Growing strings in a chemical reaction space for searching retrosynthesis pathways
- 2023
- ACS Spring 2023
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
Cloud-based AI-driven autonomous lab
- 2023
- APS March Meeting 2023
Tools for Synthesis Planning, Automation, and Analytical Data Analysis
- Miruna Cretu
- Marvin Alberts
- et al.
- 2023
- Chimia
Prediction of Phase Diagrams and Associated Phase Structural Properties
- Federico Zipoli
- Victor Viterbo
- et al.
- 2022
- MRS-J 2022
Disconnection Aware Steering of Retrosynthesis Transformer to Facilitate Materials Design
- Amol Thakkar
- Andrea Antonia Byekwaso
- et al.
- 2022
- MRS Fall Meeting 2022
Enzeptional—Enzyme Optimization via a Generative Language Modeling-Based Evolutionary Algorithm
- 2022
- MRS Fall Meeting 2022
Learning a Reactive Potential for Silica-Water Through Uncertainty Attribution
- Swagata Roy
- Johannes Duerholt
- et al.
- 2022
- MRS Fall Meeting 2022
Data-driven Reaction Template Fingerprints
- Anubhab Chakraborty
- Amol Thakkar
- et al.
- 2022
- ChemRxiv
Large scale density estimation with polynomial expansions and Johnson-Lindenstrauss transformations
- Aleksandros Sobczyk
- Teodoro Laino
- et al.
- 2022
- ACS Fall 2022
Bridging the gap between rule-based expert systems and machine learning in computer-aided retrosynthetic design
- Daniel Probst
- Anastasia Sveshnikova
- et al.
- 2022
- ACS Fall 2022
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