Anatole von Lilienfeld

Faculty Member

Professor, Department of Chemistry, University of Toronto

Professor, Department of Materials Science & Engineering, University of Toronto

Canada CIFAR Artificial Intelligence Chair

Clark Chair in Advanced Materials

Anatole is a Full Professor at the University of Toronto and holds the Clark Chair of Advanced Materials at the Vector Institute. In spring 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 returning from the Free University of Brussels (where he served briefly as an Associate Professor in 2016) to Basel as a Tenure Track Assistant Professor. He held a Swiss National Science Foundation Assistant Professorship in the Institute of Physical Chemistry at the Department of Chemistry at the University of Basel from 2013-2015. Prior to that, he was a 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 the spring of 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 Zürich and the University of Cambridge (UK). He pursued his undergraduate studies at ETH Zuerich, École de Chimie, Polymers, et Matèriaux in Strasbourg, and University of Leipzig.

Research Interests

  • Chemical Compound Space
  • Quantum Machine Learning
  • Computational Materials Design & Discovery
  • Experimental Design
  • Chemical Reactions


  • Member, Acceleration Consortium


An assessment of the structural resolution of various fingerprints commonly used in machine learning

Behnam Parsaeifard and Deb Sankar De and Anders S Christensen and Felix A Faber and Emir Kocer and Sandip De and Jörg Behler and O Anatole von Lilienfeld and Stefan Goedecker


Ab initio machine learning in chemical compound space

Bing Huang and O Anatole von Lilienfeld


Machine learning based energy-free structure predictions of molecules, transition states, and solids

Dominik Lemm and Guido Falk von Rudorff and O Anatole von Lilienfeld


Machine learning of free energies in chemical compound space using ensemble representations: Reaching experimental uncertainty for solvation

Jan Weinreich and Nicholas J Browning and O Anatole von Lilienfeld


Toward the design of chemical reactions: Machine learning barriers of competing mechanisms in reactant space

Stefan Heinen and Guido Falk von Rudorff and O Anatole von Lilienfeld


Introduction: Machine Learning at the Atomic Scale

Michele Ceriotti and Cecilia Clementi and O Anatole von Lilienfeld


Simplifying inverse materials design problems for fixed lattices with alchemical chirality

Guido Falk von Rudorff and O Anatole von Lilienfeld


Density Functional Geometries and Zero-Point Energies in Ab Initio Thermochemical Treatments of Compounds with First-Row Atoms (H, C, N, O, F)

Dirk Bakowies and O Anatole von Lilienfeld


Conformer-specific polar cycloaddition of dibromobutadiene with trapped propene ions

Ardita Kilaj and Jia Wang and Patrik Straňák and Max Schwilk and Uxía Rivero and Lei Xu and O Anatole von Lilienfeld and Jochen Küpper and Stefan Willitsch


Elucidating an Atmospheric Brown Carbon Species—Toward Supplanting Chemical Intuition with Exhaustive Enumeration and Machine Learning

Enrico Tapavicza and Guido Falk von Rudorff and David O De Haan and Mario Contin and Christian George and Matthieu Riva and O Anatole Von Lilienfeld


An orbital-based representation for accurate quantum machine learning

Konstantin Karandashev and O Anatole von Lilienfeld


Relative energies without electronic perturbations via integral transform

Simon León Krug and Guido Falk von Rudorff and O Anatole von Lilienfeld


Non-covalent interactions between molecular dimers (S66) in electric fields

Max Schwilk and Pal Mezei and Diana N Tahchieva and Anatole von Lilienfeld