Meet the authors: Zixin Jiang and Bing Dong
What can we do to mitigate climate change and achieve carbon neutrality for buildings? In their recent publication in <i>Patterns</i>, the authors proposed a modularized neural network incorporating physical priors for future building energy modeling, paving the way for scalable and reliable building energy modeling, optimization, retrofit designs, and buildings-to-grid integration. In this interview, the authors talk about incorporating fundamental heat transfer and thermodynamics knowledge into data-driven models.
Authors
- Zixin Jiang (ORCID: https://orcid.org/0009-0002-7824-6062)
- Bing Dong (ORCID: https://orcid.org/0000-0003-1603-9738)
Institutions
- Syracuse University (US)
Publication Details
- Journal
- Patterns
- Published
- 2024-08-01
- DOI
- https://doi.org/10.1016/j.patter.2024.101044
- Primary Topic
- Building Energy and Comfort Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation