CIS – “Get to know your neighbors” Seminar Series
“Accelerating Chemical Synthesis with Transformers”
Prof. Philippe Schwaller, Tenure Track Assistant Professor and Head of LIAC
Monday, Sept. 5, 2022 3:15 – 4:15pm | Hybrid
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Note: As this event is reserved to the EPFL community please register with your @epfl.ch email address.
 P. Schwaller et al., ‘Molecular Transformer: A Model for Uncertainty-Calibrated Chemical Reaction Prediction’, ACS Cent. Sci., vol. 5, no. 9, pp. 1572–1583, 2019, doi: 10.1021/acscentsci.9b00576.
 G. Pesciullesi, P. Schwaller, T. Laino, and J.-L. Reymond, ‘Transfer learning enables the molecular transformer to predict regio-and stereoselective reactions on carbohydrates’, Nat. Commun., vol. 11, no. 1, pp. 1–8, 2020.
 P. Schwaller et al., ‘Predicting retrosynthetic pathways using transformer-based models and a hyper-graph exploration strategy’, Chem. Sci., vol. 11, pp. 3316–3325, 2020, doi: 10.1039/C9SC05704H.
 A. C. Vaucher, F. Zipoli, J. Geluykens, V. H. Nair, P. Schwaller, and T. Laino, ‘Automated extraction of chemical synthesis actions from experimental procedures’, Nat. Commun., vol. 11, no. 1, p. 3601, Jul. 2020, doi: 10.1038/s41467-020-17266-6.
 A. C. Vaucher, P. Schwaller, J. Geluykens, V. H. Nair, A. Iuliano, and T. Laino, ‘Inferring experimental procedures from text-based representations of chemical reactions’, Nat. Commun., vol. 12, no. 1, p. 2573, Dec. 2021, doi: 10.1038/s41467-021-22951-1.
 P. Schwaller et al., ‘Mapping the space of chemical reactions using attention-based neural networks’, Nat. Mach. Intell., vol. 3, no. 2, pp. 144–152, Feb. 2021, doi: 10.1038/s42256-020-00284-w.
 P. Schwaller, B. Hoover, J.-L. Reymond, H. Strobelt, and T. Laino, ‘Extraction of organic chemistry grammar from unsupervised learning of chemical reactions’, Sci. Adv., vol. 7, no. 15, p. eabe4166, Apr. 2021, doi: 10.1126/sciadv.abe4166.
 P. Schwaller et al., ‘Machine intelligence for chemical reaction space’, WIREs Comput. Mol. Sci., Mar. 2022, doi: 10.1002/wcms.1604
Philippe Schwaller received a bachelor’s and master’s degree in Materials Science and Engineering from EPFL. While working for IBM Research (2017-2021), Philippe completed an MPhil degree in Physics at the University of Cambridge and a PhD in Chemistry and Molecular Sciences with the Reymond group at the University of Bern. In February 2022, Philippe joined EPFL as a tenure-track assistant professor in the Institute of Chemical Sciences and Engineering. He leads the Laboratory of Artificial Chemical Intelligence (LIAC), which works on AI-accelerated discovery and synthesis of molecules. Philippe is also a core PI of the NCCR Catalysis, a Swiss centre for sustainable chemistry research, education, and innovation.