems. This symposium will focus on current challenges in data analytics for materials science such as high throughput data generation, inverse methods, three and four dimensional data, multimodal data, multi-physics model data, and others.

Topics will include:

  • Computational strategies for analysis of large data sets
  • Mathematical inverse methods applied to materials
  • Tomography and serial sectioning
  • Segmentation
  • Hyperspectral imaging
  • Time-resolved characterization techniques
  • Data sparsity
  • Compressed sensing in microscopy
  • Multimodal data and data fusion
  • Anomaly testing, outliers, and extreme events
  • Forward modeling

Invited Speakers:

  • Hyram Anderson (Sandia National Laboratories, USA)
  • Charles Bouman (Purdue University, USA)
  • Mary Comer (Purdue University, USA)
  • Corey Czarnik (Gatan Inc., USA)
  • Rainer Gehrke (Deutsches Elektronen-Synchrotron, Germany)
  • Marc De Graef (Carnegie Mellon University, USA)
  • Alfred Hero (University of Michigan, USA)
  • Alexander Hexemer (Lawrence Berkeley National Laboratory, USA)
  • Anubhav Jain (Lawrence Berkeley National Laboratory, USA)
  • Nicola Marzari (Lausanne, Switzerland)
  • Youssef Marzouk (Massachusetts Institute of Technology, USA)
  • Eric Miller (Tufts University, USA)
  • Matthias Scheffler (Fritz Haber Berlin, Germany)
  • Jamie Sethian (Lawrence Berkeley National Laboratory, USA)
  • Renu Sharma (National Institute of Standards and Technology, USA)
  • Jeff Simmons (Air Force Research Laboratory, USA)
  • David Srolovitz (University of Pennsylvania, USA)
  • Eric Stach (Brookhaven National Laboratory, USA)
  • Peter Wang (Continuum Analytics, USA)
  • Mashashi Watanabe (Lehigh University, USA)
  • Rebecca Willett (University of Wisconsin, USA)

Symposium Organizers

Lawrence Drummy
Air Force Research Laboratory

Shaul Aloni
Lawrence Berkeley National Laboratory
Molecular Foundry

Gerd Ceder
Massachusetts Institute of Technology

Dmitri Zakharov
Brookhaven National Laboratory
Center for Functional Nanomaterials