| Can machine learning identify the next high-temperature superconductor? Examining extrapolation performance for materials discovery B Meredig, E Antono, C Church, M Hutchinson, J Ling, S Paradiso, ... Molecular Systems Design & Engineering 3 (5), 819-825, 2018 | 174 | 2018 |
| High-dimensional materials and process optimization using data-driven experimental design with well-calibrated uncertainty estimates J Ling, M Hutchinson, E Antono, S Paradiso, B Meredig Integrating Materials and Manufacturing Innovation 6, 207-217, 2017 | 167 | 2017 |
| Block copolymer self assembly during rapid solvent evaporation: insights into cylinder growth and stability SP Paradiso, KT Delaney, CJ García-Cervera, HD Ceniceros, ... ACS Macro Letters 3 (1), 16-20, 2014 | 99 | 2014 |
| Overcoming data scarcity with transfer learning ML Hutchinson, E Antono, BM Gibbons, S Paradiso, J Ling, B Meredig arXiv preprint arXiv:1711.05099, 2017 | 81 | 2017 |
| Inverse design of bulk morphologies in multiblock polymers using particle swarm optimization MR Khadilkar, S Paradiso, KT Delaney, GH Fredrickson Macromolecules 50 (17), 6702-6709, 2017 | 40 | 2017 |
| Machine learning–based reduce order crystal plasticity modeling for ICME applications M Yuan, S Paradiso, B Meredig, SR Niezgoda Integrating Materials and Manufacturing Innovation 7, 214-230, 2018 | 38 | 2018 |
| Perspective: Materials informatics across the product lifecycle: Selection, manufacturing, and certification GJ Mulholland, SP Paradiso Apl Materials 4 (5), 053207, 2016 | 36 | 2016 |
| Swarm intelligence platform for multiblock polymer inverse formulation design SP Paradiso, KT Delaney, GH Fredrickson ACS Macro Letters 5 (8), 972-976, 2016 | 32 | 2016 |
| Cyclic solvent annealing improves feature orientation in block copolymer thin films SP Paradiso, KT Delaney, CJ García-Cervera, HD Ceniceros, ... Macromolecules 49 (5), 1743-1751, 2016 | 27 | 2016 |
| Machine learning for alloy composition and process optimization J Ling, E Antono, S Bajaj, S Paradiso, M Hutchinson, B Meredig, ... Turbo Expo: Power for Land, Sea, and Air 51128, V006T24A005, 2018 | 25 | 2018 |
| Using machine learning to explore formulations recipes with new ingredients ML Hutchinson, ES Kim, RM Latture, SP Paradiso, JB Ling US Patent 10,984,145, 2021 | 6 | 2021 |
| Citrine informatics lolo M Hutchinson, S Paradiso, L Ward | 6 | 2016 |
| Overcoming data scarcity with transfer learning. arXiv 2017 ML Hutchinson, E Antono, BM Gibbons, S Paradiso, J Ling, B Meredig arXiv preprint arXiv:1711.05099, 0 | 6 | |
| Solving industrial materials problems by using machine learning across diverse computational and experimental data M Hutchinson, E Antono, B Gibbons, S Paradiso, J Ling, B Meredig APS March Meeting Abstracts 2018, K32. 002, 2018 | 4 | 2018 |
| Cyclic Solvent Vapor Annealing for Rapid, Robust Vertical Orientation of Features in BCP Thin Films S Paradiso, K Delaney, G Fredrickson APS March Meeting Abstracts 2015, D42. 007, 2015 | | 2015 |
| Computational Design and Morphology Engineering of Multiblock Polymer Films SP Paradiso University of California, Santa Barbara, 2015 | | 2015 |
| Dynamical SCFT Simulations of Solvent Annealed Thin Films S Paradiso, K Delaney, H Ceniceros, C Garcia-Cervera, G Fredrickson APS March Meeting Abstracts 2014, S19. 009, 2014 | | 2014 |
| Evaporation-induced ordering in solution-cast block copolymer thin films S Paradiso, K Delaney, H Ceniceros, C Garcia-Cervera, G Fredrickson APS March Meeting Abstracts 2013, T34. 011, 2013 | | 2013 |
| Particle and fluid diffusivity of non-colloidal suspensions E Filippidi, A Franceschini, CL Cheung, J Tutmaher, S Paradiso, T Jain, ... APS March Meeting Abstracts 2011, Z9. 015, 2011 | | 2011 |
Bryce MeredigCSO, Citrine InformaticsVerified email at u.northwestern.edu
