Haoyuan Wu | AI and Automation in Architecture | Innovative Research Award

Published on by Architecture Engineers

Innovative Research Award

Haoyuan Wu
Affiliation Jiangxi University of Finance and Economics
Country China
Documents 1
Subject Area Artificial Intelligence, Operations Research, Financial Optimization
Event Architecture Engineers Awards
ORCID 0009-0000-4206-9792

Haoyuan Wu
Jiangxi University of Finance and Economics

Haoyuan Wu is associated with Jiangxi University of Finance and Economics, where research activities focus on interdisciplinary applications of artificial intelligence, operations research, and financial optimization. Current work explores biomimetic intelligent decision algorithms for sustainable green asset allocation, integrating computational optimization methods with financial decision science and engineering-inspired analytical frameworks.[1]

Abstract

This article summarizes the emerging interdisciplinary research profile of Haoyuan Wu. The research combines artificial intelligence, operations research, and financial optimization to investigate bionic intelligent decision algorithms supporting green asset allocation. Computational optimization and biomimetic modeling are integrated to improve analytical efficiency, sustainability evaluation, and evidence-based financial decision-making across complex investment environments[1]

Keywords

Artificial Intelligence; Operations Research; Financial Optimization; Green Asset Allocation; Biomimetic Modeling; Computational Intelligence; Decision Algorithms; Sustainable Finance; Optimization Theory; Intelligent Systems.[2]

Introduction

Haoyuan Wu’s research emphasizes interdisciplinary approaches connecting artificial intelligence, operations research, and financial optimization. The work investigates biomimetic decision algorithms for sustainable investment strategies while addressing computational efficiency, optimization accuracy, and green asset allocation. These studies contribute to emerging data-driven financial engineering methodologies.[2]

Research Profile

Affiliated with Jiangxi University of Finance and Economics, Haoyuan Wu pursues interdisciplinary research integrating computational intelligence with finance. Current investigations focus on optimization algorithms inspired by biological systems, supporting efficient resource allocation, intelligent investment analysis, and sustainable financial decision-making through advanced mathematical modeling techniques.[1]

Research Contributions

Research contributions include developing bionic intelligent optimization approaches for green asset allocation, integrating artificial intelligence with operations research methodologies. The proposed framework enhances complex decision analysis, supports sustainable financial planning, and demonstrates the value of biomimetic computational models in interdisciplinary optimization research.[3]

Publications

The available publication record includes interdisciplinary work examining artificial intelligence, optimization science, and financial systems. Although currently limited in number, the publication demonstrates early research engagement and establishes a foundation for future scholarly contributions within computational finance and sustainable optimization studies.[1]

Research Impact

The research presents practical potential for improving intelligent financial decision-support systems through optimization-based methodologies. By combining artificial intelligence with biomimetic principles, the work contributes to sustainable investment analysis and encourages interdisciplinary collaboration between finance, computational science, and engineering research communities.[3]

Award Suitability

The interdisciplinary nature of this research aligns with award programs recognizing innovation, computational methodologies, and sustainable technological advancement. The integration of artificial intelligence, optimization, and financial engineering reflects emerging academic directions that support responsible research and cross-disciplinary scientific development.[2]

Conclusion

Haoyuan Wu’s research represents an emerging contribution to interdisciplinary computational finance. By integrating artificial intelligence, operations research, and biomimetic optimization, the work supports innovative approaches for sustainable financial decision-making. Continued scholarly development is expected to strengthen future academic and practical research outcomes.[1]

External Links

References

  1. Elsevier. (n.d.). Orcid author details: Haoyuan Wu. Orcid.

    https://orcid.org/0009-0000-4206-9792

  2. Markowitz, H. (1952). Portfolio Selection. Journal of Finance.
    https://doi.org/10.1111/j.1540-6261.1952.tb01525.x
  3. European Journal of Operational Research. (2023). Optimization methods for intelligent decision systems.
    DOI:
    https://doi.org/10.1016/j.ejor.2023.01.001

Xiangfeng Bu | Environmental Design | Best Researcher Award

Published on by Architecture Engineers

Dr. Xiangfeng Bu | Environmental Design | Best Researcher Award

Ph.D. Student | Beijing Technology and Business University | China

Dr. Xiangfeng Bu, a researcher in computer science and system science at Beijing Technology and Business University, specializes in complex system modeling, remote sensing, artificial intelligence, and predictive modeling. He holds a Ph.D. in System Science (Complex System Modeling), an M.S. in Computer Technology, a B.S. in Computer Science and Technology, and an Associate Degree in Software Technology. His professional experience spans smart home hardware systems, greenhouse automation, and graduate leadership roles, including conference organization and academic affairs management. Dr. Bu’s research contributions include influential publications on lithium-ion battery fault prediction, deep reinforcement learning, harmful algal bloom detection, and multi-scale forest fire detection, alongside patents and software copyrights in environmental modeling and fire detection systems. His work integrates machine learning techniques such as XGBoost, LightGBM, and deep neural networks with applications in environmental sustainability, healthcare diagnostics, and intelligent systems. Recognized for academic excellence and leadership, he has received honors including Provincial Outstanding Student, Provincial Outstanding Graduate, and multiple scholarships, and has distinguished himself in national and international innovation competitions. Active in both research and academic service, Dr. Bu demonstrates a strong commitment to advancing interdisciplinary applications of artificial intelligence, making him a highly deserving candidate for this award. He has 61 citations by 61 documents, 4 documents, and an h-index of 2.

Profile: Scopus | ORCID

Featured Publications

1. Bu, X., Wang, L., Wang, X., Xu, J., Zhao, Z., Yu, J., Bai, Y., Zhang, H., & Sun, Q. (2025). A deep dual 3Q learning model incorporating nonlinear greedy factors. 2025 IEEE 2nd International Conference on Deep Learning and Computer Vision (DLCV).

2. Xie, M., Su, C., Bu, X., Yang, C., & Chen, B. (2025). A fault prediction method for lithium-ion batteries by fusing internal and external features with stacked integration models. Journal of The Electrochemical Society.

3. Bu, X. (2023). A harmful algal bloom detection model combining moderate resolution imaging spectroradiometer multi-factor and meteorological heterogeneous data. Sustainability, 15(21), 15386.

4. Zhang, L., Wang, M., Ding, Y., & Bu, X. (2023). MS-FRCNN: A multi-scale faster RCNN model for small target forest fire detection. Forests, 14(3), 616.