| 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 | 132 | 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 | 126 | 2019 |
| Two-step machine learning enables optimized nanoparticle synthesis F Mekki-Berrada, Z Ren, T Huang, WK Wong, F Zheng, J Xie, IPS Tian, ... npj Computational Materials 7 (1), 1-10, 2021 | 35 | 2021 |
| Inverse design of crystals using generalized invertible crystallographic representation Z Ren, J Noh, S Tian, F Oviedo, G Xing, Q Liang, A Aberle, Y Liu, Q Li, ... arXiv preprint arXiv:2005.07609, 2020 | 24 | 2020 |
| 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 | 21 | 2020 |
| 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 | 11 | 2022 |
| Physics-guided characterization and optimization of solar cells using surrogate machine learning model Z Ren, F Oviedo, H Xue, M Thway, K Zhang, N Li, JD Perea, M Layurova, ... 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC), 3054-3058, 2019 | 11 | 2019 |
| Multi‐fidelity high‐throughput optimization of electrical conductivity in P3HT‐CNT composites D Bash, Y Cai, V Chellappan, SL Wong, X Yang, P Kumar, JD Tan, ... Advanced Functional Materials 31 (36), 2102606, 2021 | 7 | 2021 |
| Machine learning and high-throughput robust design of P3HT-CNT composite thin films for high electrical conductivity D Bash, Y Cai, V Chellappan, SL Wong, Y Xu, P Kumar, J Da Tan, ... arXiv preprint arXiv:2011.10382, 2020 | 7 | 2020 |
| 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 | 4 | 2020 |
| Polymer MEMS sensor for flow monitoring in biomedical device applications AGP Kottapalli, Z Shen, M Asadnia, S Tian, K Tao, J Miao, ... 2017 IEEE 30th International Conference on Micro Electro Mechanical Systems …, 2017 | 4 | 2017 |
| 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 | 3 | 2020 |
| Accelerating photovoltaic materials development via high-throughput experiments and machine-learning-assisted diagnosis S Sun, NTP Hartono, ZD Ren, F Oviedo, AM Buscemi, M Layurova, ... arXiv preprint arXiv:1812.01025, 2018 | 3 | 2018 |
| Transfer Learning for Rapid Extraction of Thickness from Optical Spectra of Semiconductor Thin Films SIP Tian, Z Ren, S Venkataraj, Y Cheng, D Bash, F Oviedo, J Senthilnath, ... arXiv preprint arXiv:2207.02209, 2022 | | 2022 |
| What Information is Necessary and Sufficient to Predict Materials Properties using Machine Learning? SIP Tian, A Walsh, Z Ren, Q Li, T Buonassisi arXiv preprint arXiv:2206.04968, 2022 | | 2022 |
| Extracting Thin-film Optical Parameters from Spectrophotometric Data by Evolutionary Optimization R Dutta, SIP Tian, Z Liu, S Venkataraj, Y Cheng, D Bash, T Buonassisi, ... | | 2021 |
| Fast classification of small X-ray diffraction datasets using data augmentation and deep neural networks TB Felipe Oviedo, Zekun Ren, Shijing Sun, Charlie Settens, Zhe Liu, Noor ... NeurIPS 2018, 2018 | | 2018 |
