Jidan Huang | Artificial Intelligence | Innovative Research Award

Innovative Research Award

Jidan Huang

Donghua University, China

Jidan Huang
Affiliation Donghua University
Country China
Scopus ID 57193425191
Documents 10
Citations 36
h-index 4
Subject Area Artificial Intelligence
Event Research Awards and Recognitions
ORCID 0000-0003-2547-0212

Jidan Huang is a Chinese academic affiliated with Donghua University whose research combines artificial intelligence, tourism decision-making, logistics management, and multi-objective fuzzy evaluation. His scholarly activities focus on sustainability assessment, intelligent decision-support systems, and advanced multi-criteria evaluation methodologies applied across tourism, management, and operations research disciplines.[1]

Abstract

This article presents a concise academic overview of Jidan Huang, Associate Professor and Senior Experimentalist at Donghua University. His work spans artificial intelligence, tourism management, logistics decision-making, sustainability evaluation, and fuzzy multi-criteria analysis, emphasizing quantitative frameworks that support evidence-based planning and intelligent decision processes across interdisciplinary research environments.[1]

Keywords

Artificial Intelligence; Tourism Management; Multi-Criteria Decision-Making; Fuzzy TOPSIS; Sustainability Assessment; Green Logistics; Decision Support Systems; Cultural Heritage Tourism; Evaluation Systems; Operations Management.

Introduction

Jidan Huang earned a Bachelor of Engineering from Shanghai Maritime University, followed by a Master of Science in Mathematics and a Doctor of Philosophy in Management Science and Engineering from Donghua University. His interdisciplinary educational background supports research integrating mathematics, management science, artificial intelligence, and applied decision analytics.[2]

Research Profile

As Associate Professor at the Glorious Sun School of Business and Management, Donghua University, Huang supervises graduate students and conducts research in tourism decision-making, logistics optimization, artificial intelligence applications, and multi-objective fuzzy evaluation. He also serves as a peer reviewer for several systems science and operations research journals.[2]

Research Contributions

  • Development of three-interval TOPSIS and fuzzy evaluation methodologies.
  • Research on sustainable tourism assessment and optimization strategies.
  • Green logistics evaluation supporting carbon peaking and carbon neutrality goals.
  • Application of artificial intelligence and neural networks in recognition systems.
  • Multi-criteria decision-making frameworks for regional and industrial evaluation.

Publications

Jidan Huang’s publication record includes research on sustainability evaluation, tourism optimization, green logistics, fuzzy decision-making, and artificial intelligence. Representative studies demonstrate the application of TOPSIS, Delphi methods, fuzzy AHP, and convolutional neural networks to address complex evaluation and recognition problems across multiple sectors.[3][4][5][6]

  1. Integrating Life Cycle Assessment and TOPSIS for Product-Level Sustainability Evaluation of Automotive Vehicles.
  2. Evaluation and Development Path Optimization of Rural Low-Altitude Tourism Using a Triangular Fuzzy TOPSIS Approach.
  3. A Model Based on Delphi and Three-Interval TOPSIS: Sustainable Evaluation of Green Logistics Under the Goals of Carbon Peaking and Carbon Neutrality.
  4. Assessing the Sustainable Development of the Tourism Industry Based on Fuzzy AHP and Grey Relational TOPSIS.
  5. Recognition Method for Stone Carved Calligraphy Characters Based on a Convolutional Neural Network.

Research Impact

According to available author metrics, Jidan Huang has produced 10 indexed publications, accumulated 36 citations, and achieved an h-index of 4. His studies contribute to sustainability evaluation, intelligent decision-making, tourism development analysis, and logistics optimization through rigorous quantitative methodologies.[1]

Award Suitability

Jidan Huang’s combination of interdisciplinary research, scholarly publication, postgraduate supervision, and educational achievements supports recognition within research award programs. His contributions to artificial intelligence applications, sustainability assessment, and decision-support methodologies demonstrate continued engagement with contemporary academic and societal challenges.[2]

Conclusion

Jidan Huang maintains an active academic profile centered on artificial intelligence, tourism management, logistics decision-making, and fuzzy evaluation systems. His research outputs, teaching achievements, and methodological contributions highlight a sustained commitment to interdisciplinary scholarship and practical decision-support research.[1]

References

  1. Elsevier. (n.d.). Scopus Author Details: Jidan Huang, Author ID 57193425191. Scopus Author Profile. https://www.scopus.com/authid/detail.uri?authorId=57193425191
  2. Zheng, M., Chen, H., & Huang, J. (2026). Integrating Life Cycle Assessment and TOPSIS for Product-Level Sustainability Evaluation of Automotive Vehicles. Sustainability. DOI: https://doi.org/10.3390/su18115615
  3. Huang, J., Chen, Y., & Pan, W. (2026). Evaluation and Development Path Optimization of Rural Low-Altitude Tourism Using a Triangular Fuzzy TOPSIS Approach. Sustainability. DOI: https://doi.org/10.3390/su18115534
  4. Li, R., Huang, J., Dai, T., & Yang, Q. (2026). A Model Based on Delphi and Three-Interval TOPSIS: Sustainable Evaluation of Green Logistics Under the Goals of Carbon Peaking and Carbon Neutrality. Sustainability. DOI: https://doi.org/10.3390/su18041920
  5. Yang, Q., Huang, J., & Pan, W. (2026). Assessing the Sustainable Development of the Tourism Industry Based on Fuzzy AHP and Grey Relational TOPSIS. Sustainability. DOI: https://doi.org/10.3390/su17219799
  6. Huang, J., Cheng, G., Zhang, J., & Miao, W. (2022). Recognition Method for Stone Carved Calligraphy Characters Based on a Convolutional Neural Network. Neural Computing and Applications. https://link.springer.com/article/10.1007/s00521-022-08049-9

Wai Kin Victor Chan | Artificial Intelligence | Best Researcher Award

Prof. Wai Kin Victor Chan | Artificial Intelligence | Best Researcher Award

Prof. Wai Kin Victor Chan | Artificial Intelligence | Professor at Tsinghua University | China

Prof. Wai Kin Victor Chan is a distinguished academic and researcher at Tsinghua University’s Tsinghua-Berkeley Shenzhen Institute, widely recognized for his expertise in agent-based simulation, discrete-event systems, intelligent transportation networks, and sustainable energy applications. Over his career, he has made significant strides in computational modeling, deep learning frameworks, blockchain systems, and manufacturing optimization, earning more than 2,600 citations across his research portfolio. His work addresses pressing technological challenges by bridging simulation science, artificial intelligence, and smart city innovation, establishing him as a thought leader and collaborator in advancing next-generation technologies for global benefit.

Academic Profile

ORCID

Google Scholar

Education

Prof. Chan earned his Ph.D. in Systems Engineering, focusing on discrete-event simulation modeling and optimization techniques for complex industrial systems. His doctoral research, supported by international collaborations, laid the foundation for his future breakthroughs in multi-cluster scheduling, simulation-based energy analysis, and AI-driven forecasting frameworks. Building upon his early academic achievements, his continuous learning through postdoctoral engagements and research residencies allowed him to refine expertise in transportation systems modeling, sustainable manufacturing, and decentralized technologies.

Experience

Prof. Chan has built an extensive research career through faculty roles, international research collaborations, and industry-linked projects that merge academic rigor with real-world impact. At Tsinghua University, he leads interdisciplinary initiatives connecting simulation, artificial intelligence, and smart infrastructure, partnering with global institutions to develop computational frameworks for blockchain energy modeling, emergency transportation planning, and AI-powered traffic systems. His experience spans conference leadership, workshop facilitation, and mentoring graduate researchers, while his advisory roles for industrial partners have enabled the application of his models to enhance supply chains, urban planning, and energy-efficient manufacturing systems.

Research Interest

Prof. Chan’s research interests are anchored in agent-based and discrete-event simulations, Monte Carlo computational techniques, AI-enabled traffic prediction, blockchain-driven sustainability, and system optimization for smart cities and industrial processes. He is particularly focused on developing hybrid modeling approaches that combine simulation and artificial intelligence to manage complex, dynamic systems. His contributions to the study of emergent behavior modeling, electricity market simulations, and multi-cluster scheduling have influenced the design of scalable frameworks for both academic research and applied engineering solutions worldwide.

Award

Prof. Chan’s exceptional academic trajectory, marked by his citation index of 2,634, h-index 24, and i10-index 49, positions him as a strong nominee for the Best Researcher Award. His contributions have advanced transportation system resilience, sustainable blockchain adoption, and AI-driven optimization techniques, earning recognition within academic and professional networks such as IEEE and ACM. His role as a collaborative leader in international research projects exemplifies the kind of global impact celebrated by this award category.

Publications

  • “Cost modeling and optimization of a manufacturing system for mycelium-based biocomposite parts”
    Published year: 2016 | Citations: 77

  • “Agent-Based Simulation Tutorial: Simulation of Emergent Behavior”
    Published year: 2010 | Citations: 240

  • “Optimal Scheduling of Multicluster Tools Part I”
    Published year: 2010 | Citations: 154

  • “Spatial-Temporal Attention Wavenet for Traffic Prediction”
    Published year: 2021 | Citations: 117

  • “Evaluation of Energy Consumption in Blockchains”
    Published year: 2020 | Citations: 109

  • “Monte Carlo Simulations Applied to Uncertainty in Measurement”
    Published year: 2013 | Citations: 125

  • “Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization”
    Published year: 2023 | Citations: 107

Conclusion

Prof. Wai Kin Victor Chan’s research career embodies the qualities celebrated by the Best Researcher Award, blending theoretical innovation, high-impact publications, and interdisciplinary leadership. His pioneering studies in agent-based systems, AI-driven simulations, and sustainable technologies not only advance the state of knowledge but also provide solutions for urban resilience, energy efficiency, and digital innovation. With a strong publication record, global collaborations, and a vision for expanding AI-integrated sustainability and smart infrastructure frameworks, he continues to shape the future of computational science, making him a deserving recipient of this recognition.