Papers

12

Total Citations

90

H-Index

4

About

Nikos Nikolaidis is a leading researcher at the intersection of autonomous systems, robotics, and deep learning, with a particular focus on enabling safe and robust operation of Unmanned Aerial Vehicles (UAVs). His most impactful work, "Vision-based UAV Safe Landing exploiting Lightweight Deep Neural Networks" (33 citations), addresses a critical challenge in drone autonomy by developing efficient, real-time visual landing systems. Nikolaidis is also the driving force behind the **OpenDR toolkit** (24 citations), an open-source framework that bridges the gap between deep learning and robotics by providing high-performance, low-footprint solutions tailored for robotic applications. His research consistently tackles the "sim-to-real" gap, as evidenced by his work on the **CARLA2Real** tool and synthetic data generation frameworks for improved UAV detection and human-centric robotic vision. By developing pipelines for generating realistic synthetic data and leveraging knowledge distillation techniques, Nikolaidis is advancing the reliability of autonomous systems in real-world environments. His contributions are foundational for students and researchers seeking to deploy deep learning on resource-constrained robotic platforms, making autonomous flight and navigation safer and more accessible.

Research Focus

Key Achievements

4
H-Index
12
Papers
90
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Vision-based UAV Safe Landing exploiting Lightweight Deep Neural Networks
33 citations · 2021
📈 Most Prolific Year: 2022 (5 Papers)
🤝 Key Collaborators: 45
🏛 Institutions: Aristotle University of Thessaloniki, International Hellenic University

Top Papers

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    Simulation environments
    8 citations · 2022
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago