Florian Häse
University of Toronto(CA)Vector Institute(CA)
Publications by Year
Research Areas
Machine Learning in Materials Science, Innovative Microfluidic and Catalytic Techniques Innovation, Computational Drug Discovery Methods, Spectroscopy and Quantum Chemical Studies, Process Optimization and Integration
Most-Cited Works
- → Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation(2020)726 cited
- → Machine-learned potentials for next-generation matter simulations(2021)543 cited
- → Phoenics: A Bayesian Optimizer for Chemistry(2018)372 cited
- → Next-Generation Experimentation with Self-Driving Laboratories(2019)365 cited
- → On scientific understanding with artificial intelligence(2022)330 cited
- → Machine learning directed drug formulation development(2021)276 cited
- → Data-science driven autonomous process optimization(2021)223 cited
- → Machine learning models to accelerate the design of polymeric long-acting injectables(2023)190 cited
- → ChemOS: Orchestrating autonomous experimentation(2018)166 cited
- → Chimera: enabling hierarchy based multi-objective optimization for self-driving laboratories(2018)159 cited