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
 Google Scholar · ORCID
 code
 GitHub
 social
 Twitter · LinkedIn
 cycling
 Strava
 books
 Goodreads
 chess
 Lichess
Publications
 Citation numbers (→) from Google Scholar
Research articles
Highly Accurate Realspace Electron Densities with Neural Networks · L. Cheng, P. B. Szabó, Z. Schätzle, D. Kooi, J. Köhler, K. J. H. Giesbertz, F. Noé, JH, P. GoriGiorgi & A. Foster · Preprint at arXiv:2409.01306 (2024) 
2 
Variational principle to regularize machinelearned density functionals: The noninteracting kineticenergy functional · P. del MazoSevillano & JH · J. Chem. Phys. 159, 194107 (2023)  5 
libMBD: A generalpurpose package for scalable quantum manybody dispersion calculations · JH, M. Stöhr, S. Góger, S. Chaudhuri, B. Aradi, R. J. Maurer & A. Tkatchenko · J. Chem. Phys. 159, 174802 (2023)  8 
DeepQMC: An opensource software suite for variational optimization of deeplearning molecular wave functions · Z. Schätzle, P. B. Szabó, M. Mezera, JH & F. Noé · J. Chem. Phys. 159, 094108 (2023)  19 
Ab initio quantum chemistry with neuralnetwork 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)  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)  42 
Roadmap on Machine learning in electronic structure · H. J. Kulik et al. · Electron. Struct. 4, 023004 (2022)  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)  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)  16 
Convergence to the fixednode limit in deep variational Monte Carlo · Z. Schätzle, JH & F. Noé · J. Chem. Phys. 154, 124108 (2021)  23 
Coulomb interactions between dipolar quantum fluctuations in van der Waals bound molecules and materials · M. Stöhr, M. Sadhukhan, Y. S. AlHamdani, JH & A. Tkatchenko · Nat. Commun. 12, 137 (2021)  33 
Deepneuralnetwork solution of the electronic Schrödinger equation · JH, Z. Schätzle & F. Noé · Nat. Chem. 12, 891–897 (2020)  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) * *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) * *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 manybody atomic approaches with nonlocal functionals · JH & A. Tkatchenko · Phys. Rev. Lett. 124, 146401 (2020)  101 
DFTB+, a software package for efficient approximate density functional theory based atomistic simulations · B. Hourahine et al. · J. Chem. Phys. 152, 124101 (2020) * *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 highpressure hydrogen solids · T. Cui, J. Li, W. Gao, JH, A. Tkatchenko & Q. Jiang · J. Phys. Chem. Lett. 11, 1521–1527 (2020) * *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)  8 
Phononpolariton 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) * *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) * *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) * *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) * *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 
Firstprinciples 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) * *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)  96 
Communication: Manybody stabilization of noncovalent interactions: Structure, stability, and mechanics of Ag₃Co(CN)₆ framework · X. Liu, JH & A. Tkatchenko · J. Chem. Phys. 145, 241101 (2016) * *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 vdWDF/CCSD(T) approach · JH & O. Bludský · J. Chem. Phys. 139, 034115 (2013) * *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. PérezMayoral, 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 densityfunctional model of van der Waals interactions · JH · Humboldt University (2018)  5 
Nonlocal correlation in density functional theory · JH · Charles University (2013) 
Software

DeepQMC ·
creator · 352
Deep learning quantum Monte Carlo for electrons in real space (Python) 
libMBD ·
creator · 52
Manybody dispersion library (Fortran) 
Pyberny ·
creator · 112
Molecular structure optimizer (Python) 
FHIaims ·
core contributor
Allelectron electronicstructure calculations (Fortran)  PySCF · contributor
 DFTB+ · contributor
 QCEngine · contributor
Presentations
Invited conference talks
2024  “Neuralnetwork 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 generalpurpose package for scalable manybody dispersion calculations” · Electronic Structure Software Development (Lausane, Switzerland) [virtual] 
“Neuralnetwork wave functions for quantum chemistry” · MLQC4DYN (Institut Pascal, Paris, France)  
“Neuralnetwork wave functions for quantum chemistry” · Monte Carlo and Machine Learning Approaches in Quantum Mechanics (IPAM, Los Angeles, USA)  
2021  “Deeplearning solution to the electronic manybody problem” · NonCovalent Interactions in Large Molecules and Extended Materials (EPFL, Lausanne, Switzerland) 
“Solving the electronic Schrödinger equation with deep learning” · ACS Fall Meeting [virtual]  
2020  “Densityfunctional model for van der Waals interactions: Unifying atomic approaches with nonlocal functionals” · Electronic Structure Theory with Numeric AtomCentered Basis Functions [virtual] 
2019  “Unifying densityfunctional and interatomic approaches to van der Waals interactions” · Frontiers in Density Functional Theory and Beyond (Kavli ITS, Beijing, China) 
2018  “Modeling van der Waals interactions in molecules and materials” · Molecular Simulations Meets Machine Learning and Artificial Intelligence (Lorentz Center, Leiden, Netherlands) 
“Modeling van der Waals interactions in materials with manybody dispersion” · Electronic Structure Theory with Numeric AtomCentered 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] 
2020  “Deep neural network solution of the electronic Schrödinger equation” · APS March Meeting (Denver, USA) [cancelled] 
2018  “Unified manybody 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) 
2016  “Firstprinciples approaches to van der Waals interactions” · ManyBody Interactions (Telluride, USA) 
2015  “Manybody dispersion meets nonlocal density functionals” · Modeling ManyBody Interactions (Lake La Garda, Italy) 
“Manybody dispersion meets nonlocal density functionals” · DPG March Meeting (Berlin, Germany)  
“Manybody dispersion meets nonlocal density functionals” · APS March Meeting (San Antonio, USA)  
2014  “Nonlocal density functionals meet manybody dispersion” · DPG March Meeting (Dresden, Germany) 
2013  “Adsorption in zeolites investigated by dispersioncorrected DFT” · Layered Materials (Liblice, Czechia) 
“Modeling of surface properties of lamellar zeolites” · Molecular Sieves (Heyrovsky Institute, Prague, Czechia) 
Conference poster presentations
2021  “Solving the electronic Schrödinger equation with deep learning” · Stochastic Methods in Electronic Structure Theory [virtual] 
2020  “Convergence to the fixednode limit in deep variational Monte Carlo” · NeurIPS workshop Machine Learning and the Physical Sciences [virtual] 
2019  “Deep neural network solution of the electronic Schrödinger equation” · NeurIPS workshop Machine Learning and the Physical Sciences (Vancouver, Canada) 
2017  “Balancing semilocal and nonlocal energy contributions in van der Waals systems” · Intermolecular Interactions (Arenas de Cabrales, Spain) 
2016  “Python interface to FHIaims” · Electronic Structure Theory with Numeric AtomCentered Basis Functions (Munich, Germany) 
2015  “Nonlocal density functionals meet manybody dispersion” · Psik Conference (San Sebastian, Spain) 
“Manybody dispersion meets nonlocal density functionals” · Congress of Theoretical Chemists (Torino, Italy)  
“Nonlocal density functionals meet manybody dispersion” · Frontiers of FirstPrinciples Simulations: Materials Design and Discovery (Berlin, Germany)  
2014  “Nonlocal density functionals meet manybody dispersion” · Addressing Challenges for FirstPrinciples Based Modeling of Molecular Materials (Lausanne, Switzerland) 
2013  “Modeling of surface properties of lamellar zeolites” · Molecular Sieves and Catalysis (Segovia, Spain) 
2012  “Silver clusters in zeolites: Structure, stability and photoactivity” · British Zeolite Association Meeting (Chester, UK) 
“Silver clusters in faujasite: A theoretical investigation” · Molecular Sieves (Prague, Czechia) 
Invited seminars
2022  UCT & IOCB Theoretical Chemistry Seminar (VŠCHT, Prague, Czechia) 
LennardJones Centre Discussion Group (University of Cambridge) [virtual]  
2021  Molecular and Ultrafast Science Seminar (Center for FreeElectron Laser Science) [virtual] 
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 MiniCourse (Carnegie Mellon University) [virtual] 
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) 
2016  “Nanoscale π–π stacked molecules bound by collective charge fluctuations” · AspuruGuzik group seminar (Harvard University, Cambridge, USA) 
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 · NonCovalent 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 ManyParticle Systems with Machine Learning”) 
Awards
Feb 2021  Marie SkłodowskaCurie Individual Fellowship [relinquished] 
Jan 2014  Heyrovsky Prize for the best science graduate · Charles University 
Jul 2008  Gold Medal · 39th International Physics Olympiad 
Professional activities
 Peerreviewed 43 manuscripts for Phys. Rev. X, Nat. Commun., Nat. Mach. Intell., Phys. Rev. Lett., J. Chem. Phys., and other journals
 Reviewed 1 grant proposal for U. S. Department of Energy
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)  
2019  “Messagepassing neural networks for modeling manyparticle systems” · CECAM Summer School (Mainz, Germany) 
Doctoral committees
2022–2024  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  Coorganized FYKOS, physics competition for high school students 