Shoji, Yutaka / 小司優陸

Education & History

Ph.D. in Engineering, Hokkaido University, 2023
Master of Engineering, Hokkaido University, 2020
Bachelor of Engineering, Hokkaido University, 2018
JSPS Research Fellow DC2 (2021.04 – 2023.03)
“Development of simulation and control model for shallow geothermal system with arbitrary-condition ground heat exchanger”, 2021.04 – 2023.03. (KAKEN, Grant-in-Aid for JSPS Fellows)

Research Interests

Shallow Geothermal System
Building Energy Modeling
Building Environment
Dynamical Systems
Machine Learning
Data Assimilation and Uncertainty Quantification

Committees

空気調和・衛生工学会データ処理手順の標準化検討小委員会

Memberships

news

Dec 07, 2025	Invited talk at UrbanAI workshop, NeurIPS 2025!
Nov 20, 2025	Poster abstract accepted and presented at BuildSys ‘25!
Jul 18, 2025	Conference paper accepted and presented at CO-BUILD workshop, ICML 2025!

selected publications

Poster Abstract: Data Assimilation for HVAC Simulations in Koopman-Invariant Subspace using Kalman Filter

Yutaka Shoji, Sohei Arisaka, Eikichi Ono, and 1 more author

In Proceedings of the 12th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, Colorado School of Mines, Golden, CO, USA, Nov 2025

Abs DOI Bib

Real-time state estimation in nonlinear HVAC dynamics requires computationally expensive nonlinear filtering methods. We present a data assimilation framework enabling standard linear Kalman filtering for nonlinear systems through Koopman operator theory. We transform nonlinear CFD simulations into linear dynamics using extended dynamic mode decomposition with neural network lifting functions. Our experiments demonstrate successful reconstruction of temperature and velocity fields from only 18 temperature sensors, achieving temperature RMSE of 0.16 °C and velocity RMSEs of 0.035 m/s and 0.031 m/s for u- and v-components respectively, notably inferring unobserved velocity fields solely from temperature measurements.
@inproceedings{10.1145/3736425.3772109, author = {Shoji, Yutaka and Arisaka, Sohei and Ono, Eikichi and Mihara, Kuniaki}, title = {Poster Abstract: Data Assimilation for HVAC Simulations in Koopman-Invariant Subspace using Kalman Filter}, year = {2025}, month = nov, isbn = {9798400719455}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3736425.3772109}, doi = {10.1145/3736425.3772109}, booktitle = {Proceedings of the 12th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation}, pages = {306–307}, numpages = {2}, location = {Colorado School of Mines, Golden, CO, USA}, series = {BuildSys '25}, }