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.

💼 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 AwardIRICT 2021 for “C-SAR: Class-Specific and Adaptive Recognition for Arabic Handwritten Cheques”
  • 🏅 Nomination for Best Paper AwardICVS 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. Kailiang Lu | Numerical Simulation | Best Researcher Award

Dr. Kailiang Lu | Numerical Simulation | Best Researcher Award

Dr. Kailiang Lu, China University of Mining and Technology, China

Kailiang Lu is a dedicated Ph.D. candidate in Geological Resources and Geological Engineering at Chang’an University, where he also completed his Bachelor’s in Geophysics. Known for his academic excellence, Kailiang progressed directly from his Master’s studies to a doctoral program, reflecting his strong performance and commitment to research. His work focuses on 3D transient electromagnetic forward modeling and transient electromagnetic migration imaging, contributing valuable insights to the field of geophysics. Kailiang has received several awards, including the National Scholarship for Postgraduate Students and the Outstanding Graduate Student Scholarship at Chang’an University in 2018 and 2019.

Professional Profile:

Google Scholar
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Suitability for the Award:

Kailiang’s research directly aligns with the objectives of the Best Researcher Award, as he has demonstrated both technical innovation and a strong publication record in geophysical methods. His achievements in developing computational algorithms for transient electromagnetic data modeling position him as an influential researcher in the field of geological engineering.

Academic Background:

Kailiang Lu is a Ph.D. candidate in Geological Resources and Geological Engineering at Chang’an University, where he also completed his Bachelor’s and Master’s studies in Geophysics. Due to his exceptional academic performance, Kailiang transitioned directly to his doctoral studies, bypassing the requirement for a formal master’s degree.

Research Focus:

Kailiang’s research specializes in 3D Transient Electromagnetic Forward Methods and Transient Electromagnetic Migration Imaging, where he advances imaging and analysis techniques in geological studies.

Awards & Honors:

His academic journey is marked by multiple recognitions, including the Outstanding Graduate Student Scholarship (2018, 2019) and the prestigious National Scholarship for Postgraduate Students. These accolades underscore his dedication and achievements in geophysical research and innovation.

Publication Top Notes:

  • New multi-resolution and multi-scale electromagnetic detection methods for urban underground spaces
    • Citations: 19
    • Year: 2018
  • A precise integration transform algorithm for transformation from the transient electromagnetic diffusion field into the pseudo wave field
    • Citations: 16
    • Year: 2021
  • The application of multi-grounded source transient electromagnetic method in the detections of coal seam goafs in Gansu Province, China
    • Citations: 15
    • Year: 2021
  • Second-order Born approximation imaging algorithm for transient electromagnetic pseudo wave-field
    • Citations: 10
    • Year: 2022
  • A new method for space-based detecting small-scale space debris with high-resolution using transient electromagnetism
    • Citations: 9
    • Year: 2018

 

 

Dr. Olumuyiwa Otegbeye | Numerical Methods | Best Researcher Award

Dr. Olumuyiwa Otegbeye | Numerical Methods | Best Researcher Award

Dr. Olumuyiwa Otegbeye, University of the Witwatersrand, South Africa

Dr. Olumuyiwa Otegbeye is a dedicated academic with a rich background in applied mathematics. He earned his Ph.D. in Applied Mathematics from the University of KwaZulu-Natal, where he also completed his M.Sc. and B.Sc. Hons. degrees, and holds a B.Sc. Hons. in Pure and Applied Mathematics from Bowen University. Dr. Otegbeye has served as a Lecturer at the University of the Witwatersrand, Johannesburg, and held postdoctoral and teaching positions at the University of KwaZulu-Natal. His early career included teaching mathematics at Nigeria Defence Academy Primary School. He boasts an H-Index of 7 on Google Scholar, 6 on Scopus, and 4 on Web of Science, reflecting his significant scholarly impact. Additionally, Dr. Otegbeye contributes as a reviewer for prominent journals such as Mathematics (MDPI), Axioms, International Journal of Modern Physics B, and Mathematics and Computers in Simulation.

🌍 Professional Profile

Orcid
Scopus
Google Schalor

Suitability for Best Researcher Award:

Dr. Olumuyiwa Otegbeye is a strong candidate for the Best Researcher Award due to his comprehensive achievements in applied mathematics, evidenced by his research impact, teaching roles, and contributions to postgraduate supervision. His active participation in academic communities and his notable bibliometric performance further affirm his qualifications for this recognition.

🎓 Academic Qualifications:

Dr. Otegbeye earned his Ph.D. in Applied Mathematics from the University of KwaZulu-Natal, following an M.Sc. and B.Sc. Hons. in Applied Mathematics from the same institution. He also holds a B.Sc. Hons. in Pure and Applied Mathematics from Bowen University.

🌍 Ratings and Citations:

His scholarly impact is notable, with an H-Index of 7 on Google Scholar, 6 on Scopus, and 4 on Web of Science, along with significant citations across these platforms.

📈 Reviewer Experience:

Dr. Otegbeye reviews for prominent journals including Mathematics (MDPI Publishing House), Axioms, International Journal of Modern Physics B, and Mathematics and Computers in Simulation.

📚 Current and Previous Positions:

Dr. Olumuyiwa Otegbeye has held several academic roles, including Lecturer at the University of the Witwatersrand, Johannesburg, from January 2021 to March 2024. Prior to this, he was a Postdoctoral Fellow at the University of KwaZulu-Natal (May 2019 – December 2020) and served as an Adhoc Mathematics Lecturer and Demonstrator/Tutor at the same institution. He began his academic career as a Mathematics Teacher at Nigeria Defence Academy Primary School.

Publication Top Notes:

  • Title: Magnetohydrodynamic Bio-Convective Casson Nanofluid Flow: A Numerical Simulation by Paired Quasilinearisation
    • Cited by: 33
    • Year: 2020
  • Title: A Machine Learning Solution Framework for Combatting COVID-19 in Smart Cities from Multiple Dimensions
    • Cited by: 32
    • Year: 2020
  • Title: A Novel Smart City-Based Framework on Perspectives for Application of Machine Learning in Combating COVID-19
    • Cited by: 29
    • Year: 2021
  • Title: A Paired Quasi-Linearization on Magnetohydrodynamic Flow and Heat Transfer of Casson Nanofluid with Hall Effects
    • Cited by: 20
    • Year: 2019
  • Title: Wind Energy Resource Assessment in South Western of Algeria
    • Cited by: 19
    • Year: 2019