Takayuki SHUKU

Emailtshukutcu.acjp

h-index

Research activity per year

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

SDG 9 Industry, Innovation, and Infrastructure
SDG 11 Sustainable Cities and Communities
SDG 15 Life on Land

Fingerprint

Dive into the research topics where Takayuki SHUKU is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

1 Similar Profiles

18 Active

ミクロレベルの観測に基づいた新しい地盤浸透理論の構築
SHUKU, T. (CoPI), 西村伸一西村 (CoPI), 藤澤和謙藤澤 (CoPI), 豊福元 (CoPI) & 珠玖隆行珠玖 (CoPI)
日本学術振興会
27/06/25 → …
Project: Subsidies for on-campus educational facilities
データベースと高精度地盤調査の連携によるため池群のリスク評価
SHUKU, T. (CoPI), 西村伸一西村 (CoPI), 柴田俊文柴田 (CoPI), 亮治工藤 (CoPI), 満小松 (CoPI) & 珠玖隆行珠玖 (CoPI)
日本学術振興会
1/04/24 → …
Project: Subsidies for on-campus educational facilities
微小・低重力環境下における高効率保水・有機質土壌の生成と展開
SHUKU, T. (CoPI), 也寸志森 (CoPI), 守弘前田 (CoPI), 浩助登尾 (CoPI), 忠臣齊藤 (CoPI), 珠玖隆行珠玖 (CoPI) & 広昭宗村 (CoPI)
日本学術振興会
30/06/23 → …
Project: Subsidies for on-campus educational facilities
Development of three-dimensional data-driven site characterization methods and benchmark examples for the methods.
SHUKU, T. (CoPI) & 珠玖隆行珠玖 (CoPI)
日本学術振興会
1/04/23 → …
Project: Subsidies for on-campus educational facilities
集中群配置型クロスホールミューオン探査手法の開発
SHUKU, T. (CoPI), 西村伸一西村 (CoPI), 柴田俊文柴田 (CoPI) & 珠玖隆行珠玖 (CoPI)
日本学術振興会
30/06/22 → …
Project: Subsidies for on-campus educational facilities

70 Article
29 Conference contribution
18 Misc
10 Paper
More

Application of ℓ1 Trend Filtering Technique to Analyze Rock Slope Subsidence in Satellite Sensing Data
Li, C., Shuku, T., Yokota, Y. & Date, K., 2026, Advances in Rock Mechanics - Infrastructure Development, Volume 3 - Proceedings of the 13th Asian Rock Mechanics Symposium, ARMS13. Deb, D., Murthy, V. M. S. R., Venkatesh, H. S., Rao, K. S., Goel, R. K. & Singh, M. (eds.). Springer Science and Business Media Deutschland GmbH, p. 43-50 8 p. (Lecture Notes in Civil Engineering; vol. 785 LNCE).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Foreword to “Special issue on machine learning in geotechnics”
Phoon, K. K., Shuku, T. & Tang, C., Oct 2026, In: Soils and Foundations. 66, 5, 101863.
Research output: Contribution to journal › Editorial

Open Access
Towards Scientific Machine Learning for Granular Material Simulations: Challenges and Opportunities
Fransen, M., Fürst, A., Tunuguntla, D., Wilke, D. N., Alkin, B., Barreto, D., Brandstetter, J., Cabrera, M. A., Fan, X., Guo, M., Kieskamp, B., Kumar, K., Morrissey, J., Nuttall, J., Ooi, J., Orozco, L., Papanicolopulos, S. A., Qu, T., Schott, D. & Shuku, T. & 4 others, Sun, W. C., Weinhart, T., Ye, D. & Cheng, H., Jan 2026, In: Archives of Computational Methods in Engineering. 33, 1, p. 789-821 33 p.
Research output: Contribution to journal › Review article › peer-review

Open Access
10 Scopus citations
A novel data-driven 3D site characterisation method: Tucker decomposition-Bayesian compressive sensing and benchmarking study
Huang, M., Shuku, T., Shibata, T. & Nishimura, S. I., 2025, In: Georisk. 19, 2, p. 247-266 20 p.
Research output: Contribution to journal › Article › peer-review
10 Scopus citations
3D Data-driven Site Characterization using Geotechnical Lasso with Basis Functions
Phoon, K. K. & Shuku, T., 2024, Proceedings of the 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022. Beer, M., Zio, E., Phoon, K.-K. & Ayyub, B. M. (eds.). Research Publishing, p. 406-409 4 p. (Proceedings of the 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
4 Scopus citations

2019 Editorial Board Member Award, Soils and Foundations
SHUKU, T. (Recipient), Aug 2019
Prize
Best Paper Aard: Parameter identification for Cam-clay model in partial loading model tests using the particle filter
SHUKU, T. (Recipient), Jun 2013
Prize
Best Paper Award
SHUKU, T. (Recipient), Apr 2020
Prize
Best Paper Award
SHUKU, T. (Recipient), Apr 2018
Prize
Bright Spark Lecture Award: Sparse modeling in Geotechnical Engineering
SHUKU, T. (Recipient), Dec 2019
Prize

Findings from Okayama University Provide New Insights into Information Technology (A Novel Data-driven 3d Site Characterisation Method: Tucker Decomposition-bayesian Compressive Sensing and Benchmarking Study)
SHUKU, T.
19/09/24
1 item of Media coverage
Press/Media
New Findings on Geotechnical Engineering Described by Investigators at Kyoto University (Developments of Inverse Analysis By Kalman Filters and Bayesian Methods Applied To Geotechnical Engineering)
SHUKU, T.
21/12/23
1 item of Media coverage
Press/Media
New Findings from Okayama University Describe Advances in Geotechnical Engineering (Comparison of Data-driven Site Characterization Methods Through Benchmarking: Methodological and Application Aspects)
SHUKU, T.
6/06/23
1 item of Media coverage
Press/Media
New Information Technology Findings from Okayama University Reported (Data-driven Subsurface Modelling Using a Markov Random Field Model)
SHUKU, T.
7/04/23
1 item of Media coverage
Press/Media
Research Conducted at Okayama University Has Updated Our Knowledge about Georisk Management (Risk Evaluation for Earth-fill Dams Due To Heavy Rains By Response Surface Method)
SHUKU, T.
20/02/23
1 item of Media coverage
Press/Media

Takayuki SHUKU

Personal profile

Expertise related to UN Sustainable Development Goals

Fingerprint

Collaborations and top research areas from the last five years

Dive into details

ミクロレベルの観測に基づいた新しい地盤浸透理論の構築

データベースと高精度地盤調査の連携によるため池群のリスク評価

微小・低重力環境下における高効率保水・有機質土壌の生成と展開

Development of three-dimensional data-driven site characterization methods and benchmark examples for the methods.

集中群配置型クロスホールミューオン探査手法の開発

Application of ℓ1 Trend Filtering Technique to Analyze Rock Slope Subsidence in Satellite Sensing Data

Foreword to “Special issue on machine learning in geotechnics”

Towards Scientific Machine Learning for Granular Material Simulations: Challenges and Opportunities

A novel data-driven 3D site characterisation method: Tucker decomposition-Bayesian compressive sensing and benchmarking study

3D Data-driven Site Characterization using Geotechnical Lasso with Basis Functions

2019 Editorial Board Member Award, Soils and Foundations

Best Paper Aard: Parameter identification for Cam-clay model in partial loading model tests using the particle filter

Best Paper Award

Best Paper Award

Bright Spark Lecture Award: Sparse modeling in Geotechnical Engineering

Findings from Okayama University Provide New Insights into Information Technology (A Novel Data-driven 3d Site Characterisation Method: Tucker Decomposition-bayesian Compressive Sensing and Benchmarking Study)

New Findings on Geotechnical Engineering Described by Investigators at Kyoto University (Developments of Inverse Analysis By Kalman Filters and Bayesian Methods Applied To Geotechnical Engineering)

New Findings from Okayama University Describe Advances in Geotechnical Engineering (Comparison of Data-driven Site Characterization Methods Through Benchmarking: Methodological and Application Aspects)

New Information Technology Findings from Okayama University Reported (Data-driven Subsurface Modelling Using a Markov Random Field Model)

Research Conducted at Okayama University Has Updated Our Knowledge about Georisk Management (Risk Evaluation for Earth-fill Dams Due To Heavy Rains By Response Surface Method)

Takayuki SHUKU

Personal profile

Expertise related to UN Sustainable Development Goals

Fingerprint

Collaborations and top research areas from the last five years

Projects

Research output

Prizes

Press/Media