Mr. Fuhao Chang | Generative Artificial Intelligence | Best Researcher Award |

Mr. Fuhao Chang | Generative Artificial Intelligence | Best Researcher Award

Master’s student at China Agricultural University, Beijing, China.

Mr. Fuhao Chang is a talented and rapidly emerging researcher in the field of Generative Artificial Intelligence, with a strong academic and technical foundation in computer technology and IoT engineering. Currently pursuing his Master’s degree at China Agricultural University, he is recognized for his innovative contributions to generative modeling, multimodal AI systems, and time-series simulation. With a passion for deep learning, diffusion models, and transformer architectures, Fuhao combines academic rigor with hands-on expertise, actively contributing to both research and industry-relevant AI applications.

Professional Profile

Scopus 

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🎓 Education 

Mr. Chang is a graduate student at China Agricultural University, a top-tier “985” institution in China, where he is pursuing a Master’s degree in Computer Technology (2023–2026). He entered the program as a recommended student (保送生), reflecting his academic excellence. Prior to this, he completed his undergraduate studies at Wuhan University of Engineering, majoring in the Internet of Things Engineering. With a GPA of 3.68/4.0, he graduated as an Outstanding Graduate within the top 5% of his class.

💼 Experience 

Fuhao gained valuable industry experience during his internship at Beijing Century Good Future Education Technology Co., Ltd., where he worked on the integration of large-scale multimodal models with Stable Diffusion for geometric image editing. His contributions included vocabulary extension of LLaVA models, fine-tuning through LoRA, and the development of bi-directional interactive modules for precise alignment between image and text features. He has also been involved in the deployment of several cutting-edge models such as LLaMA2, Qwen2-VL, SAM2, and FLUX, using multi-GPU/NPU distributed training environments.

🔬 Research Interests

Mr. Chang’s research centers on generative AI, multimodal interaction, and time-series forecasting. He has worked extensively with diffusion models, transformer-based architectures, and probabilistic forecasting techniques. A major focus of his work has been on improving the decoder and loss functions of diffusion transformers to enhance temporal dynamic simulation, integrating Fourier transforms and polynomial fitting into attention mechanisms. His innovations have led to performance improvements of over 30% in uncertainty and temporal accuracy. His recent work on stochastic weather simulation for photovoltaic integration has been well-received by top journals.

Honors & Awards 

Fuhao has earned numerous accolades at both national and provincial levels. He is a certified System Architect (高级工程师) and Software Designer, and holds CET-6 English language certification (Score: 476). His awards include the National Second Prize in the 2023 China University Digital Skills Competition, the Third Prize in the 2022 Lanqiao Cup National Software Competition, and another National Second Prize in the 2021 National University Computer Skills Challenge. He also holds more than nine provincial and five university-level honors.

Top Noted Publications:

1. Crop Pest Image Recognition Based on the Improved ViT Method
Authors: X. Fu, Q. Ma, F. Yang, C. Zhang, X. Zhao, F. Chang, L. Han
Citations: 59
Index: SCI – Information Processing in Agriculture
Year: 2024

2. Simulation and Forecasting of Fishery Weather Based on Statistical Machine Learning
Authors: X. Fu, C. Zhang, F. Chang, L. Han, X. Zhao, Z. Wang, Q. Ma
Citations: 11
Index: SCI – Information Processing in Agriculture
Year: 2024

3. Stochastic Scenario Generation Methods for Uncertainty in Wind and Photovoltaic Power Outputs: A Comprehensive Review
Authors: K. Zheng, Z. Sun, Y. Song, C. Zhang, C. Zhang, F. Chang, D. Yang, X. Fu
Citations: 1
Index: SCI – Energies
Year: 2025

4. Revolutionising Agri‐Energy: A Comprehensive Survey on the Applications of Artificial Intelligence in Agricultural Energy Internet
Authors: X. Fu, W. Ye, X. Li, X. Zeng, Y. Wang, F. Chang, J. Zhang, R. Liu
Citations: 1
Index: SCI – Energy Internet
Year: 2024

5. Knowledge-Integrated GAN Model for Stochastic Time-Series Simulation of Year-Round Weather for Photovoltaic Integration Analysis
Authors: X. Fu, F. Chang, H. Sun, P. Zhang, Y. Zhang
Citations: Not yet indexed
Index: SCI – IEEE Transactions on Power Systems
Year: 2025

Conclusion:

Mr. Fuhao Chang is a standout example of a new generation of AI researchers who blend deep technical understanding with practical, impactful innovation. His strong academic background, research achievements, and commitment to advancing AI technologies make him a worthy candidate for prestigious recognitions such as the Best Researcher Award. With continued growth in global collaboration and communication, Fuhao is poised to make significant contributions to the field of AI on both national and international stages.

Assist. Prof. Dr Saeid Afshari | Artificial intelligence | Best Researcher Award |

Assist. Prof. Dr Saeid Afshari | Artificial intelligence | Best Researcher Award | 

Faculty , at University of Isfahan , Iran.

Dr. Saeid Afshari is an Assistant Professor of Computer Engineering at the University of Isfahan, Iran. With extensive expertise in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning, and Human-Computer Interaction (HCI), he has significantly contributed to both academia and industry. His research spans AI-driven solutions for healthcare, security, organizational management, and multimedia applications. An experienced IT project manager, he has successfully led the development of various smart software systems, AI-based analytics platforms, and e-Government services. Dr. Afshari is also a dedicated educator, mentoring numerous students in AI, data science, and software engineering.

Professional Profile

Scopus

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Orcid

Education 🎓

Ph.D. in Computer Engineering – Artificial Intelligence (2015) | University of Isfahan, Iran

Thesis: Online Quality of Experience Assessment System for Interactive Applications in Computer Networks

M.Sc. in Computer Engineering – Artificial Intelligence (2005) | University of Isfahan, Iran

Thesis: Using Agents in Workflow Management System of Distributed Organizations

B.Sc. in Hardware Engineering (2000) | University of Isfahan, Iran

Professional Experience 💼

Dr. Afshari has extensive experience in managing and developing AI-powered IT projects. He has led multiple organizational management software, AI-based sports and athlete management platforms, and e-Government solutions. As an educator, he has taught a range of subjects, including AI, data science, statistical pattern recognition, and programming in Python, C++, and MATLAB. His supervision of numerous master’s theses on AI applications highlights his mentorship and contribution to academic research.

Research Interests 🌍

Dr. Afshari’s research explores AI-driven problem-solving, deep learning applications, and human-computer interaction. His work includes machine learning-based image processing for medical diagnostics (cancer detection, skin tissue analysis), AI-powered workflow automation, smart organizational management, and multimedia quality assessment. He has also worked on neural network-based human activity recognition, deep learning models for license plate recognition, and machine translation systems. His interdisciplinary approach integrates AI with healthcare, business management, and security applications.

Awards & Honors 🏆

Recognized for significant contributions in AI-driven software development and project leadership

Successfully implemented over 150 AI-based software applications in academia and industry

Leading researcher in QoE (Quality of Experience) assessment for interactive applications

Top Noted Publications 📚

Load Balancing of Servers in Software-Defined Internet of Multimedia Things Using the Long Short-Term Memory Prediction Algorithm

Authors: S. Imanpour, A. Montazerolghaem, S. Afshari

Conference: 10th International Conference on Web Research (ICWR)

Citations: 7

Year: 2024

QoE Assessment of Interactive Applications in Computer Networks

Authors: S. Afshari, N. Movahhedinia

Journal: Multimedia Tools and Applications, Volume 75, Pages 903-918

Citations: 7

Year: 2016

Non-Intrusive Online Quality of Experience Assessment for Voice Communications

Authors: S. Afshari, N. Movahhedinia

Journal: Wireless Personal Communications, Volume 79, Pages 2155-2170

Citations: 3

Year: 2014

Optimizing Server Load Distribution in Multimedia IoT Environments Through LSTM-Based Predictive Algorithms

Authors: A. R. Montazerolghaem, S. Imanpour, S. Afshari

Journal: International Journal of Web Research

Year: 2025

Projecting Road Traffic Fatalities in Australia: Insights for Targeted Safety Interventions

Authors: A. Soltani, S. Afshari, M. A. Amiri

Journal: Injury

Year: 2025

Conclusion

Dr. Saeid Afshari is a strong candidate for the Best Researcher Award, particularly for his contributions to AI, machine learning, and deep learning applications. To further enhance his competitiveness, he could focus on increasing high-impact publications, international collaborations, patents, and research funding. If the award prioritizes real-world AI applications, software development, and mentorship, he would be an excellent nominee.