Vangelis Lamprou | Network Intrusion Detection | Best Researcher Award

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Mr. Vangelis Lamprou | Network Intrusion Detection | Best Researcher Award

Vangelis Lamprou at National Technical University of Athens | Greece

Mr. Vaggelis Lamprou is a PhD student in the School of Electrical and Computer Engineering at the National Technical University of Athens (NTUA) and a Machine Learning Engineer specializing in deep learning, interpretable AI, and probabilistic modeling. With a strong academic foundation in mathematics and artificial intelligence, he has contributed to European-funded R&D projects in federated learning, generative AI, anomaly detection, and cybersecurity for next-generation networks. His research has been published in leading journals, including Computer Methods and Programs in Biomedicine and the IEEE Open Journal of the Communications Society.

Professional Profile:

Education: 

Mr. Vaggelis Lamprou holds a strong academic background spanning mathematics and artificial intelligence, currently pursuing his PhD in the School of Electrical and Computer Engineering at the National Technical University of Athens (NTUA) with a focus on deep learning, interpretable AI, and probabilistic modeling. He earned his M.Sc. in Artificial Intelligence from NCSR Demokritos and the University of Piraeus,  where his thesis explored the evaluation of deep learning interpretability methods for medical images in terms of faithfulness. Prior to that, he completed an M.Sc. in Mathematics at the University of Bonn, Germany. His academic journey began with a B.Sc. in Mathematics from the National and Kapodistrian University of Athens (NKUA).

Experience:

Mr. Vaggelis Lamprou brings extensive professional expertise in machine learning and data analytics, with a strong track record in both academic and industry-driven innovation. He has been serving as a Machine Learning Engineer at the DSS Lab, EPU-NTUA, where he develops AI-based solutions in federated learning and generative AI for European R&D projects. Previously, as a Machine Learning Engineer at Infili Technologies SA, he designed advanced anomaly detection systems and implemented privacy-preserving mechanisms for federated learning environments. He worked as a Data Analyst at Harbor Lab, where he conducted SQL-based analytics, performed Python-driven exploratory data analysis, and collaborated with the engineering team to build a Port Cost Estimator, optimizing maritime cost assessment processes.

Research Interest:

Mr. Vaggelis Lamprou’s research interests lie at the intersection of artificial intelligence, mathematics, and secure computing, with a focus on advancing both theoretical foundations and practical applications. In AI, he specializes in deep learning architectures, interpretable AI techniques, and probabilistic modeling, aiming to enhance transparency and trust in machine learning systems. His expertise extends to computer vision and natural language processing, particularly in developing interpretability methods for medical imaging and building robust NLP pipelines. He is also engaged in federated learning and cybersecurity research, working on privacy-preserving AI and ensuring trustworthiness in emerging 5G/6G network environments. Additionally, he explores the integration of probability theory and statistical methods into AI, leveraging mathematical rigor to improve model reliability and performance.

Publications Top Noted:

Federated Learning for Enhanced Cybersecurity and Trustworthiness in 5G and 6G Networks: A Comprehensive Survey

  • Year: 2024 | Citations: 16

On the Evaluation of Deep Learning Interpretability Methods for Medical Images Under the Scope of Faithfulness

  • Year: 2024 | Citations: 4

Grad-CAM vs HiResCAM: A Comparative Study via Quantitative Evaluation Metrics

  • Year: 2023 | Citations: 4

Conclusion:

With a solid foundation in mathematics, AI, and cybersecurity, Mr. Vangelis Lamprou exemplifies the qualities of a Best Researcher Award recipient in Network Intrusion Detection. His work addresses some of the most pressing challenges in ensuring trust and transparency in next-generation networks. As he continues to expand his research scope and global engagement, he is poised to play a pivotal role in shaping the future of secure AI-driven systems. His combination of academic rigor, technical innovation, and applied impact makes him a deserving candidate for this recognition.

Assoc. Prof. Dr. Muharrem Tuncay Gençoğlu | Cybersecurity | Best Researcher Award

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Assoc. Prof. Dr. Muharrem Tuncay Gençoğlu | Cybersecurity | Best Researcher Award

Assoc. Prof. Dr. Muharrem Tuncay Gençoğlu | Fırat University | Turkey

📌 Assoc. Prof. Dr. Muharrem Tuncay Gençoğlu is a distinguished researcher in Applied Mathematics, Cryptology, and Cybersecurity. He holds dual PhDs—one in Applied Mathematics from Fırat University (Türkiye) and another in Cryptology from Vector Sciences Academy (Azerbaijan). With expertise in cybersecurity, cryptographic systems, and artificial intelligence, he has worked with institutions like Fırat University, National Defense University, and Ahmet Yesevi University. His research spans random number generation, blockchain, and quantum computing, and he has published extensively in international journals. A member of multiple prestigious associations, he is actively involved in COST projects and TÜBİTAK-funded research.

Professional Profile:

Google Scholar

Suitability for Best Researcher Award

Assoc. Prof. Dr. Muharrem Tuncay Gençoğlu is a highly deserving candidate for the Best Researcher Award due to his groundbreaking contributions to Applied Mathematics, Cryptology, and Cybersecurity. His dual PhDs and extensive work with academic and defense institutions highlight his expertise and leadership in these critical fields.

Education & Experience

  • Ph.D. in Applied Mathematics – Fırat University (2013)
  • Ph.D. in Cryptology – Vector Sciences Academy, Azerbaijan
  • M.Sc. in Applied Mathematics – Fırat University (1995)
  • B.Sc. in Mathematics – Fırat University (1992)
  • B.Sc. in Mathematical Engineering – Istanbul Technical University (1997)
  • B.Sc. in Computer Engineering – Texas A&M University (2017)
  • International Relations (English, Ongoing) – Anadolu University
  • Senior Associate Professor – Fırat University (2015-Present)
  • Lecturer & Researcher – National Defense University (2017-Present)
  • Lecturer – Ahmet Yesevi University
  • Postdoctoral Researcher – Technical University of Berlin (2014)
  • Head of Department & Teacher – Private Sector (1988-2004)
  • Chairman of the Board – TEB Eğitim Hizmetleri (2004-2010)

Professional Development

📚 Dr. Gençoğlu has actively contributed to cybersecurity, cryptographic modeling, and artificial intelligence. He has received specialized training in ISO 27001 Information Security, Cyber-Terrorism, and Cyber Defense. As an academic advisor, he has guided over 50 master’s theses, including current research on cryptocurrency analysis using deep learning. He has led major TÜBİTAK-funded projects and is a member of international research groups like COST Actions. His collaborations with global cybersecurity organizations showcase his dedication to strengthening data security and cryptographic resilience.

Research Focus

🔬 Dr. Gençoğlu’s research spans applied mathematics, cybersecurity, cryptology, and artificial intelligence. His TÜBİTAK 1002 project explored random number generation through chemical reactions, a crucial innovation in cryptographic security 🔢. His work in blockchain, quantum cryptography, and network security addresses threat modeling, privacy preservation, and cyber intelligence 🔐. As a principal investigator in CHIST-ERA Distributed Systems, he contributes to privacy-enhancing cryptographic techniques. His contributions in COST Actions on mathematical modeling, quantum networks, and biological computation further cement his role as a leader in future-proof cryptographic systems.

Awards & Honors

🏆 Awards & Recognitions:

  • TÜBİTAK 1002 Grant – Project on Random Number Generation using Chemical Reactions 🏅
  • COST Action Leadership – Contributions to CA18232, CA21109, CA21169 🌍
  • Researcher in Distributed AI Lab – Technical University of Berlin (2014) 🤖
  • ISO 27001 Information Security Certification – IRCA-IPC 🛡️
  • Cybersecurity & Cyber-Terrorism Certifications – Various Institutions 🔓

Publication Top Notes:

  • 🔬 Use of quantum differential equations in sonic processes – Applied Mathematics and Nonlinear Sciences,  (Cited by: 62)
  • 🔐 Importance of Cryptography in Information Security – IOSR Journal of Computer Engineering (IOSR-JCE),  (Cited by: 43)
  • 🧠 Numerical simulations to the nonlinear model of interpersonal relationships with time fractional derivative – AIP Conference Proceedings,  (Cited by: 43)
  • 🔓 Cryptanalysis of a new method of cryptography using Laplace transform hyperbolic functions – Communications in Mathematics and Applications,  (Cited by: 24)
  • 🔢 Use of integral transform in cryptology – Science and Engineering Journal of Fırat University,  (Cited by: 18)
  • 🏫 Ortaokul öğrencilerinin bilgi güvenliği farkındalığı – Savunma Bilimleri Dergisi,  (Cited by: 10)