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Ramin Bostanabad
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Journal Articles

Unsupervised Anomaly Detection via Nonlinear Manifold Learning

Amin Yousefpour, Mehdi Shishehbor, Zahra Zanjani Foumani, Ramin Bostanabad
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. November 2024, 24(11): 111008.
Paper No: JCISE-23-1278
https://doi.org/10.1115/1.4063642
Published Online: August 6, 2024
View Article titled, Unsupervised Anomaly Detection via Nonlinear Manifold Learning
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Topics: Manifolds, Errors
Journal Articles

Multi-Fidelity Design of Porous Microstructures for Thermofluidic Applications

Jonathan Tammer Eweis-Labolle, Chuanning Zhao, Yoonjin Won, Ramin Bostanabad
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. October 2024, 146(10): 101705.
Paper No: MD-23-1728
https://doi.org/10.1115/1.4064813
Published Online: March 18, 2024
View Article titled, Multi-Fidelity Design of Porous Microstructures for Thermofluidic Applications
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Topics: Design, Modeling
Journal Articles

Safeguarding Multi-Fidelity Bayesian Optimization Against Large Model Form Errors and Heterogeneous Noise

Zahra Zanjani Foumani, Amin Yousefpour, Mehdi Shishehbor, Ramin Bostanabad
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. June 2024, 146(6): 061703.
Paper No: MD-23-1380
https://doi.org/10.1115/1.4064160
Published Online: December 18, 2023
View Article titled, Safeguarding Multi-Fidelity Bayesian Optimization Against Large Model Form Errors and Heterogeneous Noise
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Topics: Design, Noise (Sound), Optimization, Uncertainty quantification, Modeling, Manifolds, Errors, Uncertainty
Includes: Supplementary data
Proceedings Papers

Mitigating the Effects of Source-Dependent Bias and Noise on Multi-Source Bayesian Optimization: Application to Materials Design

Zahra Zanjani Foumani, Amin Yousefpour, Mehdi Shishehbor, Ramin Bostanabad
Proc. ASME. IDETC-CIE2023, Volume 3B: 49th Design Automation Conference (DAC), V03BT03A010, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-114414
https://doi.org/10.1115/DETC2023-114414
View Paper titled, Mitigating the Effects of Source-Dependent Bias and Noise on Multi-Source Bayesian Optimization: Application to Materials Design
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Topics: Design, Noise (Sound), Optimization
Journal Articles

Data-Driven Calibration of Multifidelity Multiscale Fracture Models Via Latent Map Gaussian Process

Shiguang Deng, Carlos Mora, Diran Apelian, Ramin Bostanabad
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. January 2023, 145(1): 011705.
Paper No: MD-22-1319
https://doi.org/10.1115/1.4055951
Published Online: November 17, 2022
View Article titled, Data-Driven Calibration of Multifidelity Multiscale Fracture Models Via Latent Map Gaussian Process
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Topics: Calibration, Damage, Simulation, Fracture (Materials), Fracture (Process), Modeling
Proceedings Papers

Multi-Fidelity Reduced-Order Models for Multiscale Damage Analyses With Automatic Calibration

Shiguang Deng, Carlos Mora, Diran Apelian, Ramin Bostanabad
Proc. ASME. IDETC-CIE2022, Volume 3B: 48th Design Automation Conference (DAC), V03BT03A031, August 14–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: DETC2022-90163
https://doi.org/10.1115/DETC2022-90163
View Paper titled, Multi-Fidelity Reduced-Order Models for Multiscale Damage Analyses With Automatic Calibration
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Topics: Calibration, Damage
Proceedings Papers

Data Fusion as a Latent Space Learning Problem

Jonathan Tammer Eweis-Labolle, Nicholas Oune, Ramin Bostanabad
Proc. ASME. IDETC-CIE2022, Volume 3B: 48th Design Automation Conference (DAC), V03BT03A032, August 14–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: DETC2022-90233
https://doi.org/10.1115/DETC2022-90233
View Paper titled, Data Fusion as a Latent Space Learning Problem
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Topics: Calibration, Data fusion
Journal Articles

Data Fusion With Latent Map Gaussian Processes

Jonathan Tammer Eweis-Labolle, Nicholas Oune, Ramin Bostanabad
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. September 2022, 144(9): 091703.
Paper No: MD-21-1733
https://doi.org/10.1115/1.4054520
Published Online: June 13, 2022
View Article titled, Data Fusion With Latent Map Gaussian Processes
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Topics: Calibration, Data fusion, Modeling, Noise (Sound), Errors
Journal Articles

Evolutionary Gaussian Processes

Robert Planas, Nick Oune, Ramin Bostanabad
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. November 2021, 143(11): 111703.
Paper No: MD-20-1834
https://doi.org/10.1115/1.4050746
Published Online: May 28, 2021
View Article titled, Evolutionary Gaussian Processes
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Topics: Computer programming, Errors, Interpolation, Maximum likelihood estimation, Modeling, Noise (Sound), Numerical stability, Algorithms, Databases, Optimization
Proceedings Papers

Extrapolation With Gaussian Random Processes and Evolutionary Programming

Robert Planas, Nicholas Oune, Ramin Bostanabad
Proc. ASME. IDETC-CIE2020, Volume 11A: 46th Design Automation Conference (DAC), V11AT11A004, August 17–19, 2020
Publisher: American Society of Mechanical Engineers
Paper No: DETC2020-22381
https://doi.org/10.1115/DETC2020-22381
View Paper titled, Extrapolation With Gaussian Random Processes and Evolutionary Programming
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Topics: Computer programming, Maximum likelihood estimation, Stochastic processes
Proceedings Papers

Gaussian Process Emulation for Big Data in Data-Driven Metamaterials Design

Ramin Bostanabad, Yu-Chin Chan, Liwei Wang, Ping Zhu, Wei Chen
Proc. ASME. IDETC-CIE2019, Volume 2A: 45th Design Automation Conference, V02AT03A006, August 18–21, 2019
Publisher: American Society of Mechanical Engineers
Paper No: DETC2019-98027
https://doi.org/10.1115/DETC2019-98027
View Paper titled, Gaussian Process Emulation for Big Data in Data-Driven Metamaterials Design
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Topics: Design, Metamaterials
Journal Articles

Globally Approximate Gaussian Processes for Big Data With Application to Data-Driven Metamaterials Design

Ramin Bostanabad, Yu-Chin Chan, Liwei Wang, Ping Zhu, Wei Chen
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. November 2019, 141(11): 111402.
Paper No: MD-19-1164
https://doi.org/10.1115/1.4044257
Published Online: September 16, 2019
View Article titled, Globally Approximate Gaussian Processes for Big Data With Application to Data-Driven Metamaterials Design
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Topics: Design, Metamaterials, Modeling, Optimization, Dimensions, Databases, Shapes, Noise (Sound)
Proceedings Papers

Enhanced Gaussian Process Metamodeling and Collaborative Optimization for Vehicle Suspension Design Optimization

Siyu Tao, Kohei Shintani, Ramin Bostanabad, Yu-Chin Chan, Guang Yang, Herb Meingast, Wei Chen
Proc. ASME. IDETC-CIE2017, Volume 2B: 43rd Design Automation Conference, V02BT03A039, August 6–9, 2017
Publisher: American Society of Mechanical Engineers
Paper No: DETC2017-67976
https://doi.org/10.1115/DETC2017-67976
View Paper titled, Enhanced Gaussian Process Metamodeling and Collaborative Optimization for Vehicle Suspension Design Optimization
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Topics: Design, Optimization, Suspension systems, Modeling, Dynamic stability, Engineering systems and industry applications, Motor vehicles, Vehicle dynamics