Jan Hermann

Computational chemist and physicist by training️, who got later hooked on machine learning, and now enjoys integrating deep learning into quantum chemistry. I was born and raised in Český Krumlov, moved for university to Prague, and later for a Phd to Berlin, where I now live with my wife and our two kids. I work at Microsoft in AI for Science.

research
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GitHub
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Lichess

Publications

Research articles

Highly Accurate Real-space Electron Densities with Neural Networks · L. Cheng, P. B. Szabó, Z. Schätzle, D. Kooi, J. Köhler, K. J. H. Giesbertz, F. Noé, JH, P. Gori-Giorgi & A. Foster · Preprint at arXiv:2409.01306 (2024)  PDF 2
Variational principle to regularize machine-learned density functionals: The non-interacting kinetic-energy functional · P. del Mazo-Sevillano & JH · J. Chem. Phys. 159, 194107 (2023)  PDF 5
libMBD: A general-purpose package for scalable quantum many-body dispersion calculations · JH, M. Stöhr, S. Góger, S. Chaudhuri, B. Aradi, R. J. Maurer & A. Tkatchenko · J. Chem. Phys. 159, 174802 (2023)  PDF 8
DeepQMC: An open-source software suite for variational optimization of deep-learning molecular wave functions · Z. Schätzle, P. B. Szabó, M. Mezera, JH & F. Noé · J. Chem. Phys. 159, 094108 (2023)  PDF 19
Ab initio quantum chemistry with neural-network wavefunctions · JH, J. Spencer, K. Choo, A. Mezzacapo, W. M. C. Foulkes, D. Pfau, G. Carleo & F. Noé · Nat. Rev. Chem. 7, 692–709 (2023)  PDF 74
Electronic excited states in deep variational Monte Carlo · M. T. Entwistle, Z. Schätzle, P. A. Erdman, JH & F. Noé · Nat. Commun. 14, 274 (2023)  PDF 42
Roadmap on Machine learning in electronic structure · H. J. Kulik et al. · Electron. Struct. 4, 023004 (2022)  PDF 131
Quantum Chemistry Common Driver and Databases (QCDB) and Quantum Chemistry Engine (QCEɴɢɪɴᴇ): Automation and interoperability among computational chemistry programs · D. G. A. Smith et al. · J. Chem. Phys. 155, 204801 (2021)  PDF 37
Anisotropic interlayer force field for transition metal dichalcogenides: The case of molybdenum disulfide · W. Ouyang, R. Sofer, X. Gao, JH, A. Tkatchenko, L. Kronik, M. Urbakh & O. Hod · J. Chem. Theory Comput. 17, 7237–7245 (2021)  PDF 16
Convergence to the fixed-node limit in deep variational Monte Carlo · Z. Schätzle, JH & F. Noé · J. Chem. Phys. 154, 124108 (2021)  PDF 23
Coulomb interactions between dipolar quantum fluctuations in van der Waals bound molecules and materials · M. Stöhr, M. Sadhukhan, Y. S. Al-Hamdani, JH & A. Tkatchenko · Nat. Commun. 12, 137 (2021)  PDF 33
Deep-neural-network solution of the electronic Schrödinger equation · JH, Z. Schätzle & F. Noé · Nat. Chem. 12, 891–897 (2020)  PDF 563
Fluctuational electrodynamics in atomic and macroscopic systems: van der Waals interactions and radiative heat transfer · P. S. Venkataram, JH, A. Tkatchenko & A. W. Rodriguez · Phys. Rev. B 102, 085403 (2020)  PDF *

*Copyright 2020 by the American Physical Society

3
Recent developments in the PʏSCF program package · Q. Sun et al. · J. Chem. Phys. 153, 024109 (2020)  PDF *

*This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing.

778
Density functional model for van der Waals interactions: Unifying many-body atomic approaches with nonlocal functionals · JH & A. Tkatchenko · Phys. Rev. Lett. 124, 146401 (2020)  PDF 101
DFTB+, a software package for efficient approximate density functional theory based atomistic simulations · B. Hourahine et al. · J. Chem. Phys. 152, 124101 (2020)  PDF *

*This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing.

900
Nonlocal electronic correlations in the cohesive properties of high-pressure hydrogen solids · T. Cui, J. Li, W. Gao, JH, A. Tkatchenko & Q. Jiang · J. Phys. Chem. Lett. 11, 1521–1527 (2020)  PDF *

*This document is the unedited Author’s version of a Submitted Work that was subsequently accepted for publication in The Journal of Physical Chemistry Letters, copyright © American Chemical Society after peer review. To access the final edited and published work follow this link.

7
Impact of nuclear vibrations on van der Waals and Casimir interactions at zero and finite temperature · P. S. Venkataram, JH, T. J. Vongkovit, A. Tkatchenko & A. W. Rodriguez · Sci. Adv. 5, eaaw0456 (2019)  PDF 8
Phonon-polariton mediated thermal radiation and heat transfer among molecules and macroscopic bodies: Nonlocal electromagnetic response at mesoscopic scales · P. S. Venkataram, JH, A. Tkatchenko & A. W. Rodriguez · Phys. Rev. Lett. 121, 045901 (2018)  PDF *

*Copyright 2018 by the American Physical Society

16
Electronic exchange and correlation in van der Waals systems: Balancing semilocal and nonlocal energy contributions · JH & A. Tkatchenko · J. Chem. Theory Comput. 14, 1361–1369 (2018)  PDF *

*This document is the unedited Author’s version of a Submitted Work that was subsequently accepted for publication in Journal of Chemical Theory and Computation, copyright © American Chemical Society after peer review. To access the final edited and published work follow this link.

36
Unifying microscopic and continuum treatments of van der Waals and Casimir interactions · P. S. Venkataram, JH, A. Tkatchenko & A. W. Rodriguez · Phys. Rev. Lett. 118, 266802 (2017)  PDF *

*Copyright 2017 by the American Physical Society

31
Tuning intermolecular interactions with nanostructured environments · M. Chattopadhyaya, JH, I. Poltavsky & A. Tkatchenko · Chem. Mater. 29, 2452–2458 (2017)  PDF *

*This document is the unedited Author’s version of a Submitted Work that was subsequently accepted for publication in Chemistry of Materials, copyright © American Chemical Society after peer review. To access the final edited and published work follow this link.

11
First-principles models for van der Waals interactions in molecules and materials: Concepts, theory, and applications · JH, R. A. DiStasio, Jr. & A. Tkatchenko · Chem. Rev. 117, 4714–4758 (2017)  PDF *

*This document is the unedited Author’s version of a Submitted Work that was subsequently accepted for publication in Chemical Reviews, copyright © American Chemical Society after peer review. To access the final edited and published work follow this link.

563
Nanoscale π–π stacked molecules are bound by collective charge fluctuations · JH, D. Alfè & A. Tkatchenko · Nat. Commun. 8, 14052 (2017)  PDF 96
Communication: Many-body stabilization of non-covalent interactions: Structure, stability, and mechanics of Ag₃Co(CN)₆ framework · X. Liu, JH & A. Tkatchenko · J. Chem. Phys. 145, 241101 (2016)  PDF *

*This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing.

17
Theoretical investigation of layered zeolite frameworks: Surface properties of 2D zeolites · JH, M. Trachta, P. Nachtigall & O. Bludský · Catal. Today 227, 2–8 (2014) 26
A novel correction scheme for DFT: A combined vdW-DF/CCSD(T) approach · JH & O. Bludský · J. Chem. Phys. 139, 034115 (2013)  PDF *

*This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing.

19
Theoretical investigation of the Friedländer reaction catalysed by CuBTC: Concerted effect of the adjacent Cu²⁺ sites · M. Položij, E. Pérez-Mayoral, J. Čejka, JH & P. Nachtigall · Catal. Today 204, 101–107 (2013) 35

Book chapters

Introduction to material modeling · JH · In Machine learning meets quantum physics (eds K. T. Schütt et al.) 7–24 (Springer, 2020)
Van der Waals interactions in material modelling · JH & A. Tkatchenko · In Handbook of materials modeling (eds W. Andreoni & S. Yip) 1–33 (Springer, 2018) 4

Theses

Towards unified density-functional model of van der Waals interactions · JH · Humboldt University (2018)  PDF 5
Nonlocal correlation in density functional theory · JH · Charles University (2013)  PDF

Software

Presentations

Invited conference talks

2024 “Neural-network wave functions for quantum chemistry” · European Seminar on Computational Methods in Quantum Chemistry (Copenhagen, Denmark)
2023 Solving the electronic Schrödinger equation with deep learning” · SIAM Conference on Computational Science and Engineering (Amsterdam, Netherlands)
2022 “Libmbd: A general-purpose package for scalable many-body dispersion calculations” · Electronic Structure Software Development (Lausane, Switzerland) [virtual]  PDF
“Neural-network wave functions for quantum chemistry” · MLQC4DYN (Institut Pascal, Paris, France)
“Neural-network wave functions for quantum chemistry” · Monte Carlo and Machine Learning Approaches in Quantum Mechanics (IPAM, Los Angeles, USA)  PDF   video
2021 “Deep-learning solution to the electronic many-body problem” · Non-Covalent Interactions in Large Molecules and Extended Materials (EPFL, Lausanne, Switzerland)  PDF   video
Solving the electronic Schrödinger equation with deep learning” · ACS Fall Meeting [virtual]  PDF
2020 “Density-functional model for van der Waals interactions: Unifying atomic approaches with nonlocal functionals” · Electronic Structure Theory with Numeric Atom-Centered Basis Functions [virtual]  PDF
2019 “Unifying density-functional and interatomic approaches to van der Waals interactions” · Frontiers in Density Functional Theory and Beyond (Kavli ITS, Beijing, China)  video
2018 “Modeling van der Waals interactions in molecules and materials” · Molecular Simulations Meets Machine Learning and Artificial Intelligence (Lorentz Center, Leiden, Netherlands)  PDF
“Modeling van der Waals interactions in materials with many-body dispersion” · Electronic Structure Theory with Numeric Atom-Centered Basis Functions (TU Munich, Germany)
“Modeling van der Waals interactions” · Python for Quantum Chemistry and Materials Simulation Software (Caltech, Pasadena, USA)

Contributed conference talks

2021 Approaching exact solutions of the electronic Schrödinger equation with deep quantum Monte Carlo” · APS March Meeting [virtual]  PDF   video
2020 Deep neural network solution of the electronic Schrödinger equation” · APS March Meeting (Denver, USA) [cancelled]
2018 Unified many-body approach to van der Waals interactions based on semilocal polarizability functional” · APS March Meeting (Los Angeles, USA)
2017 What is the range of electron correlation in density functionals?” · APS March Meeting (New Orleans, USA)  PDF
2016 “First-principles approaches to van der Waals interactions” · Many-Body Interactions (Telluride, USA)
2015 “Many-body dispersion meets non-local density functionals” · Modeling Many-Body Interactions (Lake La Garda, Italy)
Many-body dispersion meets non-local density functionals” · DPG March Meeting (Berlin, Germany)
Many-body dispersion meets non-local density functionals” · APS March Meeting (San Antonio, USA)
2014 Non-local density functionals meet many-body dispersion” · DPG March Meeting (Dresden, Germany)
2013 “Adsorption in zeolites investigated by dispersion-corrected DFT” · Layered Materials (Liblice, Czechia)  PDF
“Modeling of surface properties of lamellar zeolites” · Molecular Sieves (Heyrovsky Institute, Prague, Czechia)  PDF

Conference poster presentations

2021 “Solving the electronic Schrödinger equation with deep learning” · Stochastic Methods in Electronic Structure Theory [virtual]  PDF
2020 “Convergence to the fixed-node limit in deep variational Monte Carlo” · NeurIPS workshop Machine Learning and the Physical Sciences [virtual]  PDF
2019 “Deep neural network solution of the electronic Schrödinger equation” · NeurIPS workshop Machine Learning and the Physical Sciences (Vancouver, Canada)  PDF
2017 “Balancing semilocal and nonlocal energy contributions in van der Waals systems” · Intermolecular Interactions (Arenas de Cabrales, Spain)
2016 “Python interface to FHI-aims” · Electronic Structure Theory with Numeric Atom-Centered Basis Functions (Munich, Germany)  PDF
2015 “Non-local density functionals meet many-body dispersion” · Psi-k Conference (San Sebastian, Spain)
“Many-body dispersion meets non-local density functionals” · Congress of Theoretical Chemists (Torino, Italy)
“Non-local density functionals meet many-body dispersion” · Frontiers of First-Principles Simulations: Materials Design and Discovery (Berlin, Germany)
2014 “Non-local density functionals meet many-body dispersion” · Addressing Challenges for First-Principles Based Modeling of Molecular Materials (Lausanne, Switzerland)
2013 “Modeling of surface properties of lamellar zeolites” · Molecular Sieves and Catalysis (Segovia, Spain)  PDF
2012 “Silver clusters in zeolites: Structure, stability and photoactivity” · British Zeolite Association Meeting (Chester, UK)  PDF
“Silver clusters in faujasite: A theoretical investigation” · Molecular Sieves (Prague, Czechia)

Invited seminars

2022 UCT & IOCB Theoretical Chemistry Seminar (VŠCHT, Prague, Czechia)  PDF
Lennard-Jones Centre Discussion Group (University of Cambridge) [virtual]  video
2021 Molecular and Ultrafast Science Seminar (Center for Free-Electron Laser Science) [virtual]  PDF
Machine Learning seminar (Chalmers University of Technology) [virtual]
Grüneis group seminar (TU Wien) [virtual]
(Nano)Materials Modeling Seminar (Charles University) [virtual]
Cosmology Seminar (University of Szczecin) [virtual]
2020 “Solving the electronic Schrödinger equation with deep learning” · Scientific Machine Learning Mini-Course (Carnegie Mellon University) [virtual]  PDF   video
Machine Learning in Physics, Chemistry and Materials (University of Cambridge) [virtual]
Jordan group seminar (University of Pittsburgh) [virtual]
2018 “Mona: Calculation framework for reproducible science” · Theory Department seminar (Fritz Haber Institute, Berlin, Germany)  PDF
2016 “Nanoscale π–π stacked molecules bound by collective charge fluctuations” · Aspuru-Guzik group seminar (Harvard University, Cambridge, USA)  PDF
2015 DiStasio group seminar (Cornell University, Ithaca, USA)

Employment

Microsoft, Berlin
Nov 2022 Principal research manager · AI for Science
Free University of Berlin
Nov 2020–Oct 2022 Junior research group leader · Department of Mathematics
Jan 2019–Oct 2020 Postdoctoral researcher · AI4Science group
University of Luxembourg
Jan–Dec 2018 Postdoctoral researcher · Theoretical Chemical Physics group
Fritz Haber Institute, Berlin
Oct 2013–Dec 2017 Graduate research assistant · Theory department
Institute of Organic Chemistry and Biochemistry, Prague
Mar 2010–Sep 2013 Undergraduate research assistant · Non-Covalent Interactions group

Education

Humboldt University of Berlin
Dec 2017 Ph.D. in Physics · summa cum laude
Charles University, Prague
Sep 2013 M.S. in Molecular Modeling
Sep 2011 B.S. in Physics
Jun 2011 B.S. in Chemistry

Secondary appointments

Jul 2021–Oct 2022 Junior Fellow · BIFOLD, Berlin
Jan 2019–Oct 2020 Postdoctoral research fellow · Machine Learning group, TU Berlin
Sep–Dec 2016 Visiting graduate researcher · IPAM, UCLA
(long program “Understanding Many-Particle Systems with Machine Learning”)

Awards

Feb 2021 Marie Skłodowska-Curie Individual Fellowship [relinquished]
Jan 2014 Heyrovsky Prize for the best science graduate · Charles University
Jul 2008 Gold Medal · 39th International Physics Olympiad

Professional activities

Teaching & mentoring

Professional mentorship

Sep 2022–Jul 2024 U. C. Kaya, Master student
Mar–Sep 2022 E. Trushin, Postdoc (with F. Noé)
Sep 2021–Oct 2022 B. Szabó, Phd student (with F. Noé)
May 2021–Dec 2022 P. del Mazo, Postdoc
Apr 2021–Apr 2022 M. Höfler, Master student
Jul 2019–Jul 2020 J. Lederer, Phd student, TU Berlin (with K.-R. Müller)
Jan 2019–Oct 2022 Z. Schätzle, Master/Phd student (with F. Noé)

Lectures for students

2022 “Machine Learning in Quantum Chemistry” · IMPRS Summer School (Berlin, Germany)
“Basic principles of application of machine learning in quantum chemistry” (VŠCHT, Prague)  PDF
2019 “Message-passing neural networks for modeling many-particle systems” · CECAM Summer School (Mainz, Germany)

Doctoral committees

20222024 B. Ames, University of Luxembourg
2021 M. Wilson, University of Bristol, UK

Public outreach

Sep 2019 Public lecture in the Six Minute Challenge series, Czech Center, Berlin
2018 Mentored a student in the LEAF program, accepted to University of Edinburgh
Sep 2008–Jun 2010 Co-organized FYKOS, physics competition for high school students