Mohd Khaled Shambour | Computational Science | Research Excellence Award

Prof. Mohd Khaled Shambour | Computational Science | Research Excellence Award

Middle East University | Jordan

Mohd-Khaled Yousef Shambour is a Jordanian professor specializing in Intelligent System Techniques, optimization, and artificial intelligence. He holds a PhD in Intelligent Systems and advanced degrees in computer science, with extensive academic, research, and teaching experience across Jordan and Saudi Arabia. His research focuses on meta-heuristic and evolutionary optimization, data science, scheduling, and deep learning, with strong applications to large-scale real-world problems such as transportation, airport slot scheduling, resource allocation, and mega-event management. He has led and contributed to impactful community-oriented research, particularly in improving services for pilgrims during Hajj and Umrah using AI and data analytics. Prof. Shambour has published widely in high-quality international journals and conferences and serves as an associate editor and reviewer for leading scientific publishers. An experienced educator, he teaches courses spanning AI, machine learning, optimization, data analytics, and programming, and actively contributes to academic service, professional societies, and community development.

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Featured Publications

Marco Zanotti | Data Science | Best Researcher Award

Mr. Marco Zanotti | Data Science | Best Researcher Award

Mr. Marco Zanotti | University of Milan-Bicocca | Italy

Marco Zanotti is an accomplished Machine Learning Engineer and Data Scientist specializing in time series analysis, forecasting, anomaly detection, and econometrics. With extensive experience across sectors such as e-commerce fashion, tourism, aviation, and digital services, he has played a key role in designing and improving advanced forecasting systems that drive data-informed business decisions. He currently serves as a Data Scientist and Forecasting Specialist at Wanan Luxury (Rome, Italy), following previous positions at Blogmeter, T-Voice, and Uvet Amex GBT, where he contributed to predictive modeling, machine learning optimization, and process automation. In academia, Marco is an Adjunct Professor at the University of Milan and other leading Italian universities, where he teaches modern time series forecasting, machine learning, programming, and statistics at both Bachelor’s and Master’s levels. He holds a Ph.D. in Statistics from the University of Milano-Bicocca, a Post-graduate Diploma in Data Science for Economics, Business and Finance, and an M.Sc. in Economics and Finance from the University of Milan. Fluent in Italian, English, and French, Marco is proficient in R, Python, SQL, Git, Shiny, and Google Cloud Platform. A member of the International Institute of Forecasters, he is passionate about bridging the gap between academic research and industrial applications, mentoring young data scientists, and advancing the science of predictive analytics.

Profile: Orcid

Featured Publications

Zanotti, M. (2025, December). On the retraining frequency of global models in retail demand forecasting. Machine Learning with Applications. https://doi.org/10.1016/j.mlwa.2025.100769

Zanotti, M., & Mazzucchelli, L. (2021). dispositionEffect [Research protocol or software].

Tsomene Doungmo Stany Lionel | Computational Science | Best Researcher Award

Mr. Tsomene Doungmo Stany Lionel | Computational Science | Best Researcher Award

Mr. Tsomene Doungmo Stany Lionel | University of Yaoundé 1 | Cameroon

Tsomene Doungmo Stany Lionel is a passionate and dedicated researcher in organic chemistry with a strong academic foundation from the University of Yaoundé I. Guided by Dr. Angélique Nicolas Messi, he has developed a deep interest in chemical synthesis, molecular modeling, and sustainable material development. His academic journey has been complemented by active participation in international workshops, scientific conferences, and professional training programs focused on structural biology, drug discovery, and research funding. He possesses excellent digital and analytical skills, proficient in a range of scientific software used for chemical analysis and molecular visualization. Fluent in French and English, Lionel communicates scientific ideas effectively and is committed to contributing to innovative and sustainable advancements in chemistry.

Profiles:  Orcid

Featured Publications

Mbeket, S. B. N., Doungmo, S. L. T., & Nicolas, M. A. (2025). Computational insights into C–O–C-type biflavonoids as multi-target inhibitors of ERα, PR, EGFR, and mTOR in breast cancer therapy. Computational and Structural Biotechnology Reports, 100065. https://doi.org/10.1016/j.csbr.2025.100065