Scientific contributions
My full publication list can be found on Google Scholar.
Peer-reviewed publications
2024
M. Alberts, T. Laino, A. C. Vaucher,
Leveraging infrared spectroscopy for automated structure elucidation,
Commun. Chem. 2024, 7, 268.
F. Zipoli, Z. Ayadi, P. Schwaller, T. Laino, A. C. Vaucher,
Completion of partial chemical equations,
Mach. Learn.: Sci. Technol. 2024, 5, 025071.
2023
M. Suvarna, A. C. Vaucher, S. Mitchell, T. Laino, J. Pérez-Ramírez,
Language models and protocol standardization guidelines for accelerating synthesis planning in heterogeneous catalysis,
Nat. Commun., 2023, 7964.
A. Toniato, A. C. Vaucher, M. M. Lehmann, T. Luksch, P. Schwaller, M. Stenta, T. Laino,
Fast Customization of Chemical Language Models to Out-of-Distribution Data Sets,
Chem. Mater., 2023, 35, 8806-8815.
M. T. Cretu, A. Toniato, A. Thakkar, A. A. Debabeche, T. Laino, A. C. Vaucher,
Standardizing chemical compounds with language models,
Mach. Learn.: Sci. Technol. 2023, 4, 035014.
F. Bosia, P. Zheng, A. C. Vaucher, T. Weymuth, P. O. Dral, M. Reiher,
Ultra-fast semi-empirical quantum chemistry for high-throughput computational campaigns with Sparrow,
J. Chem. Phys., 2023, 158, 054118.
O. Schilter, A. C. Vaucher, P. Schwaller, T. Laino,
Designing catalysts with deep generative models and computational data. A case study for Suzuki cross coupling reactions,
Digital Discovery, 2023, 2, 728-735.
A. Toniato, J. P. Unsleber, A. C. Vaucher, T. Weymuth, D. Probst, T. Laino, M. Reiher,
Quantum chemical data generation as fill-in for reliability enhancement of machine-learning reaction and retrosynthesis planning,
Digital Discovery, 2023, 2, 663-673.
A. Toniato, A. C. Vaucher, P. Schwaller, T. Laino,
Enhancing diversity in language based models for single-step retrosynthesis,
Digital Discovery, 2023, 2, 489-501.
A. Thakkar, A. C. Vaucher, A. Byekwaso, P. Schwaller, A. Toniato, T. Laino,
Unbiasing Retrosynthesis Language Models with Disconnection Prompts,
ACS Cent. Sci., 2023, 9, 1488-1498.
2022
P. Schwaller, A. C. Vaucher, R. Laplaza, C. Bunne, A. Krause, C. Corminboeuf, T. Laino,
Machine intelligence for chemical reaction space,
WIREs Comput. Mol. Sci., 2022, 12, e1604.
A. Toniato, A. C. Vaucher, T. Laino,
Grand challenges on accelerating discovery in catalysis,
Catal. Today, 2022, 387, 140-142.
2021
P. Schwaller, D. Probst, A. C. Vaucher, V. H. Nair, D. Kreutter, T. Laino, J.-L. Reymond,
Mapping the space of chemical reactions using attention-based neural networks,
Nat. Mach. Intell. 2021.
A. C. Vaucher, F. Zipoli, J. Geluykens, V. H. Nair, P. Schwaller, T. Laino,
Inferring Experimental Procedures from Text-Based Representations of Chemical Reactions,
Nat. Commun. 2021, 12, 2573.
P. Schwaller, A. C. Vaucher, T. Laino, J.-L. Reymond,
Prediction of chemical reaction yields using deep learning,
Mach. Learn.: Sci. Technol. 2021, 2, 015016.
J. Geluykens, S. Mitrović, C.E. Ortega Vázquez, T. Laino, A. C. Vaucher, J. De Weerdt,
Neural Machine Translation for Conditional Generation of Novel Procedures,
Proceedings of the 54th Hawaii International Conference on System Sciences 2021.
2020
A. C. Vaucher, P. Schwaller, T. Laino,
Completion of partial reaction equations,
Machine Learning for Molecules Workshop @ NeurIPS, 2020.
P. Schwaller, A. C. Vaucher, T. Laino, J.-L. Reymond,
Data augmentation strategies to improve reaction yield predictions and estimate uncertainty,
Machine Learning for Molecules Workshop @ NeurIPS, 2020.
A. C. Vaucher, F. Zipoli, J. Geluykens, V. H. Nair, P. Schwaller, T. Laino,
Automated extraction of chemical synthesis actions from experimental procedures,
Nat. Commun. 2020, 11, 3601.
2019
N. Brown, M. Fiscato, M. H. S. Segler, A. C. Vaucher,
GuacaMol: Benchmarking Models for de Novo Molecular Design,
J. Chem. Inf. Model. 2019, 59, 1096-1108.
S. Amabilino, L. A. Bratholm, S. J. Bennie, A. C. Vaucher, M. Reiher, D. R. Glowacki,
Training Neural Nets To Learn Reactive Potential Energy Surfaces Using Interactive Quantum Chemistry in Virtual Reality,
J. Phys. Chem. A 2019, 123, 4486-4499.
G. N. Simm, A. C. Vaucher, M. Reiher,
Exploration of Reaction Pathways and Chemical Transformation Networks,
J. Phys. Chem. A 2019, 123, 385-399.
2018
T. Husch, A. C. Vaucher, M. Reiher,
Semiempirical Molecular Orbital Models based on the Neglect of Diatomic Differential Overlap Approximation,
Int. J. Quantum Chem. 2018, 118, e25799.
A. C. Vaucher, M. Reiher,
Minimum Energy Paths and Transition States by Curve Optimization,
J. Chem. Theory Comput. 2018, 14, 3091-3099.
M. A. Heuer, A. C. Vaucher, M, P. Haag, M. Reiher,
Integrated Reaction Path Processing from Sampled Structure Sequences,
J. Chem. Theory Comput. 2018, 14, 2052-2062.
2017
A. C. Vaucher, M. Reiher,
Steering Orbital Optimization out of Local Minima and Saddle Points Toward Lower Energy,
J. Chem. Theory Comput. 2017, 13, 1219-1228.
2016
A. C. Vaucher, M. Reiher,
Molecular propensity as a driver for explorative reactivity studies,
J. Chem. Inf. Model. 2016, 56, 1470-1478.
A. H. Mühlbach, A. C. Vaucher, M. Reiher,
Accelerating Wave Function Convergence in Interactive Quantum Chemical Reactivity Studies,
J. Chem. Theory Comput. 2016, 12, 1228-1235.
A. C. Vaucher, M. P. Haag, M. Reiher,
Real-time feedback from iterative electronic structure calculations,
J. Comput. Chem. 2016, 37, 805-812.
2014
M. P. Haag, A. C. Vaucher, M. Bosson, S. Redon, M. Reiher,
Interactive Chemical Reactivity Exploration,
ChemPhysChem 2014, 15, 3301-3319.
Talks
2023
"Advancing Chemistry with Artificial Intelligence: Challenges and Opportunities"
CIC Annual Meeting @ Wissenschaftsforum Chemie 2023,
Leipzig, Germany,
05.09.2023.
"Increasing the adoption of machine learning technologies by chemists with graphical and programmatic interfaces"
ACS Spring 2023,
Indianapolis, IN, USA,
26.03.2023.
2022
"Boosting the Adoption of AI Models for Chemical Reactivity"
Collegium Helveticum workshop: "The Future of Machine Learning in Chemistry",
Zurich, Switzerland,
05.12.2022.
"Combining high-quality, humanly curated data with language models: the dawn of on-demand machine learning models for digital chemistry"
Machine Learning and AI for Organic Chemistry @ ACS Fall 2022,
Chicago, IL, USA,
24.08.2022.
"Molecular Transformer-aided Biocatalysed Synthesis Planning"
Summer School Biotransformations 2022,
Bad Herrenalb, Germany,
15.08.2022.
"Learning how to do organic chemistry from literature-extracted synthesis actions"
International Symposium for Materials R&D Data (online),
08.07.2022.
"RoboRXN, a cloud-based AI-driven autonomous robot"
Future Labs Live,
Basel, Switzerland,
07.06.2022.
"Learning from literature-extracted synthesis actions for organic synthesis"
Applied Machine Learning Days @ EPFL 2022,
Lausanne, Switzerland,
30.03.2022.
Video link.
"Human-in-the-loop for a disconneciton-aware retrosynthesis"
Data Science and the Chemistry Ecosystem @ ACS Spring 2022 (online),
23.03.2022.
2021
"Cloud-based AI-driven autonomous lab"https://zenodo.org/doi/10.5281/zenodo.6259292)
6th SCS-Syngenta Symposium: "Chemistry lab of the future" (online),
26.11.2021.
"Inferring missing molecules in incomplete chemical equations"
Reactions: Representation, Planning and Robotics @ ACS Fall 2021 (online),
22.08.2021.
"Learning from literature-extracted synthesis actions for organic synthesis"
Machine Learning and AI for Organic Chemistry @ ACS Spring 2021 (online),
13.04.2021.
2020
"Completion of partial reaction equations"
Machine Learning for Molecules Workshop @ NeurIPS 2020 (online),
12.12.2020.
Video link.
"Learning how to do chemical reactions from data"
SCS Fall Meeting (online),
25.08.2020.
2018
"Interactive Quantum Chemistry"
"Computational Toolbox" Winterschool 2018: "Virtual Reality in the Natural Sciences",
Engelberg, Switzerland,
16.02.2018.
2017
"Interactive Quantum Chemistry"
Minisymposium Doktorierende,
Zurich, Switzerland,
26.09.2017.
2016
"Interactive Exploration of Chemical Reactivity in Education"
Future of Chemical Education (Workshop within the SCS Meeting),
Zurich, Switzerland,
15.09.2016.
2015
"Real-time quantum chemistry"
2nd Joint Seminar on Purpose-Driven Quantum Chemistry,
Bödefeld, Germany,
16.09.2015.
"Response time of quantum-chemical calculations during real-time reactivity explorations"
SCS Fall Meeting,
Lausanne, Switzerland,
04.09.2015.
Posters (as presenter)
A. C. Vaucher, P. Schwaller, A. Toniato, T. Laino "Inferring missing molecules in incomplete chemical equations", SCS Fall Meeting (online), Virtual, 10.09.2021.
A. C. Vaucher, P. Schwaller, T. Laino "Completion of partial reaction equations", Machine Learning for Molecules Workshop @ NeurIPS, Virtual, 2020.
A. C. Vaucher, A. Cardinale, J. Geluykens, M. Manica, P. Schwaller, A. Sobczyk, A. Toniato, F. Zipoli, T. Laino "Autonomous cloud-based platform for the AI-driven synthesis of molecules", Chemical Science Symposium, Virtual, 2020.
A. C. Vaucher, A. Cardinale, J. Geluykens, V. H. Nair, P. Schwaller, A. Toniato, F. Zipoli, T. Laino "Learning how to do chemical reactions from data", 3rd RSC-BMCS / RSC-CICAG Artificial Intelligence in Chemistry, Virtual, 2020.
A. C. Vaucher, M. Reiher "Steering Orbital Optimization out of Local Minima and Saddle Points Toward Lower Energy", 11th Triennial Congress of the World Association of Theoretical and Computational Chemists, Munich, Germany, 2017.
A. C. Vaucher, M. Reiher, "Real-Time Quantum Chemistry", C4 Workshop, Rüschlikon, Switzerland, 2017.
A. C. Vaucher, M. Reiher, "Real-Time Quantum Chemistry", 8th Molecular Quantum Mechanics, Uppsala, Sweden, 2016.
T. Husch, F. Krausbeck, J. Proppe, G. N. Simm, A. C. Vaucher, M. Reiher, "Exploration of Complex Chemical Reaction Mechanisms", Exploring Chemical Space with Machine Learning and Quantum Mechanics, Zurich, Switzerland, 2016.
A. C. Vaucher, M. P. Haag, M. Reiher, "Modern human-molecule interaction — molecular feedback in a virtual laboratory", Novartis Day, Zurich, Switzerland, 2015.
Other publications
A. Cardinale, A. Castrogiovanni, T. Gaudin, J. Geluykens, T. Laino, M. Manica, D. Probst, P. Schwaller, A. Sobczyk, A. Toniato, A. C. Vaucher, H. Wolf, F. Zipoli,
Fuelling the Digital Chemistry Revolution with Language Models,
Chimia, 2023, 77, 484-488.
A. C. Vaucher,
One Bronze Medal for Switzerland at the 48th International Chemistry Olympiad in Tbilisi, Georgia,
Chimia, 2016, 70, 911-912.
P. E. Ludwig, A. C. Vaucher, T. P. Lê, Y. Suter,
Two Bronze Medals for Switzerland at the 46th International Chemistry Olympiad in Hanoi, Vietnam,
Chimia 2015, 69, 71-72.
B. I. M. Wicky, S. Keller, P. Ludwig, P., A. Vaucher,
Two Bronze Medals for Switzerland at the 44th International Chemistry Olympiad Held in Washington DC, USA,
Chimia 2013, 67, 351-352.
K. Birbaum, P. Ludwig, B. Wicky, A. Vaucher,
Two Bronze Medals for Switzerland at the 43rd International Chemistry Olympiad in Ankara, Turkey,
Chimia 2012, 66, 136-137.