Loïc M. Roch

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Alan Aspuru-GuzikProfessor of Chemistry and Computer Science, University of Toronto (starting July 1, 2018)Adresse e-mail validée de utoronto.ca
Christoph KreisbeckChief Executive OfficerAdresse e-mail validée de aixelo.com
Kim BaldridgeAdresse e-mail validée de tju.edu.cn
Semion SaikinKebotix, Inc.Adresse e-mail validée de kebotix.com
Daniel P. TaborTexas A&M University (Department of Chemistry)Adresse e-mail validée de chem.tamu.edu
Jay S. SiegelCSU-Northridge; Princeton; U. Strasbourg; UC-San Diego; U. Zurich; Tianjin U., U. Freiburg, HKUAdresse e-mail validée de hku.hk
Dennis SheberlaPostdoctoral Associate, Harvard UniversityAdresse e-mail validée de g.harvard.edu
Benji MaruyamaAir Force Research LaboratoryAdresse e-mail validée de us.af.mil
Muratahan AykolGoogle DeepMindAdresse e-mail validée de google.com
Benjamin Sanchez-LengelingResearch Scientist at Google DeepmindAdresse e-mail validée de google.com
Jerome F GonthierSenior Staff Scientist, QC WareAdresse e-mail validée de qcware.com
Kay SeverinEcole Polytechnique Fédérale de Lausanne (EPFL)Adresse e-mail validée de epfl.ch
Stephan SteinmannCNRS, Ecole Normale Supérieure de LyonAdresse e-mail validée de ens-lyon.fr
Michael GraetzelProfessor, EPFLAdresse e-mail validée de epfl.ch
Jacques-E. MoserProfessor of physical chemistry, Ecole polytechnique fédérale de LausanneAdresse e-mail validée de epfl.ch
Joël TeuscherAdresse e-mail validée de joelteuscher.ch
Angelos MichaelidesUniversity of CambridgeAdresse e-mail validée de cam.ac.uk
sandro sorellaSISSA- International School of Advanced Studies DEMOCRITOS Simulation Centre CNR-IOMAdresse e-mail validée de sissa.it
Dario AlfeProfessor of Physics at University College London and Universita' di Napoli Federico IIAdresse e-mail validée de ucl.ac.uk
Clemence CorminboeufProfessor of Chemistry, EPFL

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Loïc M. Roch

Chief Technology Officer & co-founder, Atinary Technologies

Adresse e-mail validée de atinary.com - Page d'accueil

Artificial Intelligence Self-driving labs Materials discovery Process optimization


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Accelerating the discovery of materials for clean energy in the era of smart automation DP Tabor, LM Roch, SK Saikin, C Kreisbeck, D Sheberla, JH Montoya, ... Nat. Rev. Mater. 3, 5-20, 2018	698	2018
Self-driving laboratory for accelerated discovery of thin-film materials BP MacLeod, FGL Parlane, TD Morrissey, F Häse, LM Roch, ... Science Advances 6 (20), eaaz8867, 2020	505	2020
Phoenics: A Bayesian optimizer for chemistry F Häse, LM Roch, C Kreisbeck, A Aspuru-Guzik ACS central science 4 (9), 1134-1145, 2018	327	2018
Next-generation experimentation with self-driving laboratories F Häse, LM Roch, A Aspuru-Guzik Trends in Chemistry 1 (3), 282-291, 2019	273	2019
Beyond Ternary OPV: High‐Throughput Experimentation and Self‐Driving Laboratories Optimize Multicomponent Systems S Langner, F Häse, J Darío Perea, T Stubhan, J Hauch, LM Roch, ... Advanced Materials, 1907801, 2020	231	2020
Data-science driven autonomous process optimization M Christensen, LPE Yunker, F Adedeji, F Häse, LM Roch, T Gensch, ... Communications Chemistry 4 (1), 112, 2021	165	2021
ChemOS: orchestrating autonomous experimentation LM Roch, F Häse, C Kreisbeck, T Tamayo-Mendoza, LPE Yunker, ... Science Robotics 3 (19), eaat5559, 2018	160	2018
ChemOS: An orchestration software to democratize autonomous discovery LM Roch, F Häse, C Kreisbeck, T Tamayo-Mendoza, LPE Yunker, ... PLoS ONE 15 (4), e0229862, 2020	149	2020
ChemOS: An Orchestration Software to Democratize Autonomous Discovery LM Roch, F Häse, A Aspuru-Guzik Artificial Intelligence in Drug Discovery 75, 351, 2020	147	2020
Chimera: enabling hierarchy based multi-objective optimization for self-driving laboratories F Häse, LM Roch, A Aspuru-Guzik Chemical science 9 (39), 7642-7655, 2018	145	2018
Gryffin: An algorithm for Bayesian optimization of categorical variables informed by expert knowledge F Häse, M Aldeghi, RJ Hickman, LM Roch, A Aspuru-Guzik Applied Physics Reviews 8 (3), 2021	129	2021
Materials Acceleration Platform: Accelerating Advanced Energy Materials Discovery by Integrating High-Throughput Methods with Artificial Intelligence. A Aspuru-Guzik, K Persson, A Alexander-Katz, C Amador, D Solis-Ibarra, ... http://mission-innovation.net/wp-content/uploads/2018/01/Mission-Innovation …, 2018	105	2018
A Bayesian approach to predict solubility parameters B Sanchez‐Lengeling, LM Roch, JD Perea, S Langner, CJ Brabec, ... Advanced Theory and Simulations 2 (1), 1800069, 2019	86	2019
Olympus: a benchmarking framework for noisy optimization and experiment planning F Häse, M Aldeghi, RJ Hickman, LM Roch, M Christensen, E Liles, ... Machine Learning: Science and Technology 2 (3), 035021, 2021	82	2021
Designing and understanding light-harvesting devices with machine learning F Häse, LM Roch, P Friederich, A Aspuru-Guzik Nature Communications 11 (1), 4587, 2020	79	2020
π-Depletion as criterion to predict π-stacking ability J Gonthier, S Steinmann, L Roch, A Ruggi, N Luisier, K Severin, ... Chemical Communications (London) 48 (74), 9239 - 9241, 2012	79	2012
Interface molecular engineering for laminated monolithic perovskite/silicon tandem solar cells with 80.4% fill factor CO Ramírez Quiroz, GD Spyropoulos, M Salvador, LM Roch, M Berlinghof, ... Advanced Functional Materials 29 (40), 1901476, 2019	55	2019
Pentaindenocorannulene: Properties, Assemblies and C60 Complex S Lampart, LM Roch, AK Dutta, Y Wang, R Warshamanage, AD Finke, ... Angewandte Chemie International Edition 128 (47), 14868 - 14872, 2016	52	2016
Kinetics of the Regeneration by Iodide of Dye Sensitizers Adsorbed on Mesoporous Titania J Teuscher, A Marchioro, J Andrès, LM Roch, M Xu, SM Zakeeruddin, ... Journal of Physical Chemistry C 118 (30), 17108 - 17115, 2014	36	2014
Toward Accurate Adsorption Energetics on Clay Surfaces A Zen, LM Roch, SJ Cox, X Hu, S Sorella, D Alfè, A Michaelides Journal of Physical Chemistry C 120 (46), 26402 - 26413, 2016	34	2016

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