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

Google Scholar

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.

Mr Ernesto Diaz | Data Scientist | Best Researcher Award

Assistant Specialist at University of California, San Francisco – Radiology & Biomedical Imaging , United States.

Ernesto Diaz is an accomplished researcher and data scientist specializing in biomedical imaging and artificial intelligence applications in healthcare. With a strong background in medical imaging, deep learning, and data science, he has contributed significantly to Hyperpolarized Carbon-13 MRI research, cancer imaging, and radiation oncology. His work has been recognized through prestigious NIH awards, peer-reviewed publications, and multiple conference presentations. Passionate about advancing healthcare technology, Ernesto combines technical expertise with a commitment to mentorship and diversity in STEM.

Education 🎓

Ernesto earned his Bachelor of Science in Computer Science from San Francisco State University in 2022, graduating with Dean’s List honors (2020-2022). His education provided a strong foundation in programming, data analysis, and computational research, which he has applied extensively in biomedical imaging and artificial intelligence projects.

Professional Experience 💼

As a Data Scientist at UCSF’s Department of Radiology and Biomedical Imaging, Ernesto leads software development for medical imaging analysis, enhancing data processing and visualization tools. His previous research experience includes working on automated radiation treatment planning and bioinformatics coding for population health studies. His contributions have improved efficiency in clinical workflows and advanced AI applications in medical imaging.

Research Interests 🌍

His research revolves around Hyperpolarized Carbon-13 MRI, deep learning for medical image segmentation, and automation in radiation oncology. At UCSF, he developed a DICOM standardization tool for metabolic imaging and co-developed a U-Net deep learning model for prostate cancer segmentation. Additionally, he has explored health disparities in underserved communities, analyzing COVID-19’s impact on marginalized populations.

Awards & Honors 🏆

NIH Diversity Supplement Award (2022-2024) – Recognized for contributions to Hyperpolarized 13C MRI research.

NIH-SF BUILD Scholar (2021-2022) – Selected for leadership potential and commitment to diversity in research.

Dean’s List (2020-2022) – Awarded for academic excellence at San Francisco State University.

Top Noted Publications 📚

Title: Deep Learning-Based Tumor Segmentation of Murine Magnetic Resonance Images of Prostate Cancer Patient-Derived Xenografts

Authors: Satvik Nayak, Henry Salkever, Ernesto Diaz, Avantika Sinha, Nikhil Deveshwar, Madeline Hess, Matthew Gibbons, Sule Sahin, Abhejit Rajagopal, Peder E. Z. Larson, et al.

Journal: Tomography

Publication Year: 2025

DOI: 10.3390/tomography11030021

Indexing: Indexed in major scientific databases.

Conclusion

Ernesto Diaz is a rising leader in medical imaging research, blending AI, data science, and biomedical imaging to drive innovation. With his technical skills, research excellence, and dedication to mentorship, he continues to push the boundaries of healthcare technology and scientific discovery. 🚀