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Sean Paradiso
Sean Paradiso
Citrine Informatics
Verified email at mrl.ucsb.edu
Title
Cited by
Cited by
Year
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
2152018
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
1962017
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
1032014
Overcoming data scarcity with transfer learning
ML Hutchinson, E Antono, BM Gibbons, S Paradiso, J Ling, B Meredig
arXiv preprint arXiv:1711.05099, 2017
982017
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
492017
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 (4), 214-230, 2018
442018
Perspective: Materials informatics across the product lifecycle: Selection, manufacturing, and certification
GJ Mulholland, SP Paradiso
Apl Materials 4 (5), 2016
392016
Swarm intelligence platform for multiblock polymer inverse formulation design
SP Paradiso, KT Delaney, GH Fredrickson
ACS Macro Letters 5 (8), 972-976, 2016
352016
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
282016
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
252018
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
112021
ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition
J Ling, E Antono, S Bajaj, S Paradiso, M Hutchinson, B Meredig, ...
Oslo, 2018
92018
Citrine informatics lolo
M Hutchinson, S Paradiso, L Ward
82016
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
42018
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
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Articles 1–20