Felipe Oviedo

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Tonio BuonassisiMassachusetts Institute of TechnologyVerificeret mail på mit.edu
ZEKUN RENSingapore MIT Alliance for Research and TechnologyVerificeret mail på smart.mit.edu
Zhe LiuMassachusetts Institute of TechnologyVerificeret mail på mit.edu
Siyu Isaac Parker TianPhD, National University of SingaporeVerificeret mail på u.nus.edu
Ian Marius PetersForschungszentrum JülichVerificeret mail på fz-juelich.de
Noor Titan Putri HartonoData Scientist, SolarLab Aiko EuropeVerificeret mail på solarlab-aiko.com
Janak ThapaMassachusetts Institute of TechnologyVerificeret mail på mit.edu
Savitha RamasamyInstitute of Infocomm Research; Senior Member, IEEEVerificeret mail på i2r.a-star.edu.sg
A Gilad KusneMaterials Measurement & Science Division, NIST & Materials Science & Engineering, UMDVerificeret mail på umd.edu
Prof Armin ABERLENational University of SingaporeVerificeret mail på nus.edu.sg
Qianxiao LiAssistant Professor, Department of Mathematics and Institute for Functional Intelligent MaterialsVerificeret mail på nus.edu.sg
Armi TiihonenPostdoctoral fellow at Massachusetts Institute of TechnologyVerificeret mail på mit.edu
Brian L. DeCostNational Institute of Standards and TechnologyVerificeret mail på nist.gov
Christoph J. BrabecFriedrich Alexander Universität Erlangen Nürnberg; Forschungszentrum JülichVerificeret mail på fau.de
Jason J. YooAppleVerificeret mail på apple.com
Antonio M. BuscemiMassachusetts Institute of TechnologyVerificeret mail på mit.edu
Giuseppe RomanoResearch Scientist, MITVerificeret mail på mit.edu
Maung ThwayResearch Assistant, Solar Energy Research Institute of SingaporeVerificeret mail på nus.edu.sg
Juan-Pablo Correa-BaenaAssociate Professor, Georgia TechVerificeret mail på gatech.edu
Hansong XueSingapore University of Technology and DesignVerificeret mail på sutd.edu.sg

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Felipe Oviedo

MIT

Verificeret mail på mit.edu

machine learning deep learning material science chemistry


Titel Sortér efter henvisninger Sortér efter årstal Sortér efter titel	Citeret af Citeret af	År
Accelerated development of perovskite-inspired materials via high-throughput synthesis and machine-learning diagnosis S Sun, NTP Hartono, ZD Ren, F Oviedo, AM Buscemi, M Layurova, ... Joule 3 (6), 1437-1451, 2019	287	2019
Fast and interpretable classification of small X-ray diffraction datasets using data augmentation and deep neural networks F Oviedo, Z Ren, S Sun, C Settens, Z Liu, NTP Hartono, S Ramasamy, ... npj Computational Materials 5 (1), 60, 2019	281	2019
An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties Z Ren, SIP Tian, J Noh, F Oviedo, G Xing, J Li, Q Liang, R Zhu, AG Aberle, ... Matter 5 (1), 314-335, 2022	177*	2022
Interpretable and explainable machine learning for materials science and chemistry F Oviedo, JL Ferres, T Buonassisi, KT Butler Accounts of Materials Research 3 (6), 597-607, 2022	160	2022
How machine learning can help select capping layers to suppress perovskite degradation NTP Hartono, J Thapa, A Tiihonen, F Oviedo, C Batali, JJ Yoo, Z Liu, R Li, ... Nature communications 11 (1), 4172, 2020	147	2020
A data fusion approach to optimize compositional stability of halide perovskites S Sun, A Tiihonen, F Oviedo, Z Liu, J Thapa, Y Zhao, NTP Hartono, ... Matter 4 (4), 1305-1322, 2021	131	2021
Predicting the locations of cryptic pockets from single protein structures using the PocketMiner graph neural network A Meller, MD Ward, JH Borowsky, JM Lotthammer, M Kshirsagar, ... Biophysical journal 122 (3), 445a, 2023	95	2023
Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaics Z Ren, F Oviedo, M Thway, SIP Tian, Y Wang, H Xue, J Dario Perea, ... npj Computational Materials 6 (1), 9, 2020	58*	2020
Machine learning in materials science KT Butler, F Oviedo, P Canepa American Chemical Society, 2022	43	2022
Combinatorial polycation synthesis and causal machine learning reveal divergent polymer design rules for effective pDNA and ribonucleoprotein delivery R Kumar, N Le, F Oviedo, ME Brown, TM Reineke Jacs Au 2 (2), 428-442, 2022	40	2022
Developing a robust recombination contact to realize monolithic perovskite tandems with industrially common p-type silicon solar cells RLZ Hoye, KA Bush, F Oviedo, SE Sofia, M Thway, X Li, Z Liu, J Jean, ... IEEE Journal of Photovoltaics 8 (4), 1023-1028, 2018	36	2018
An artificial intelligence dataset for solar energy locations in India A Ortiz, D Negandhi, SR Mysorekar, SK Nagaraju, J Kiesecker, ... Scientific Data 9 (1), 497, 2022	25	2022
Residual stress in high-velocity impact coatings: parametric finite element analysis approach F Oviedo, A Valarezo Journal of Thermal Spray Technology 29, 1268-1288, 2020	23	2020
Becoming good at AI for good M Kshirsagar, C Robinson, S Yang, S Gholami, I Klyuzhin, S Mukherjee, ... Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 664-673, 2021	21	2021
An open-source environmental chamber for materials-stability testing using an optical proxy R Keesey, A Tiihonen, AE Siemenn, TW Colburn, S Sun, NTP Hartono, ... Digital Discovery 2 (2), 422-440, 2023	13	2023
2019 IEEE 46th Photovoltaic Specialists Conf.(PVSC) Z Ren, F Oviedo, H Xue, M Thway, K Zhang, N Li, JD Perea, M Layurova, ... IEEE, 2019	13	2019
Ohmic shunts in two-terminal dual-junction solar cells with current mismatch F Oviedo, Z Liu, Z Ren, M Thway, T Buonassisi, IM Peters Japanese Journal of Applied Physics 56 (8S2), 08MA05, 2017	12	2017
Bridging the gap between photovoltaics R&D and manufacturing with data-driven optimization F Oviedo, Z Ren, X Hansong, SIP Tian, K Zhang, M Layurova, ... arXiv preprint arXiv:2004.13599, 2020	9	2020
Polymer design via SHAP and Bayesian machine learning optimizes pDNA and CRISPR ribonucleoprotein delivery RJ Dalal, F Oviedo, MC Leyden, TM Reineke Chemical Science 15 (19), 7219-7228, 2024	7	2024
Detecting microcracks in photovoltaics silicon wafers using varitional autoencoder Z Liu, F Oviedo, EM Sachs, T Buonassisi 2020 47th IEEE Photovoltaic Specialists Conference (PVSC), 0139-0142, 2020	6	2020

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