Loı̈c M. Roch

Institute for Work and Health — Switzerland

Materials Science · Physical Sciences

22h-index3.2kcitations79works9.62yr avg
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Research Topics

Machine Learning in Materials Science(33), Innovative Microfluidic and Catalytic Techniques Innovation(16), Crystallization and Solubility Studies(9), Computational Drug Discovery Methods(8), Synthesis and Properties of Aromatic Compounds(8)

Publications79 total

Bayesian Optimization for Resource-Efficient Hydroformylation
ACS Catalysis·2025
Bridging Innovation and Efficiency: The Promises and Challenges of Self-Driving Labs as Sustainable Drivers for Chemistry
CHIMIA International Journal for Chemistry·2025· 1 citedOpen Access
Best practices for multi-fidelity Bayesian optimization in materials and molecular research
Nature Computational Science·2025· 9 citedOpen Access
Best Practices for Multi-Fidelity Bayesian Optimization in Materials and Molecular Research
arXiv (Cornell University)·2024· 1 citedOpen Access
Turbocharge R&D with Self-Driving Labs and Bayesian Optimization
2024
Accelerated exploration of heterogeneous CO2 hydrogenation catalysts by Bayesian-optimized high-throughput and automated experimentation
Chem Catalysis·2024· 32 citedOpen Access
Combining Bayesian optimization and automation to simultaneously optimize reaction conditions and routes
Chemical Science·2024· 24 citedOpen Access
Accelerated Exploration of Heterogeneous CO2 Hydrogenation Catalysts by Bayesian Optimized High-throughput and Automated Experimentation.
2023· 11 citedOpen Access
Raw, processed and merged Data for Swiss Cat+ East A1 project related to the automated and high-throughput Bayesian Optimization of CO2 hydrogenation heterogeneous catalysts
2023Open Access
Raw, processed and merged Data for Swiss Cat+ East A1 project related to the automated and high-throughput Bayesian Optimization of CO2 hydrogenation heterogeneous catalysts
Zenodo (CERN European Organization for Nuclear Research)·2023Open Access
How to Accelerate R&D and Optimize Experiment Planning with Machine Learning and Data Science
CHIMIA International Journal for Chemistry·2023· 15 citedOpen Access
Equipping data-driven experiment planning for Self-driving Laboratories with semantic memory: case studies of transfer learning in chemical reaction optimization
Reaction Chemistry & Engineering·2023· 15 cited
Serendipity based recommender system for perovskites material discovery: balancing exploration and exploitation across multiple models
2022· 5 citedOpen Access
Serendipity based recommender system for perovskites material discovery: balancing exploration and exploitation across multiple models
2022· 9 citedOpen Access
Equipping data-driven experiment planning for Self-driving Laboratories with semantic memory: case studies of transfer learning in chemical reaction optimization
2022· 15 citedOpen Access
Data-science driven autonomous process optimization
Communications Chemistry·2021· 223 citedOpen Access
Gemini: Dynamic Bias Correction for Autonomous Experimentation and Molecular Simulation
arXiv (Cornell University)·2021· 1 citedOpen Access
Unexpected three-state hydrochromism of a donor–acceptor self-complex with fluctuations in relative humidity
Chemical Communications·2021· 5 cited
Data-Science Driven Autonomous Process Optimization
2020· 3 citedOpen Access
Data-science driven autonomous process optimization
2020· 10 citedOpen Access
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Frequent Co-authors

Alán Aspuru‐Guzik(24), Florian Häse(19), Kim K. Baldridge(10), Lars P. E. Yunker(8), Jason E. Hein(8), Christoph Kreisbeck(7), Hermann Tribukait(6), Jay S. Siegel(6), Christoph J. Brabec(5), Teresa Tamayo-Mendoza(5), José Darío Perea(5), Alberto García-Durán(5), Pascal Friederich(4), Salvador León(4), Daniel Pacheco Gutiérrez(4), Semion K. Saikin(3), Melodie Christensen(3), Folarin Adedeji(3), Tobias Gensch(3), Gabriel dos Passos Gomes(3)