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Institute for Machine Learning
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Dipl.-Ing. Dr Thomas Unterthiner, MSc

Research Interests

  • Understanding the inner working of deep learning
  • Generative Adversarial Networks
  • Deep Learning and Neural Networks
  • Autonomous Driving
  • Drug Target Prediction
  • Machine Learning in Bioinformatics
  • Machine Learning and Artificial Intelligence

Selected Publications

Software

  • binet: A Deep Learning framework in Python with GPU support
  • librfn: high-performance implementation of Rectified Factor Networks, runs on CPU and GPU
  • libfabia: High performance parallel implementation of the FABIA biclustering algorithm
  • pyfabia: Cython implementation of FABIA
  • Regular contributor to various open source projects such as scikit-learnPyCUDAscikit-cuda and others

Education

  • 2012 - present: PhD in Computer Science, Johannes Kepler University, Linz
  • 2008-2016: MSc Computer Science (Diplom-Ingeneur), Johannes Kepler University, Linz, Austria (passed with distinction)
  • 2008-2012: MSc Bioinformatics, Johannes Kepler University, Linz, Austria (passed with distinction)
  • 2009-2010: Erasmus Study Abroad, University of Reading, United Kingdom
  • 2005-2008: BSc Computer Science, Johannes Kepler University, Linz, Austria (passed with distinction)
  • 2004: Matura (high school graduation) Deutschsprachige Handelsoberschule, Bolzano, Italy, Grade: 100/100

Employment Record

  • 2012 - present: Research Assistant, Institute of Bioinformatics, Johannes Kepler University, Linz, Austria
  • 2010 - 2011: Research Assistant, Department of Mathematics Education, Johannes Kepler University, Linz, Austria
  • 2009: Research Assistant, Department of Bioinformatics, Institute for Microbiology and Genetics, University of Göttingen, Germany
  • 2009: Summer-Internship as Software Developer at Orgachim ISC, Ruse, Bulgaria
  • 2008: Summer-Internship as Software Developer at Würth-Phönix SRL, Bolzano, Italy