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
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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.