Anatole von Lilienfeld develops methods for the first principles based sampling of chemical compound space using quantum mechanics, super computers, Big Data, and machine learning. He is also interested in pseudopotentials, van der Waals forces, density functional theory, molecular dynamics, and nuclear quantum effects. Anatole is an incoming Full Professor at University of Toronto and Clark Chair of Advanced Materials at the Vector Institute, Canada. As of 2022, he’s been a Visiting Professor at the Machine Learning group at TU Berlin, after serving as a Full Professor of Computational Materials Discovery at the Faculty of Physics, University of Vienna, Austria from 2020 onward. Prior to that, Anatole was awarded tenure and a promotion to Associate Professor of Physical Chemistry at the Department of Chemistry at the University of Basel in 2019, after he had returned as a Tenure Track Assistant Professor from the Free University of Brussels (where he served briefly as an Associate Professor in 2016). He was a Swiss National Science Foundation Assistant Professor in the Institute of Physical Chemistry at the Department of Chemistry at the University of Basel from 2013-2015. Prior to that he was member of scientific staff at the Argonne National Laboratory’s Leadership Computing Facility in Illinois which hosts one of the world’s largest supercomputers accessible to open science and research. In spring 2011 he chaired the 3 months program, “Navigating Chemical Compound Space for Materials and Bio Design”, at the Institute for Pure and Applied Mathematics, UCLA, California. From 2007 to 2010 he was a Distinguished Harry S. Truman Fellow at Sandia National Laboratories, New Mexico. Anatole carried out postdoctoral research at the Max-Planck Institute for Polymer Research (2007) and at New York University (2006). He received a PhD in computational chemistry from EPF Lausanne in 2005. He performed his diploma thesis work at ETH Zuerich and the University of Cambridge (UK). He studied chemistry at ETH Zuerich, the Ecole de Chimie, Polymers, et Materiaux in Strasbourg, and the University of Leipzig. Anatole descends from Baltic German refugees, he was born in Minnesota (1976), and grew up in Germany.
As of Jul 2022 Full Professor at University of Toronto and Clark Chair of Advanced Materials at the Vector Institute, Canada
Since Apr 2022 Visiting Professor, Machine Learning group, TU Berlin, Germany
Oct 2020 – Mar 2022 Full Professor of Computational Materials Discovery, Faculty of Physics, University of Vienna, Austria.
Feb 2019 – Sep 2020 Associate Professor at Institute of Physical Chemistry, Department of Chemistry University of Basel, Switzerland.
Jun 2016 – Jan 2019 Assistant Professor (TTAP) at Institute of Physical Chemistry, Department of Chemistry University of Basel, Switzerland.
Jan 2016 – May 2016 Associate Professor at Lab of General Chemistry (ALGC), Department of Chemistry, Free University of Brussels, Belgium.
Jul 2013 – 2015 SNF Assistant Professor at Institute of Physical Chemistry, Department of Chemistry University of Basel, Switzerland.
Feb 2011 – 2015 Assistant Computational Scientist in the Argonne Leadership Computing Facility at Argonne National Laboratories, Illinois.
Dec 2011 – 2013 Fellow at Computation Institute at University of Chicago, Illinois.
2010-2011 Senior Member of Technical Staff in the Surface and Interface Sciences Department at Sandia National Laboratories, New Mexico.
2007-2010 Truman Fellow in the Multiscale Dynamic Material Modeling Department at Sandia National Laboratories, New Mexico.
Spring 2007 Postdoctoral Research Fellow with Denis Andrienko (projectleader in Prof. K. Kremer’s Theory of Polymers group), MPI Mainz, Germany.
2005-2007 Postdoctoral Research Fellow with Mark Tuckerman, Chemistry Department, NYU, New York.
Fall 2005 Postdoctoral Research Fellow at IPAM, UCLA, Los Angeles.
2002-2005 Doctoral studies, Roethlisberger group, ETH Zuerich /EPF Lausanne, Switzerland. Download my doctoral thesis (EPFL).
Fall 2001 Photoacoustics research project in the Sigrist group, Institute for Quantum Electronics, Physics Department, ETH Zuerich, Switzerland.
Spring 2001 Erasmus exchange diploma thesis in the group of Prof. N. C. Handy at the University of Cambridge, UK, and in the group of Prof. M. Quack, Laboratory of Physical Chemistry, ETH Zuerich, Switzerland. Download my diploma thesis (ETHZ/University of Cambridge), or the resulting paper with C. Leonard “Spectroscopic properties of CCl3F calculated by density functional theory”, OAvL, C. Leonard, N. C. Handy, S. Carter, M. B. Willeke, M. Quack, Phys. Chem. Chem. Phys. 9 5027 (2007).
1999-2001 Undergraduate chemistry studies at the Chemistry Department, ETH Zuerich, Switzerland.
1998-1999 ECPM, Strasbourg, France.
1996-1998 Chemie Fakultaet, Universitaet Leipzig, Germany.
1992-1996 Grimmelshausen Gymnasium Gelnhausen, Gelnhausen, Germany.
Languages: English (fluent), French (fluent), German (native)
Birth: Dec 1976
Awards and fellowships
2021 recently awarded the honorary title of being the ‘Loewdin lecturer 2021 at Uppsala University, Sweden’
2020 co-PI on H2020 BIG-MAP grant
2020 co-PI on H2020 TREX grant
2019 SNI PhD student grant
2018 SNI PhD student grant
2018 co-PI in second phase of MARVEL NCCR (Swiss National Science Foundation)
2018 Feynman prize in theory
2017 ERC Consolidator grant
2016 co-PI on Swiss National Science Foundation NRP 75 grant “Big Data for Computational Chemistry: Unified machine learning and sparse grid combination technique for quantum based molecular design” with Prof. Harbrecht group (Mathematics Department)
2016 Google unrestricted research grant
2016 Odysseus grant from the Flemish Science Foundation (funding for multiple positions)
2015 co-PI on Swiss National Science Foundation grant for rabies elimination (funding for 1 doctoral student)
2014 PI on EOARD grant (funding for 1 doctoral student)
2013 co-PI on MARVEL NCCR (Swiss National Science Foundation)
2013 Assistant Professorship (Swiss National Science Foundation)
2013 Thomas Kuhn Paradigm Shift Award
2012 LDRD funding on machine learning, Argonne National Laboratory
2010 LDRD Award for Excellence (Sandia National Labs)
2007 Truman Fellowship (Sandia National Labs)
2006 Postdoctoral Fellowship (Swiss National Science Foundation)
2022- Scientific Advisory Board of SIMPLAIX https://www.h-its.org/research/simplaix/
2019- Editor in Chief of IOP’s Machine Learning: Science Technology
2019- Member of the Editorial Board of AAAS’s Science Advances
2014-2019 Member of the Editorial Board of Nature‘s Scientific Data.
2011 Chair of 3 months IPAM program “Navigating Chemical Compound Space for Materials and Bio Design”
Reviewer for Angewandte Chemie, Nature Materials, Accounts of Chemical Research, Physical Review Letters, Physical Review B, Journal of Chemical Physics, Proceedings of the Materials Research Society, Journal of Chemical Theory and Computation, Journal of Physical Chemistry A/B/C, Chemical Physics (Elsevier), Journal of Computational Physics, as well as for the Swiss National Supercomputing Centre (CSCS), Computational Readiness Review for INCITE and ALCC CPU time programs, US-Department of Energy, US National Science Foundation, Swiss National Science Foundation, Deutsche Forschungsgemeinschaft, Belgian Research Foundation Flanders (FWO).
10 Questions with Anatole von Lilienfeld and Gabor Csanyi (asked by the Thomas Young Centre (TYC) during the TYC Soiree on Machine Learning, Nov 2014).
We asked them…
1) What is the best thing about your job?
GC: The freedom to pick up any problem that I find interesting and have a chance at solving
2) What projects are you working on at the moment?
AvL: Many, all concerned with compound space
GC: My main interest is to develop new algorithms for simulating materials. We have a long running research program to try and accurately fit the Born-Oppenheimer potential energy surface of an arbitrary material or molecular system using an interatomic potential. I am also interested in statistical mechanics, and thinking about the most informationally efficient way to extract thermodynamic properties from simulations
3) What is the most amazing single thing you could tell me about your field of research?
AvL: Compound space is unfathomably huge, and we haven’t even scratched its surface yet
GC: That we can predict how materials in the real world will behave just by thinking about them and using a big computer to solve mathematical equations
4) What is the biggest problem or challenge you face in your field?
AvL: Size of compound space
GC: Currently there is a heck of a lot of data being generated by vast supercomputers, both on the electronic structure and the thermodynamic properties of materials, but most of this data is “dark” after the corresponding publications have appeared, and sitting on hard drives without anyone making any use of them
5) What, from your area of research, would you like to know the answer to in your lifetime?
AvL: Can we make cheap drugs that inhibit aging or cheap materials that make energy abundant? Is there an analytical and universal expression linking the electronic density of one compound to another, and how does it look like? What is transferability? What is the damage due to the selection bias represented in the choice of chemicals which nature surrounded us with? Will we ever have a satisfying orbital-free density functional?
GC: Whether the solution of the full Schroedinger equation for electrons and nuclei really takes exponential effort, or if there is a polynomial shortcut. Does Nature really have exponential “computing capacity” ?
6) What makes a good scientist or engineer?
AvL: Motivation, curiosity, perseverance, fantasy, creativity, friendliness, integrity and at least some writing skills (in random order and true for most professions)
GC: Curiosity – and honesty. You need a careful balance between enthusiastically pursuing an idea, but also being able to see what wonâ€™t work long before youâ€™ve spent your life turning every stone
7) Who are your scientific heroes – dead or alive?
AvL: Gibbs, Planck, Einstein, Pauli, Boltzmann, Feynman, Wilson (all dead)
8) How do you think scientists can make their work accessible to the public?
AvL: Demonstrate its usefulness, or at least its promise to be useful one day. Improve teaching and writing skills. Improve science funding policies
GC: BBC Radio 4 has excellent science programms, and seems to be able to call on an unending supply of scientists who are excellent communicators. They set a high standard to aspire t
9) What is your advice for anyone wanting to be a scientist or engineer?
AvL: Talent and education are helpful but not crucial. Study chemistry, it’s remarkable. Learn how to write. Don’t be afraid.
GC:Follow your dreams. Don’t be afraid to dirty your hands. Learn as early as possible to identify mentors worth learning from
10) Any last comments?
AvL: Who is John Galt?
GC: The above sounds a bit too serious. Science should be fun.