Ioannis Mademlis
Papers
9
Total Citations
147
H-Index
6
About
Ioannis Mademlis is a researcher specializing in autonomous Unmanned Aerial Vehicles (UAVs), computer vision, and human-robot interaction, with a particular focus on intelligent drone systems for real-world applications. His work spans embedded AI for UAVs, deep learning-based visual perception, and autonomous cinematography, establishing him as a notable contributor to the rapidly evolving field of drone autonomy. Mademlis has made significant contributions to UAV safety and autonomy, including pioneering lightweight deep neural network approaches for safe drone landing and real-time visual object detection on embedded platforms — his most-cited work earning 46 citations. His research into gesture-based human-drone interaction, covered across multiple papers totaling over 30 citations, has opened new avenues for intuitive, contactless drone control in collaborative environments. Notably, he has advanced autonomous UAV cinematography, bridging computer vision and media production in ways that push commercial drone capabilities forward. Beyond individual UAVs, his recent work on human-swarm interaction for safety monitoring demonstrates a broadening vision toward multi-robot coordination. With over 140 cumulative citations and consistent output across high-impact topics, Mademlis represents an engaging voice at the intersection of robotics, deep learning, and practical autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Embedded UAV Real-Time Visual Object Detection and Tracking46 citations · 2019
- 2Vision-based UAV Safe Landing exploiting Lightweight Deep Neural Networks33 citations · 2021
- 3An Overview of Hand Gesture Languages for Autonomous UAV Handling22 citations · 2021
- 4Vision-based drone control for autonomous UAV cinematography17 citations · 2023
- 5Autonomous UAV Cinematography8 citations · 2022
- 6Semantic Image Segmentation Guided By Scene Geometry7 citations · 2021
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