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Danial Khatamsaz
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Multi-objective materials bayesian optimization with active learning of design constraints: Design of ductile refractory multi-principal-element alloys
D Khatamsaz, B Vela, P Singh, DD Johnson, D Allaire, R Arróyave
Acta Materialia 236, 118133, 2022
322022
Efficiently exploiting process-structure-property relationships in material design by multi-information source fusion
D Khatamsaz, A Molkeri, R Couperthwaite, J James, R Arróyave, D Allaire, ...
Acta Materialia, 116619, 2021
282021
Adaptive active subspace-based efficient multifidelity materials design
D Khatamsaz, A Molkeri, R Couperthwaite, J James, R Arróyave, ...
Materials & Design 209, 110001, 2021
272021
Bayesian optimization with active learning of design constraints using an entropy-based approach
D Khatamsaz, B Vela, P Singh, DD Johnson, D Allaire, R Arróyave
npj Computational Materials 9 (1), 49, 2023
212023
Materials design through batch bayesian optimization with multisource information fusion
R Couperthwaite, A Molkeri, D Khatamsaz, A Srivastava, D Allaire, ...
Jom 72, 4431-4443, 2020
212020
On the importance of microstructure information in materials design: PSP vs PP
A Molkeri, D Khatamsaz, R Couperthwaite, J James, R Arróyave, D Allaire, ...
Acta Materialia 223, 117471, 2022
152022
Bayesian optimization of multiobjective functions using multiple information sources
D Khatamsaz, L Peddareddygari, S Friedman, D Allaire
AIAA Journal 59 (6), 1964-1974, 2021
142021
Efficient multi-information source multiobjective bayesian optimization
D Khatamsaz, L Peddareddygari, S Friedman, DL Allaire
AIAA Scitech 2020 Forum, 2127, 2020
142020
A perspective on Bayesian methods applied to materials discovery and design
R Arróyave, D Khatamsaz, B Vela, R Couperthwaite, A Molkeri, P Singh, ...
MRS communications 12 (6), 1037-1049, 2022
102022
A comparison of reification and cokriging for sequential multi-information source fusion
D Khatamsaz, DL Allaire
AIAA Scitech 2021 Forum, 1477, 2021
102021
Data-augmented modeling for yield strength of refractory high entropy alloys: A bayesian approach
B Vela, D Khatamsaz, C Acemi, I Karaman, R Arróyave
Acta Materialia 261, 119351, 2023
72023
Materials design using an active subspace-based batch bayesian optimization approach
D Khatamsaz, R Arroyave, DL Allaire
AIAA SCITECH 2022 Forum, 0075, 2022
52022
The BAREFOOT optimization framework
R Couperthwaite, D Khatamsaz, A Molkeri, J James, A Srivastava, ...
Integrating Materials and Manufacturing Innovation 10, 644-660, 2021
52021
Towards inverse microstructure-centered materials design using generative phase-field modeling and deep variational autoencoders
V Attari, D Khatamsaz, D Allaire, R Arroyave
Acta Materialia 259, 119204, 2023
42023
A physics informed bayesian optimization approach for material design: application to NiTi shape memory alloys
D Khatamsaz, R Neuberger, AM Roy, SH Zadeh, R Otis, R Arróyave
npj Computational Materials 9 (1), 221, 2023
32023
Multi-objective Bayesian alloy design using multi-task Gaussian processes
D Khatamsaz, B Vela, R Arróyave
Materials Letters 351, 135067, 2023
22023
Multi-Objective Bayesian Optimization using an Active Subspace-based Approach
D Khatamsaz, DL Allaire
AIAA SCITECH 2023 Forum, 2203, 2023
12023
Asynchronous Multi-Information Source Bayesian Optimization
D Khatamsaz, R Arroyave, DL Allaire
Journal of Mechanical Design 146 (10), 2024
2024
Data-driven study of composition-dependent phase compatibility in NiTi shape memory alloys
SH Zadeh, C Cakirhan, D Khatamsaz, J Broucek, TD Brown, X Qian, ...
arXiv preprint arXiv:2402.12520, 2024
2024
Efficient Propagation of Uncertainty via Reordering Monte Carlo Samples
D Khatamsaz, V Attari, R Arroyave, DL Allaire
arXiv preprint arXiv:2302.04945, 2023
2023
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Articles 1–20