Mr. Nikolaos Schetakis began his academic career in physics, earning a Bachelor’s Degree in Physics from the University of Crete in 2008. His early academic promise was solidified through his Master of Science in Quantum Physics at the Technical University of Crete (TUC), completed in 2012 with an outstanding final grade of 8.92/10. This strong foundation in quantum theory laid the groundwork for his later specialization in Quantum Machine Learning, a field that merges his deep understanding of quantum mechanics with data-driven computational techniques. As of 2023, he is a PhD Candidate at TUC, continuing his advanced research and academic engagement in quantum systems and intelligent technologies.
Professional Endeavors
Nikolaos has blended academic rigor with industry experience over the past 14 years, showcasing a rare balance between theoretical innovation and practical implementation. He is currently the CEO of Quantum Innovation (Greece), where he leads quantum computing and AI initiatives, and Head of R&D at Alma-Sistemi Srl (Italy), overseeing advanced technological developments in aerospace and remote sensing. He has also served as a Scientific Researcher and Teaching Associate at TUC. His past roles include software developer at Sunrise Technologies, reinforcing his hands-on programming and system design capabilities. Across these roles, he has advanced projects focused on Quantum Machine Learning, AI integration, and adaptive intelligent platforms.
Contributions and Research Focus
Mr. Schetakis’s research contributions are centered around Quantum Machine Learning, plasma reconfigurable metasurfaces, space instrumentation, and intelligent remote sensing systems. He has led and participated in numerous EU-funded R&D projects, including four HORIZON 2020-MSCA-RISE programs and the prestigious HORIZON-EIC-PATHFINDER call. Notable initiatives include ERA4CH (earthquake risk platform for cultural heritage), PULSE (plasma-based metamaterials), and EUMAP (utilities management platform for lockdown scenarios). His research brings quantum theories into real-world applications, especially in aerospace, defense, and environmental risk assessment—bridging fundamental science and engineering through the lens of Quantum Machine Learning.
Impact and Influence
Nikolaos Schetakis has established a broad and growing influence in both the academic and industrial spheres. His leadership in multi-national research consortia under the HORIZON framework reflects his capacity to steer high-impact projects at the intersection of quantum physics, machine learning, and aerospace engineering. His work in Quantum Machine Learning is recognized as pioneering, especially in the context of intelligent sensor fusion, adaptive system calibration, and AI-driven quantum data processing. As a project manager and researcher, he has fostered collaboration among major European institutions such as OHB System AG, Thales Alenia Space, Airbus Defence & Space, and NEOSAT programs.
Academic Cites
Though still completing his doctoral studies, Nikolaos has already established an impressive academic record, with multiple publications and conference participations stemming from the projects he has contributed to. His involvement in cross-disciplinary applications of Quantum Machine Learning is increasingly cited in discussions related to remote sensing AI, quantum computing algorithms, and intelligent geospatial systems. As his doctoral research progresses, his academic profile is expected to rise further in citations and collaborative outputs.
Legacy and Future Contributions
Mr. Nikolaos Schetakis is poised to leave a significant legacy in the convergence of quantum computing and intelligent systems. With his leadership in Quantum Machine Learning, his ongoing projects will likely shape next-generation aerospace applications, intelligent sensing platforms, and quantum-enhanced AI tools. His future contributions are expected to focus on scalable and adaptive quantum models for large-scale data environments, particularly within the fields of Earth observation, defense, and advanced manufacturing. As he continues mentoring, innovating, and publishing, Nikolaos is set to become a key figure in Europe’s quantum-AI ecosystem.
📘Quantum Machine Learning
Mr. Nikolaos Schetakis has consistently applied Quantum Machine Learning principles in cutting-edge projects involving aerospace systems, remote sensing, and adaptive intelligent platforms. His research integrates quantum mechanics and AI, pushing the boundaries of Quantum Machine Learning toward real-world, scalable applications. As he continues leading interdisciplinary R&D, his commitment to Quantum Machine Learning is paving the way for disruptive innovations across both academia and industry.
✍️ Notable Publication
1️⃣Review of some existing QML frameworks and novel hybrid classical–quantum neural networks realising binary classification for the noisy datasets
Authors: N. Schetakis, D. Aghamalyan, P. Griffin, M. Boguslavsky
Journal: Scientific Reports
Year: 2022
Citations: 57
2️⃣Few-photon transport in many-body photonic systems: A scattering approach
Authors: C. Lee, C. Noh, N. Schetakis, D.G. Angelakis
Journal: Physical Review A
Year: 2015
Citations: 25
3️⃣ Quantum machine learning for credit scoring
Authors: N. Schetakis, D. Aghamalyan, M. Boguslavsky, A. Rees, M. Rakotomalala, ...
Journal: Mathematics
Year: 2024
Citations: 21
4️⃣Frozen photons in Jaynes–Cummings arrays
Authors: N. Schetakis, T. Grujic, S. Clark, D. Jaksch, D. Angelakis
Journal: Journal of Physics B: Atomic, Molecular and Optical Physics
Year: 2013
Citations: 17
5️⃣Binary classifiers for noisy datasets: a comparative study of existing quantum machine learning frameworks and some new approaches
Authors: N. Schetakis, D. Aghamalyan, M. Boguslavsky, P. Griffin
Journal: arXiv preprint
Year: 2021
Citations: 13
6️⃣Exploring Deep Learning Models on GPR Data: A Comparative Study of AlexNet and VGG on a Dataset from Archaeological Sites
Authors: M. Manataki, N. Papadopoulos, N. Schetakis, A. Di Iorio
Journal: Remote Sensing
Year: 2023
Citations: 12
7️⃣A serverless computing architecture for Martian aurora detection with the Emirates Mars Mission
Authors: D. Pacios, J.L. Vázquez-Poletti, D.B. Dhuri, D. Atri, R. Moreno-Vozmediano, ...
Journal: Scientific Reports
Year: 2024
Citations: 10