Jan Hermann

I'm a BIFOLD junior group leader at FU Berlin.

My research focuses on advancing quantum chemistry through tight integration of deep learning. I search for suitable entry points for machine learning in electronic structure theory and incorporate exact priors induced by the underlying physics into neural-network and training architectures. The goal is to push through the existing scale–accuracy tradeoff offered by traditional methods of quantum chemistry.

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email
jan.hermann@fu-berlin.de
phone
+49 30 838-66432
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Publications

Research articles

• M. Entwistle, Z. Schätzle, P. A. Erdman, JH & F. Noé. Electronic excited states in deep variational Monte Carlo. arXiv:2203.09472 (2022) 
• H. Kulik et al. Roadmap on machine learning in electronic structure. Electron. Struct. (2022)  5
• D. G. A. Smith et al. Quantum Chemistry Common Driver and Databases (QCDB) and Quantum Chemistry Engine (QCEɴɢɪɴᴇ): Automation and interoperability among computational chemistry programs. J. Chem. Phys. 155, 204801 (2021)  *

*This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in Journal of Chemical Physics and may be found at this link.

9
• W. Ouyang, R. Sofer, X. Gao, JH, A. Tkatchenko, L. Kronik, M. Urbakh & O. Hod. Anisotropic interlayer force field for transition metal dichalcogenides: The case of molybdenum disulfide. J. Chem. Theory Comput. 17, 7237–7245 (2021)  1
• Z. Schätzle, JH & F. Noé. Convergence to the fixed-node limit in deep variational Monte Carlo. J. Chem. Phys. 154, 124108 (2021)  5
• M. Stöhr, M. Sadhukhan, Y. S. Al-Hamdani, JH & A. Tkatchenko. Coulomb interactions between dipolar quantum fluctuations in van der Waals bound molecules and materials. Nat. Commun. 12, 137 (2021)  13
• JH, Z. Schätzle & F. Noé. Deep-neural-network solution of the electronic Schrödinger equation. Nat. Chem. 12, 891–897 (2020)  238
• P. S. Venkataram, JH, A. Tkatchenko & A. W. Rodriguez. Fluctuational electrodynamics in atomic and macroscopic systems: van der Waals interactions and radiative heat transfer. Phys. Rev. B 102, 085403 (2020)  *

*Copyright 2020 by the American Physical Society

• Q. Sun et al. Recent developments in the PʏSCF program package. 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.

185
• JH & A. Tkatchenko. Density functional model for van der Waals interactions: Unifying many-body atomic approaches with nonlocal functionals. Phys. Rev. Lett. 124, 146401 (2020)  33
• B. Hourahine et al. DFTB+, a software package for efficient approximate density functional theory based atomistic simulations. 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.

331
• T. Cui, J. Li, W. Gao, JH, A. Tkatchenko & Q. Jiang. Nonlocal electronic correlations in the cohesive properties of high-pressure hydrogen solids. 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.

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

*Copyright 2018 by the American Physical Society

12
• JH & A. Tkatchenko. Electronic exchange and correlation in van der Waals systems: Balancing semilocal and nonlocal energy contributions. 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.

27
• P. S. Venkataram, JH, A. Tkatchenko & A. W. Rodriguez. Unifying microscopic and continuum treatments of van der Waals and Casimir interactions. Phys. Rev. Lett. 118, 266802 (2017)  *

*Copyright 2017 by the American Physical Society

24
• M. Chattopadhyaya, JH, I. Poltavsky & A. Tkatchenko. Tuning intermolecular interactions with nanostructured environments. 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.

9
• JH, R. A. DiStasio, Jr. & A. Tkatchenko. First-principles models for van der Waals interactions in molecules and materials: Concepts, theory, and applications. 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.

414
• JH, D. Alfè & A. Tkatchenko. Nanoscale π–π stacked molecules are bound by collective charge fluctuations. Nat. Commun. 8, 14052 (2017)  73
• X. Liu, JH & A. Tkatchenko. Communication: Many-body stabilization of non-covalent interactions: Structure, stability, and mechanics of Ag₃Co(CN)₆ framework. 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.

10
• JH, M. Trachta, P. Nachtigall & O. Bludský. Theoretical investigation of layered zeolite frameworks: Surface properties of 2D zeolites. Catal. Today 227, 2–8 (2014) 24
• JH & O. Bludský. A novel correction scheme for DFT: A combined vdW-DF/CCSD(T) approach. 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.

18
• M. Položij, E. Pérez-Mayoral, J. Čejka, JH & P. Nachtigall. Theoretical investigation of the Friedländer reaction catalysed by CuBTC: Concerted effect of the adjacent Cu²⁺ sites. Catal. Today 204, 101–107 (2013) 32

Book chapters

• JH. Introduction to material modeling. In: K. T. Schütt et al. (eds), Machine learning meets quantum physics (Springer, Cham, 2020)
• JH & A. Tkatchenko. Van der Waals interactions in material modelling. In: W. Andreoni & S. Yip (eds), Handbook of Materials Modeling (Springer, Cham, 2018) 1

Theses

• JH. Towards unified density-functional model of van der Waals interactions (Humboldt University, 2018)  1
• JH. Nonlocal correlation in density functional theory (Charles University, 2013) 

Software

• DeepQMC, creator, 242
Deep learning quantum Monte Carlo for electrons in real space (Python)
• Libmbd, creator, 38
Many-body dispersion library (Fortran)
• Pyberny, creator, 81
Molecular structure optimizer (Python)
• FHI-aims, core contributor
All-electron electronic structure theory (Fortran)
• PySCF, contributor
• DFTB+, contributor
• QCEngine, contributor

Presentations

Invited conference talks

2022 “Neural-network wave functions for quantum chemistry”, Monte Carlo and Machine Learning Approaches in Quantum Mechanics, IPAM, Los Angeles, USA   
2021 “Deep-learning solution to the electronic many-body problem”, Non-Covalent Interactions in Large Molecules and Extended Materials, EPFL, Lausanne, Switzerland   
• “Solving the electronic Schrödinger equation with deep learning”, ACS Fall Meeting, Atlanta, USA [virtual] 
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] 
2019 “Unifying density-functional and interatomic approaches to van der Waals interactions”, Frontiers in Density Functional Theory and Beyond, Beijing, China 
2018 “Modeling van der Waals interactions in molecules and materials”, Molecular Simulations Meets Machine Learning and Artificial Intelligence, Leiden, Netherlands 
• “Modeling van der Waals interactions in materials with many-body dispersion”, Electronic Structure Theory with Numeric Atom-Centered Basis Functions, Munich, Germany
• “Modeling van der Waals interactions”, Python for Quantum Chemistry and Materials Simulation Software, 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 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 
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 
• “Modeling of surface properties of lamellar zeolites”, Molecular Sieves, Prague, Czechia 

Conference poster presentations

2021 “Solving the electronic Schrödinger equation with deep learning”, Stochastic Methods in Electronic Structure Theory, Telluride, USA [virtual] 
2020 “Convergence to the fixed-node 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 FHI-aims”, Electronic Structure Theory with Numeric Atom-Centered Basis Functions, Munich, Germany 
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 
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 
• Lennard-Jones Centre Discussion Group, University of Cambridge [virtual] 
2021 Molecular and Ultrafast Science Seminar, Center for Free-Electron Laser Science, Hamburg [virtual] 
• Machine Learning seminar, Chalmers University of Technology [virtual]
• Grüneis group, TU Wien [virtual]
• (Nano)Materials Modeling Seminar, Charles University [virtual]
• Institute of Physics, University of Szczecin [virtual]
2020 “Solving the electronic Schrödinger equation with deep learning”, Scientific Machine Learning Mini-Course, Carnegie Mellon University [virtual]   
• Machine Learning in Physics, Chemistry and Materials, University of Cambridge [virtual]
• Jordan group, University of Pittsburgh [virtual]
2018 “Mona: Calculation framework for reproducible science”, Theory department, Fritz Haber Institute 
2016 “Nanoscale π–π stacked molecules bound by collective charge fluctuations”, Aspuru-Guzik group, Harvard University 
2015 DiStasio group, Cornell University

Employment

Free University of Berlin
Nov 2020–BIFOLD Junior Group Leader, Department of Mathematics
Jan 2019–Oct 2020Postdoctoral researcher, Noé group
University of Luxembourg
Jan–Dec 2018Postdoctoral researcher, Tkatchenko group
Fritz Haber Institute of the Max Planck Society, Berlin
Oct 2013–Dec 2017Graduate researcher, Tkatchenko group, Theory Department
Institute of Organic Chemistry and Biochemistry, Prague
Mar 2010–Sep 2013Undergraduate researcher, Hobza group

Education

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

Secondary appointments

Jul 2021–Junior Fellow, BIFOLD, Berlin
Jun 2021–Associated PI, DAEDALUS, Berlin
Jan 2019–Oct 2020Research fellow in Müller group, TU Berlin
Sep–Dec 2016Research fellow at 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

Funding

Apr 2021–Mar 2024MATH+ AA2-8 (co-PI), “Deep backflow for accurate solution of the electronic Schrödinger equation”, €160k

Professional activities

•Peer-reviewed 39 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

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

Lectures for students

2022 “Basic principles of application of machine learning in quantum chemistry”, VŠCHT, Prague 
2019 “Message-passing neural networks for modeling many-particle systems”, CECAM Summer School, Mainz, Germany

Doctoral examinations

2021M. Wilson, University of Bristol, UK

Public outreach

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