Felipe Oviedo
Felipe Oviedo
Microsoft AI for Good | Massachusetts Institute of Technology
Verified email at - Homepage
Cited by
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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
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), 1-9, 2019
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), 1-9, 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
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
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), 1-9, 2020
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
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
Residual stress in high-velocity impact coatings: parametric finite element analysis approach
F Oviedo, A Valarezo
Journal of Thermal Spray Technology 29 (6), 1268-1288, 2020
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
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
Accelerated Development of Perovskite-Inspired Materials via High-Throughput Synthesis and Machine-Learning Diagnosis. Joule 3, 1437–1451
S Sun, NTP Hartono, ZD Ren, F Oviedo, AM Buscemi, M Layurova, ...
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
Rapid and accurate thin film thickness extraction via UV-Vis and machine learning
SIP Tian, Z Liu, V Chellappan, YF Lim, Z Ren, F Oviedo, BH Teo, J Thapa, ...
2020 47th IEEE Photovoltaic Specialists Conference (PVSC), 0128-0132, 2020
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
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
Accelerated Development of Photovoltaics by Physics-Informed Machine Learning
JFO Perhavec
Massachusetts Institute of Technology, Department of Mechanical Engineering, 2020
Machine Learning in Materials Science
KT Butler, F Oviedo, P Canepa
American Chemical Society, 2022
Transfer Learning for Rapid Extraction of Thickness from Optical Spectra of Semiconductor Thin Films
SI Parker Tian, Z Ren, S Venkataraj, Y Cheng, D Bash, F Oviedo, ...
arXiv e-prints, arXiv: 2207.02209, 2022
BankNote-Net: Open dataset for assistive universal currency recognition
F Oviedo, S Vinnakota, E Seleznev, H Malhotra, S Shaikh, JL Ferres
arXiv preprint arXiv:2204.03738, 2022
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