Stefan Gugler

Stefan Gugler

PhD Student in the Reiher Lab at ETH Zurich. Interested in how machine learning and artificial intelligence can help us with problems in theoretical and quantum chemistry.

Publications

You can also find my articles on my Google Scholar profile.

Peer-Reviewed Articles

  1. J. Proppe⊥, S. Gugler⊥, M. Reiher "Gaussian Process-Based Refinement of Dispersion Corrections", J. Chem. Theory. Comput. 2019, 15, 6046; arXiv:1906.09342
  2. S. Gugler, J. P. Janet, H. J. Kulik, "Enumeration of de novo Inorganic Complexes for Chemical Discovery and Machine Learning", Mol. Syst. Des. Eng. 2019; chemrxiv
  3. A. Nandy, C. Duan, J. P. Janet, S. Gugler, H. J. Kulik, "Strategies and Software for Machine Learning Accelerated Discovery in Transition Metal Chemistry", Ind. Eng. Chem. Res. 2018, 57, 13973; chemrxiv

Conference Talks

  1. Gaussian process-based refinement of weak intermolecular forces (contributed talk), MRS Fall Meeting 2019, Boston (December 2019)
  2. Gaussian Process-Based Sampling and Refinement for Dispersion Correction (lightning talk), IBM Research C4 Workshop, Zurich (November 2019)

Conference Posters

  1. Gaussian Process-Based Refinement of Dispersion Correction 9th Molecular Quantum Mechanics Conference, Heidelberg (June 2019)
  2. Enumerating the inorganic universe of small complexes for machine learning
    256th ACS National Meeting & Exposition, Boston (August 2018)

Awards

  1. PCCP Poster Award at Molecular Quantum Mechanicas 2019 for poster "Gaussian Process-Based Refinement of Dispersion Correction" (June 2019)