Christos Roumeliotis | Computer Science | Young Scientist Award

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Mr. Christos Roumeliotis | Computer Science | Young Scientist Award

Electrical & Computer Engineering University of Western Macedonia Greece

Christos Roumeliotis is an accomplished Electrical and Computer Engineer specializing in Biomedical Technology, Healthcare, and Blockchain applications in energy. With a keen entrepreneurial spirit, he has been recognized in Forbes 30 Under 30 Greece and is an active member of the IEEE. As a young leader, he has held notable positions in the IEEE Student Branch and worked in various technology-driven roles.

Profile

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🎓 Education:

Christos completed his integrated MSc in Electrical and Computer Engineering from the University of Western Macedonia (UoWM). His academic journey has been complemented by a Reciprocal Scholarship and active participation in IEEE initiatives.

💼 Experience:

Christos serves as a Business Development Partner at Because Group, focusing on innovative marketing solutions. He co-founded Innovation Bee, where he leads as CEO, providing strategic AI-driven solutions across industries. He also co-founded Gridustry, a blockchain-based energy certification and trading company, aiming to optimize green energy market systems.

🔬 Research Interests:

Christos’s research spans Biomedical Technology for health solutions, Blockchain in energy, and smart contracts. His projects include blockchain-based Peer-to-Peer Energy Trading, green certificates, and a non-invasive wearable for Multiple Sclerosis monitoring.

🏆 Awards:

  • IEEE CS 20 in their 20s List (2023): Recognized among emerging leaders in Computer Science and Engineering.
  • Forbes 30 Under 30 Greece (2023): Featured among Greece’s dynamic young professionals.
  • Green Cities Competition (2022): Won 2nd place for innovative solutions in sustainable city development.

📄 Publications Top Notes:

“A Comprehensive Survey of Blockchain in IoT,” 2024. Intelligent Computing on IoT 2.0, Taylor & Francis. Co-authored with Konstantina Banti and others, this survey highlights IoT innovations and blockchain applications across industries.

“Blockchain and Digital Twins in Smart Industry 4.0,” 2024. Designs, DOI. This review discusses blockchain-integrated digital twins, analyzing Industry 4.0 applications and benefits.

Oksana Mandrikova | Neural Networks | Best Researcher Award

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Prof Dr. Oksana Mandrikova | Neural Networks | Best Researcher Award

Chief Researcher, Federal State Budget Research Institution Institute of Cosmophysical Research and Radio Wave Propagation, Far Eastern Branch of the Russian Academy of Sciences (IKIR FEB RAS), Russia

Oksana V. Mandrikova was born in 1972. She graduated from Shevchenko Kyiv National University in 1995 and was awarded the title of Doctor of Technical Science in 2009. Currently, she serves as the Chief Researcher and Head of the Laboratory of System Analysis at the Institute of Cosmophysical Research and Radio Wave Propagation, Far Eastern Branch of the Russian Academy of Sciences. Additionally, she is a Professor at the Control System Department of Kamchatka State Technical University. Her scientific interests encompass intelligent techniques for geophysical data analysis, wavelets, neural networks, the ionosphere, the magnetosphere, and signal anomalies. She has authored over 150 publications, including books and papers. 📚

Profile

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Publications Top Notes 🏆

  1. Hybrid Neural Network Approaches
  2. Generalized Multicomponent Model (GCCM)
  3. Hybrid Model for Non-Stationary Time Series
  4. Nonlinear Approximating Scheme
  5. Neural Network Methods for Galactic Cosmic Rays
  6. Geomagnetic Disturbance Detection

Souhail Dhouib | Artificial Intelligence | Best Researcher Award

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Prof Dr. Souhail Dhouib | Artificial Intelligence | Best Researcher Award

Full Professor, Higher Institute of Industrial Management, University of Sfax, Tunisia

 

Prof. Souhail Dhouib, a Tunisian national born on June 18, 1972, is a distinguished figure in the realms of Artificial Intelligence and Operations Research. With over two decades of experience in academia and industry, he stands as a pioneering figure in decision making and planning methodologies, notably recognized for inventing the Dhouib-Matrix optimization concept.

Profile

Orcid

Education 🎓

Prof. Dhouib pursued his academic journey at the Faculty of Management and Economics Sciences, Sfax University, Tunisia, where he earned his Ph.D. in Quantitative Methods, his Master’s degree in Operations Research and Production Management, and his Bachelor’s degree in Management Information Systems.

Experience 💼

With a rich blend of academic prowess and practical acumen, Prof. Dhouib has served in various capacities. From being a General Manager to founding companies specializing in business software development, his expertise spans across industries. Moreover, his proficiency extends to consultancy for businesses and industries, shaping his role as a seasoned Operations Research Analyst.

Research Interests 🔍

Prof. Dhouib’s research interests revolve around Artificial Intelligence, Operations research, Optimization algorithms, Logistic, Supply Chain Management, Business Intelligence Systems, and Enterprise Resource Planning (ERP). His innovative approaches have garnered recognition in academia and industry alike.

Awards 🏆

Prof. Dhouib’s contributions have been acknowledged through numerous awards and accolades, symbolizing his impact and influence in the field of decision making and planning methodologies.

Publications Top Notes📚

Intelligent Path Planning for Cognitive Mobile Robot Based on DhouibMatrix-SPP Method – Cognitive Robotics, 2024.

Multi-Start Constructive Heuristic through Descriptive Statistical Metrics: The Dhouib-Matrix-4 Metaheuristic – International Journal of Operational Research, 2024.

Innovative Method to Solve the Minimum Spanning Tree Problem: The Dhouib-Matrix-MSTP (DM-MSTP) – Results in Control and Optimization, 2024.

Enhancing the Dhouib-Matrix-4 Metaheuristic to Generate the Pareto Non-Dominated Set Solutions for Multi-objective Travelling Salesman Problem: The DM4-PMO Method – Results in Control and Optimization, 2024.

Faster than Dijkstra and A* Methods for the Mobile Robot Path Planning Problem Using Four Movement Directions: The Dhouib-Matrix-SPP-4 – Advances in Transdisciplinary Engineering, Mechatronics and Automation Technology, 2024.