Fingerprint
Fingerprint is based on mining the text of the expert's scholarly documents to create an index of weighted terms, which defines the key subjects of each individual researcher.
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Collaborations and top research areas from the last five years
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Explainable, interpretable, and trustworthy AI for an intelligent digital twin: A case study on remaining useful life
Kobayashi, K. & Alam, S. B., Mar 2024, In: Engineering Applications of Artificial Intelligence. 129, 107620.Research output: Contribution to journal › Article › peer-review
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Deep neural operator-driven real-time inference to enable digital twin solutions for nuclear energy systems
Kobayashi, K. & Alam, S. B., Jan 24 2024, In: Scientific reports. 14, 1, 2101.Research output: Contribution to journal › Article › peer-review
Open Access -
Improved generalization with deep neural operators for engineering systems: Path towards digital twin
Kobayashi, K. & Alam, S. B., May 2024, In: Engineering Applications of Artificial Intelligence. 131, 107844.Research output: Contribution to journal › Article › peer-review
Open Access -
Multi-criteria decision making under uncertainties in composite materials selection and design
Kumar, D., Marchi, M., Alam, S. B., Kavka, C., Koutsawa, Y., Rauchs, G. & Belouettar, S., Jan 1 2022, In: Composite Structures. 279, 114680.Research output: Contribution to journal › Article › peer-review
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Quantitative risk assessment of a high power density small modular reactor (SMR) core using uncertainty and sensitivity analyses
Kumar, D., Alam, S., Ridwan, T. & Goodwin, C. S., Jul 15 2021, In: Energy. 227, 120400.Research output: Contribution to journal › Article › peer-review