Ioanna Pappa
About
I am a postgraduate student in Computer Science with a background in Intelligent Systems and a strong interest in Artificial Intelligence, Machine Learning and Unmanned Systems. My academic work focuses on research-driven methodologies, model development and evaluation and AI applications in environmental and real-time detection systems.
Research Interests
- Artificial Intelligence & Deep Learning
- Computer Vision
- Unmanned Aerial Systems (UAS)
- Environmental Risk Modeling
- Geospatial Data Analysis (GIS)
Research
This research investigates the application of deep learning models for real-time lightning detection. YOLOv5 and YOLOv8 architectures were implemented and evaluated on a curated lightning image dataset. The study explores AI-driven alternatives to traditional physics-based detection systems.
Request Thesis PDF
Skilodimou, H. D.; Bathrellos, G. D.;
Pappa, M.-I.;
Youssef, A. M.; Kontakiotis, G.;
Karymbalis, E. (2024).
Assessing flood hazard mapping using AHP and GIS in a tectonically active region.
Zeitschrift für Geomorphologie.
https://doi.org/10.1127/zfg/2024/0804
Independent Projects
Development of a custom object detection pipeline using YOLOv8. Includes dataset preprocessing, model training, and performance evaluation.
View ProjectPersonal project applying spatial analysis techniques in GIS for environmental hazard assessment and visualization.
View ProjectTutorials
MicroBlaze AXI4-Lite Adder on Arty A7-100T
End-to-end hardware–software co-design tutorial demonstrating custom AXI4-Lite peripheral integration with MicroBlaze, including timing closure, power analysis and Vitis validation.
Technical Skills
- Programming: Python, C, SQL
- AI/ML: Neural Networks, Deep Learning, Computer Vision (YOLO)
- GIS: ArcGIS, QGIS
- Robotics: ROS, Trajectory Planning
- Tools: Linux, MATLAB
Contact
Email: ipappa [at] cs.uoi [dot] gr
GitHub: github.com/ioannapappa