Prof. Khaled Shaban | Data Science | Best Researcher Award

Prof. Khaled Shaban | Data Science | Best Researcher Award

Prof. Khaled Shaban, Qatar University, Qatar

Prof. Khaled Shaban is a distinguished researcher and professor in Computer Science and Engineering at Qatar University. With expertise in Computational Intelligence, Machine Learning, and Data Science, he has significantly contributed to advancing pattern recognition, cloud computing, and cybersecurity. A senior member of IEEE and ACM, he has received multiple accolades for his groundbreaking research. He also holds an adjunct professorship at the University of Waterloo, reinforcing his global academic influence. His work focuses on AI-driven disease prediction, smart systems, and optimization techniques, making him a leader in intelligent computing innovations.

🌍 Professional Profile:

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🏆 Suitability for Best Researcher Award

Prof. Khaled Shaban’s research excellence, innovative contributions, and global recognition make him an ideal candidate for the Best Researcher Award. His pioneering work in Machine Learning, AI, and Computational Intelligence has led to influential publications and prestigious awards, such as the Best Paper Award at IRICT 2021. His ability to merge theory and application in AI, cloud computing, and cybersecurity has significantly impacted academia and industry. His leadership in top-tier conferences and IEEE/ACM communities underscores his commitment to advancing knowledge, making him a highly deserving candidate for this distinguished recognition.

🎓 Education

Prof. Khaled Shaban holds a Ph.D. in Electrical and Computer Engineering from the University of Waterloo, Canada (2006), specializing in Pattern Recognition and Machine Intelligence. His academic journey began with an M.Sc. in Engineering Systems and Computing (2002) from the University of Guelph, Canada, where he developed a strong foundation in computational intelligence and optimization. His interdisciplinary education has enabled him to integrate machine learning, data science, and engineering systems into cutting-edge research. His expertise in algorithms and computing theory has positioned him as a global leader in AI and intelligent systems research.

đź’Ľ Experience

Prof. Khaled Shaban has an extensive academic career, currently serving as a Professor at Qatar University’s College of Engineering (since April 2021). He previously held roles as Associate Professor (2016-2021) and Assistant Professor (2008-2016). Additionally, he is an Adjunct Professor at the University of Waterloo (2021-2027), collaborating on AI-driven computing innovations. His professional affiliations with IEEE, ACM, and international research communities enhance his impact on global technological advancements. Over the years, he has mentored numerous students and led transformative research in Artificial Intelligence, Data Science, and Optimization.

🏅 Awards & Honors

  • 🏆 Best Paper Award – IRICT 2021 for “C-SAR: Class-Specific and Adaptive Recognition for Arabic Handwritten Cheques”
  • 🏅 Nomination for Best Paper Award – ICVS 2021 for “MARL: Multimodal Attentional Representation Learning for Disease Prediction”
  • 🎖 Promoted to Professor – Qatar University, 2021
  • 🔬 Senior Member, IEEE & ACM – Recognized for contributions to AI and Computational Intelligence
  • 🌍 International Collaborations – Adjunct Professor at the University of Waterloo, fostering global research partnerships

🔬 Research Focus

Prof. Khaled Shaban’s research lies at the intersection of Artificial Intelligence, Computational Intelligence, and Data Science. His work in Machine Learning-driven healthcare analytics, particularly in disease prediction and medical image analysis, is widely recognized. He has also made significant contributions to cybersecurity, cloud computing, and smart grid systems. His studies on optimization and knowledge discovery enhance IoT, AI-based automation, and intelligent computing solutions. Through numerous publications and projects, he has addressed real-world challenges in AI, energy-efficient computing, and adaptive learning systems, making his research impactful across academia and industry.

📖 Publication Top Notes

  • Urban Air Pollution Monitoring System with Forecasting Models

    • Year: 2016
    • Citations: 341
  • Fault Detection, Isolation, and Service Restoration in Distribution Systems: State-of-the-Art and Future Trends

    • Year: 2016
    • Citations: 321
  • Delay-Aware Scheduling and Resource Optimization with Network Function Virtualization

    • Year: 2016
    • Citations: 266
  • A Reliability-Aware Network Service Chain Provisioning with Delay Guarantees in NFV-Enabled Enterprise Datacenter Networks

    • Year: 2017
    • Citations: 224
  • Deep Learning Models for Sentiment Analysis in Arabic

    • Year: 2015
    • Citations: 150

 

 

Dr. Seyed Reza Nabavi | Neural Networking Awards | Best Researcher Award

Dr. Seyed Reza Nabavi | Neural Networking Awards | Best Researcher Award

Dr. Seyed Reza Nabavi, University of Mazandaran, Iran

Dr. Seyed Reza Nabavi is a distinguished scholar with a Ph.D. in Applied Chemistry from the University of Tabriz, where his research focused on hybrid modeling and artificial intelligence in chemical processes. He further advanced his expertise as a visiting scholar at the National University of Singapore. Dr. Nabavi’s research encompasses nanotechnology, catalytic processes, reaction engineering, and the use of machine learning and evolutionary algorithms for optimizing chemical processes. Known for his work on pyrolysis and coke formation, he has been recognized for academic excellence since his undergraduate studies and has a robust teaching record at the University of Mazandaran, where he imparts knowledge in advanced chemical engineering topics.

Professional Profile:

Orcid
Scopus
Google Scholar

Suitability for the Award

Dr. Seyed Reza Nabavi is a strong candidate for the Best Researcher Award due to the following reasons:

  1. Innovative Research:
    • Dr. Nabavi’s research encompasses advanced topics in nanotechnology, catalytic processes, and chemical process optimization using modern computational techniques. His work in hybrid modeling and artificial intelligence reflects a forward-thinking approach in applied chemistry.
  2. Teaching Contributions:
    • Dr. Nabavi’s extensive teaching experience in a range of advanced chemical engineering and chemistry courses demonstrates his commitment to education and his ability to contribute to the development of future professionals in his field.
  3. Impactful Publications:
    • His contributions to books and high-impact journal articles showcase his research’s influence and relevance in the field. The focus on multi-criteria decision-making and optimization techniques aligns well with current industry and academic needs.

Summary of Qualifications

Educational Background:

Dr. Seyed Reza Nabavi holds a Ph.D. in Applied Chemistry from the University of Tabriz (2009), with a focus on hybrid modeling and artificial intelligence in chemical processes. His academic journey is further enhanced by his experience as a visiting scholar at the National University of Singapore, where he deepened his expertise in chemical and biomolecular engineering. His educational background provides a solid foundation in both theoretical and practical aspects of applied chemistry, making him well-versed in cutting-edge research methodologies.

Research Interests:

Dr. Nabavi’s research portfolio is diverse and impactful, spanning nanotechnology of polymers, catalytic processes, reaction engineering, and the modeling and optimization of chemical processes using advanced machine learning and evolutionary algorithms. His work on pyrolysis, thermal cracking, and coke formation showcases his expertise in high-impact areas within chemical engineering and applied chemistry.

Awards and Recognition:

Dr. Nabavi’s recognition includes a first-rank position among graduate students during his B.Sc., demonstrating his long-standing commitment to excellence in his academic career. Although his list of formal awards might not be extensive, his consistent output of high-quality research and his ongoing contributions to advanced chemical engineering and applied chemistry mark him as a significant figure in his field.

Teaching Experience:

Dr. Nabavi has extensive teaching experience at the University of Mazandaran, where he has taught various graduate-level courses in chemical engineering. His courses cover crucial aspects of chemical processes, including modeling, simulation, process control, and experimental design, indicating his deep involvement in both research and education.

Publications and Contributions:

Dr. Nabavi has contributed significantly to the academic community through his publications, including a book and multiple chapters in prominent books published by Springer and Wiley. His recent work on multi-criteria decision-making methods, published in Industrial & Engineering Chemistry Research (2023), highlights his ongoing contributions to the field, particularly in optimization and decision-making processes.

Conclusion:

Dr. Seyed Reza Nabavi’s robust educational background, significant research contributions, and commitment to teaching and advancing chemical engineering make him a strong candidate for the Research for Best Researcher Award. His work aligns with the award’s objectives, particularly his innovative approaches in chemical process optimization and nanotechnology. While his formal awards are limited, his academic and research achievements, particularly his contributions to applied chemistry and chemical engineering, suggest that he is well-suited for recognition through this prestigious award.