... Taisei Saida
Taisei Saida

Taisei Saida

Ph.D Student (JSPS DC2 Researcher)

University of Tsukuba (Lab's url)

Biography

Taisei Saida is doctor’s student in University of Tsukuba. I am primarily working on surrogate models. Topics of interest will be structural reliability, structural health monitoring, and machine learning.

Interests

  • 🤖 Surrogate Modeling
  • 🖥️ Machine Learning
  • 🌉 Structural Reliability

Education

  • Ph.D. in Engineering, Current

    University of Tsukuba, Tsukuba in Japan

  • Master of Engineering, 2023

    University of Tsukuba, Tsukuba in Japan

  • Bachelor of Engineering, 2021

    University of Tsukuba, Tsukuba in Japan

Jounal Articles

All jounal articles »

System fragility analysis of highway bridge using multi-output Gaussian process regression surrogate model

Advances in Structural Engineering (Impact Factor: 2.1 in 2023)
Taisei Saida, Muhammad Rashid, Mayuko Nishio
DOI
System fragility analysis of highway bridge using multi-output Gaussian process regression surrogate model

TL-GPRSM: A python software for constructing transfer learning Gaussian process regression surrogate model with explainability

Software Impacts (Impact Factor: 2.1 in 2022)
Taisei Saida, Mayuko Nishio
PDF DOI
TL-GPRSM: A python software for constructing transfer learning Gaussian process regression surrogate model with explainability

Transfer learning Gaussian process regression surrogate model with explainability for structural reliability analysis under variation in uncertainties

Computers & Structures (Impact Factor: 5.372 in 2021; Structural Engineering at Google Scholar Metrics)
Taisei Saida, Mayuko Nishio
DOI PDF (Accepted version)
Transfer learning Gaussian process regression surrogate model with explainability for structural reliability analysis under variation in uncertainties

CNN-based segmentation frameworks for structural component and earthquake damage determinations using UAV images

Earthquake Engineering and Engineering Vibration (Impact Factor: 2.810 in 2021)
Taisei Saida, Muhammad Rashid, Yudai Nemoto, Shota Tsukamoto, Takehiko Asai, Mayuko Nishio
PDF DOI
CNN-based segmentation frameworks for structural component and earthquake damage determinations using UAV images

ARD カーネルによる非線形地震応答解析のガウス過程回帰代替モデル構築

土木学会論文集A2（応用力学）
才田 大聖, 西尾 真由子
DOI
ARD カーネルによる非線形地震応答解析のガウス過程回帰代替モデル構築

Conference Papers

All conference papers »

Gaussian process regression surrogate model for dynamic analysis to account for uncertainties in seismic loading

Reliability assessment of civil structures under seismic loads requires probabilistic evaluation considering the uncertainty of input …
Taisei Saida, Mayuko Nishio
DOI

Gaussian Process Regression Surrogate Model for Seismic Vulnerability Assessment of Highway Bridge Structure System

System fragility is required especially for the vulnerability assessment of existing bridges that configure transportation network as a …
Taisei Saida, Muhammad Rashid, Mayuko Nishio
DOI

Digital twin framework for real-time dynamic analysis visualization with detecting dynamic changes in structures properties using PINN

This study developed a framework for real-time dynamic analysis of structural members using physics-informed neural networks (PINN). …
Toko Okuda, Taisei Saida, Gen Matono, Mayuko Nishio
DOI

転移学習ガウス過程回帰サロゲートモデルによる構造性能解析の計算負荷低減

This study proposes the surrogate modeling by the Gaussian process regression with the transfer learning (TL-GPRSM). The TL-GPRSM can …
才田 大聖, 西尾 真由子

ARD カーネルによる非線形地震応答解析のガウス過程回帰代替モデル構築

Monte Carlo calculation is used in the seismic risk analysis of infrastructures that consider various parameter uncertainties; however, …
才田 大聖, 西尾 真由子

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