Big Data Summer - A summer school of the BiGmax Network

Big Data Summer

A summer school of the BiGmax Network
Platja d’Aro, Spain, September 9 - 13, 2019

Workshop Program

The scientific program will start Monday at 3 pm and will end Friday 11:30 am.

You can find a program draft, here: pdf

Invited speakers and talks (+slides):

  • Stefan Bauer (Max Planck Institute for Intelligent Systems, Tübingen, Germany)
     Recent Advances in Unsupervised Representation Learning
Hot Topic: Learning Disentangled Representations
  • Hans-Joachim Bungartz (Technische Universität München, Germany)
     Research Data Infrastructures – How Generic, How Specific? Overview of the GeRDIProject
  • Claudia Draxl (Humboldt-Universität zu Berlin, Germany)
     The NOMAD Encyclopedia – a Tool for Exploring Computed Data
Hot Topic: Benchmark Calculations Towards Ultimate Precision in Density-Functional Theory
  • Luca M. Ghiringhelli (Fritz-Haber-Institut, Berlin, Germany)
     Metadata towards FAIR data sharing for data-driven materials science: achievements and open challenges
     Hot Topic: Identifying interpretable descriptors for materials properties with subgroup discovery and information theory
     Learning Descriptors for Materials Properties with Symbolic Regression and Compressed Sensing
  • Cecile Hébert (EPFL Lausanne, Switzerland)
     Big Data in analytical TEM
     Hot Topic: Machine learning tools in analytical TEM
  • Karsten Jacobsen (Danish Technical University, Denmark)
     Machine learning and computational screening
     Hot Topic: High Entropy Alloys for Catalysis
  • Chiho Kim (Georgia Tech, USA)
     Polymer Informatics: Past, Present, and Future
  • Dierk Raabe (Max-Planck-Institut für Eisenforschung GmbH, Düsseldorf, Germany)
     Big Data-Related Challenges in Microstructure Research and Alloy Design
Hot topic: Atomic-Scale Imaging of Chemistry at Lattice Defects
  • Markus Rampp (Max Planck Computing and Data Facility, Garching, Germany) ''
     High-performance Data Analytics Basic concepts of distributed deep learning
  • Joseph F. Rudzinski (Max Planck Institute for Polymer Research, Mainz, Germany)
     Data-driven methods for soft matter
     Hot Topic: Variational autoencoders for dimensionality reduction and clustering of molecular dynamics data
  • Matthias Scheffler(Fritz-Haber-Institut, Berlin, Germany)
  • Isao Tanaka (University Kyoto, Japan)
     Recommender System for Materials Discovery
Hot topic: Data Driven Discovery of New Inorganic Crystalline Materials
  • Annette Trunschke (Fritz-Haber-Institut, Berlin, Germany)
     Big-Data Driven Catalysis Research: Challenges and Chances
Hot topic: Clean Data Acquisition in Oxidation Catalysis
  • Jilles Vreeken (Helmholtz Center for Information Security, Germany)
     Material Subgroups
Hot topic: Telling Causal from Confounded
  • Siyuan Zhang (Max-Planck-Institut für Eisenforschung GmbH, Düsseldorf, Germany)
     Modern electron microscopy goes high dimensions: handling big data

There will be 60-minute pedagogical presentations and 20-minute “hot topic” talks on recent research.


Page last modified on September 23, 2019, at 02:31 PM EST