Yishuo Jiang

dblp:307/5437 · DBLP profile ↗
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6ranked-venue papers
2as first author
6since 2021 · last 2027
0009-0006-2779-0913ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 3 · 2 first-author · 3 since 2021Artificial intelligence and machine learning · 2 · 2 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
YearPublicationVenuePosition
2027 SMARAG: a trustworthy AI system for carbon reporting using self-decisive multi-agentic retrieval-augmented generation
Xinlai Liu, Praneet Pabolu, Yishuo Jiang, Timothy Fraser, Runying Chen, Huaizhu Oliver Gao
Expert Syst. Appl.3
2026 Digital twin-augmented spatio-temporal Bayesian nowcasting model for emissions accounting in complex urban grid systems
Yishuo Jiang, Minghui Cheng, Shijie Pan, Xinlai Liu, Ziheng Geng, H. Oliver Gao
Inf. Sci.1
2026 Digital Twin-Enabled Building Demolition Waste Trading: A Demonstrative Case
abstract
With the increasing demand for housing renovation and demolition, the amount of building demolition waste is rising year by year. However, due to the low recycling and reusing rate, a large proportion of waste is disposed of by landfill, which has a great impact on the environment. In addition, compared with other industries, the level of digitalization and intelligence in the construction industry is still relatively low. Facing these problems, this paper aims to explore a market-oriented circulation channel for building demolition waste and to achieve it from a technical perspective. Firstly, a digital twin-enabled building demolition waste trading workflow is proposed. The digital twin model could integrate, analyze, and display demolition-related data in real time, which is the basis of building demolition waste trading. Through the two-way information sharing mechanism, contractors and recyclers could quickly get in touch and know each other’s products and needs. Secondly, an innovative building demolition waste trading platform has been developed utilizing cutting-edge technologies, including robotics, big data, IoT, and 3D printing. Furthermore, to cater to the diverse needs of various stakeholders, a dedicated management platform for logistics providers and a comprehensive monitoring platform for the government are developed.
Shuaiming Su, Yishuo Jiang, Ray Y. Zhong
IEEE Trans Autom. Sci. Eng.3
2024 The marriage of operations research and reinforcement learning: Integration of NEH into Q-learning algorithm for the permutation flowshop scheduling problem
Daqiang Guo, Sichao Liu, Shiquan Ling, Mingxing Li 0002, Yishuo Jiang, Ming Li 0055, George Q. Huang
Expert Syst. Appl.5
2023 Multi-domain ubiquitous digital twin model for information management of complex infrastructure systems
Yishuo Jiang, Ming Li 0055, Wei Wu 0041, Xiqiang Wu, Ray Y. Zhong, George Q. Huang
Adv. Eng. Informatics1
2023 Digital twin and its potential applications in construction industry: State-of-art review and a conceptual framework
Shuaiming Su, Ray Y. Zhong, Yishuo Jiang, Jidong Song, Hongrui Cao
Adv. Eng. Informatics3