Ramin Bostanabad

Ramin Bostanabad

University of California, Irvine

H-index: 18

North America-United States

About Ramin Bostanabad

Ramin Bostanabad, With an exceptional h-index of 18 and a recent h-index of 18 (since 2020), a distinguished researcher at University of California, Irvine, specializes in the field of Design under uncertainty, Uncertainty quantification, Optimization, Materials Informatics, Scientific Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

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

Corrigendum to “Multi-Fidelity Cost-Aware Bayesian Optimization”[Computer Methods in Applied Mechanics and Engineering 407 (2023) 115937]

Data-driven physics-constrained recurrent neural networks for multiscale damage modeling of metallic alloys with process-induced porosity

Parametric Encoding with Attention and Convolution Mitigate Spectral Bias of Neural Partial Differential Equation Solvers

Multi-Fidelity Design of Porous Microstructures for Thermofluidic Applications

Neural Networks with Kernel-Weighted Corrective Residuals for Solving Partial Differential Equations

On the Effects of Heterogeneous Errors on Multi-fidelity Bayesian Optimization

Unsupervised anomaly detection via nonlinear manifold learning

Ramin Bostanabad Information

University

Position

Assistant Professor

Citations(all)

2223

Citations(since 2020)

2069

Cited By

747

hIndex(all)

18

hIndex(since 2020)

18

i10Index(all)

25

i10Index(since 2020)

25

Email

University Profile Page

University of California, Irvine

Google Scholar

View Google Scholar Profile

Ramin Bostanabad Skills & Research Interests

Design under uncertainty

Uncertainty quantification

Optimization

Materials Informatics

Scientific Machine Learning

Top articles of Ramin Bostanabad

Title

Journal

Author(s)

Publication Date

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

Journal of Mechanical Design

Zahra Zanjani Foumani

Amin Yousefpour

Mehdi Shishehbor

Ramin Bostanabad

2024/6/1

Corrigendum to “Multi-Fidelity Cost-Aware Bayesian Optimization”[Computer Methods in Applied Mechanics and Engineering 407 (2023) 115937]

Computer Methods in Applied Mechanics and Engineering

Zahra Zanjani Foumani

Mehdi Shishehbor

Amin Yousefpour

Ramin Bostanabad

2024/3/15

Data-driven physics-constrained recurrent neural networks for multiscale damage modeling of metallic alloys with process-induced porosity

Computational Mechanics

Shiguang Deng

Shirin Hosseinmardi

Libo Wang

Diran Apelian

Ramin Bostanabad

2024/1/11

Parametric Encoding with Attention and Convolution Mitigate Spectral Bias of Neural Partial Differential Equation Solvers

arXiv preprint arXiv:2403.15652

Mehdi Shishehbor

Shirin Hosseinmardi

Ramin Bostanabad

2024/3/22

Multi-Fidelity Design of Porous Microstructures for Thermofluidic Applications

Journal of Mechanical Design

Chuanning Zhao

Yoonjin Won

Ramin Bostanabad

2024/10

Neural Networks with Kernel-Weighted Corrective Residuals for Solving Partial Differential Equations

arXiv preprint arXiv:2401.03492

Carlos Mora

Amin Yousefpour

Shirin Hosseinmardi

Ramin Bostanabad

2024/1/7

On the Effects of Heterogeneous Errors on Multi-fidelity Bayesian Optimization

arXiv preprint arXiv:2309.02771

Zahra Zanjani Foumani

Amin Yousefpour

Mehdi Shishehbor

Ramin Bostanabad

2023/9/6

Unsupervised anomaly detection via nonlinear manifold learning

Journal of Computing and Information Science in Engineering

Amin Yousefpour

Mehdi Shishehbor

Zahra Zanjani Foumani

Ramin Bostanabad

2023/10/4

Adaptive spatiotemporal dimension reduction in concurrent multiscale damage analysis

Computational Mechanics

Shiguang Deng

Diran Apelian

Ramin Bostanabad

2023/7

GP+: A Python Library for Kernel-based learning via Gaussian Processes

arXiv preprint arXiv:2312.07694

Amin Yousefpour

Zahra Zanjani Foumani

Mehdi Shishehbor

Carlos Mora

Ramin Bostanabad

2023/12/12

Multi-fidelity cost-aware Bayesian optimization

Computer Methods in Applied Mechanics and Engineering

Zahra Zanjani Foumani

Mehdi Shishehbor

Amin Yousefpour

Ramin Bostanabad

2023/3/15

Probabilistic neural data fusion for learning from an arbitrary number of multi-fidelity data sets

Computer Methods in Applied Mechanics and Engineering

Carlos Mora

Jonathan Tammer Eweis-Labolle

Tyler Johnson

Likith Gadde

Ramin Bostanabad

2023/10/1

Systems and Methods for Smart Boiling Control

2023/11/23

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

2023/8/20

Breaking Boundaries: Distributed Domain Decomposition with Scalable Physics-Informed Neural PDE Solvers

Arthur Feeney

Zitong Li

Ramin Bostanabad

Aparna Chandramowlishwaran

2023/11/12

Data-driven calibration of multifidelity multiscale fracture models via latent map gaussian process

Journal of Mechanical Design

Shiguang Deng

Carlos Mora

Diran Apelian

Ramin Bostanabad

2023/1/1

Data Fusion as a Latent Space Learning Problem

Jonathan Tammer Eweis-Labolle

Nicholas Oune

Ramin Bostanabad

2022/8/14

Mosaic flows: A transferable deep learning framework for solving PDEs on unseen domains

Computer Methods in Applied Mechanics and Engineering

Hengjie Wang

Robert Planas

Aparna Chandramowlishwaran

Ramin Bostanabad

2022/2/1

Reduced-order multiscale modeling of plastic deformations in 3D alloys with spatially varying porosity by deflated clustering analysis

Computational Mechanics

Shiguang Deng

Carl Soderhjelm

Diran Apelian

Ramin Bostanabad

2022/9

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

Shiguang Deng

Carlos Mora

Diran Apelian

Ramin Bostanabad

2022/8/14

See List of Professors in Ramin Bostanabad University(University of California, Irvine)

Co-Authors

H-index: 83
Wei Chen

Wei Chen

Northwestern University

H-index: 36
Daniel Apley

Daniel Apley

Northwestern University

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