CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models
- Vijil Chenthamarakshan
- Payel Das
- et al.
- 2020
- NeurIPS 2020
Bio
Teo received the Master degree in theoretical chemistry in 2001 (University of Pisa and Scuola Normale Superiore di Pisa, Italy) and the doctorate in computational chemistry in 2006 (Scuola Normale Superiore di Pisa, Italy) defending a thesis on 'Multi-Grid QM/ MM Approaches in ab initio Molecular Dynamics' supervised by Prof. Dr. Michele Parrinello. From 2006 to 2008, Teo worked as a post-doctoral researcher in the research group of Prof. Dr. Jürg Hutter at the University of Zurich, contributing to the development of the CP2K simulation package. In 2008, Teo joined the IBM Research - Zurich Laboratory (ZRL) as Research Scientist. He is currently Distinguished Research Scientist and manager.
His research interests focus on developing machine learning/artificial intelligence technologies to digitalize chemistry and materials science, with IBM RXN for chemistry being an example of a recent community success. In 2022, the team received the Sandmeyer Award of the Swiss Chemical Society for the important contributions to the field of digital chemistry.
Publications
Completion of partial reaction equations
- Alain Vaucher
- Philippe Schwaller
- et al.
- 2020
- NeurIPS 2020
Data augmentation strategies to improve reaction yield predictions and estimate uncertainty
- Philippe Schwaller
- Alain Vaucher
- et al.
- 2020
- NeurIPS 2020
Transfer learning enables the molecular transformer to predict regio- and stereoselective reactions on carbohydrates
- Giorgio Pesciullesi
- Philippe Schwaller
- et al.
- 2020
- Nature Communications
Chemistry puppeteer: Enhancing the diversity of retrosynthetic predictions
- Alessandra Toniato
- Philippe Schwaller
- et al.
- 2020
- ACS Fall 2020
Reaction Transformers for Fingerprints, Classification and Atom-Mapping
- Philippe Schwaller
- Daniel Probst
- et al.
- 2020
- ACS Fall 2020
Automated extraction of chemical synthesis actions from experimental procedures
- Alain C. Vaucher
- Federico Zipoli
- et al.
- 2020
- Nature Communications
CP2K: An electronic structure and molecular dynamics software package -Quickstep: Efficient and accurate electronic structure calculations
- Thomas D. Kühne
- Marcella Iannuzzi
- et al.
- 2020
- Journal of Chemical Physics
Exploring chemical space using natural language processing methodologies for drug discovery
- Hakime Öztürk
- Arzucan Özgür
- et al.
- 2020
- Drug Discovery Today
Predicting retrosynthetic pathways using transformer-based models and a hyper-graph exploration strategy
- Philippe Schwaller
- Riccardo Petraglia
- et al.
- 2020
- Chemical Science
Patents
- US
- 11854670
- US
- 11133528
- US
- 11121409
- US
- 11016965
- US
- 10559847
- US
- 10170790
- US
- 9971736
Projects
AI for Scientific Discovery
Creating the AI-enabled lab for a new era of reproducible and collaborative experimentation
Lab that Learns
Leveraging AI foundation models and multi-cloud computing to usher in a new era of reproducible and collaborative experimentation for scientific discovery.
Blog posts
Thieme trains IBM RXN for Chemistry with high-quality data
NewsAlain Vaucher, Fiona Shortt de Hernandez, Sascha Hausberg, and Teodoro Laino6 minute readIBM RXN for Chemistry: Unveiling the grammar of the organic chemistry language
ResearchPhilippe Schwaller, Hendrik Strobelt, Teodoro Laino, and Benjamin Hoover7 minute readIBM RXN for Chemistry: Automatically cleaning chemical reaction datasets
ResearchAlessandra Toniato and Teodoro Laino7 minute readIBM RXN: New AI model boosts mapping of chemical reactions
ResearchPhilippe Schwaller and Teodoro Laino5 minute read- See more blog posts
Top collaborators
MM
Matteo Manica
Senior Research Scientist
FZ
Federico Zipoli
Research Scientist
MA
MG
Mara Graziani
Research Scientist