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I am a Research Lecturer at the KIOS Research & Innovation Center of Excellence at the University of Cyprus. I earned my Ph.D. in Computer Engineering from the Department of Electrical and Computer Engineering at the University of Cyprus in 2014. I graduated top of my class with a B.Sc. in Computer Engineering in 2008 and completed an M.Sc. in Computer Engineering in 2010 with a full scholarship, all from the University of Cyprus.

My research lies at the intersection of Computing, Machine Learning, and Computer Vision. I have made significant contributions in the areas of computation/data-efficient machine/deep learning design/search (Cascade SVM), and perception learning for vision systems (EmergencyNet, DroNet), particularly in recognition, detection, segmentation, and control. My work has resulted in over 65 scientific publications, including two best paper awards. My long-term research goal is to address the questions: a) How can we design and optimize machine learning models to achieve high performance while being computation- and data- efficient? b) How can learning systems dynamically adapt to changing contexts and environmental conditions to enhance efficiency and robustness in real-time applications? c) What strategies can be developed to ensure the robustness and trustworthiness of AI systems, particularly in safety-critical applications, by mitigating vulnerabilities to cybersecurity threats, noise, and adversarial attacks?

My expertise extends to actively participating in the conception, design, and implementation of numerous National and European funded research and innovation projects. My research activities encompass applications in emergency management, traffic monitoring, autonomous vehicles, and surveillance. I also serve as a reviewer for several computer vision and machine learning journals (e.g., IEEE Trans. PAMI, IEEE Trans. Artificial Intelligence; IEEE Trans. Neural Networks and Learning Systems, IEEE Trans. Image Processing), and conferences (e.g., CVPR, ECCV, ICCV, WACV,  NeurIPS, ICML, ICLR). 

NEWS

JUN 2025🗣 Paper Presented at 6th International Conference on IEEE International Conference on Image Processing Applications and Systems (IPAS) - "A Lightweight and Efficient Convolutional Neural Network for Crowd Counting" - presentation video

OCT 2024📢 Kick-off of the Horizon Europe GuardAI project, coordinated by KIOS CoE where I serve as the Technical Lead.

JUL 2024📜Paper Accepted at IEEE TAI - Spatiotemporal Object Detection for Improved Aerial Vehicle Detection in Traffic Monitoring

JUL 2024🗣Paper Presented at 5th International Conference on Deep Learning Theory and Applications (DeLTA) - "Closing the Sim-to-Real Gap: Enhancing Autonomous Precision Landing of UAVs with Detection-Informed Deep Reinforcement Learning" - presentation

JUN 2024📜Paper Accepted at SN Computer Science - DiRecNetV2: A Transformer-Enhanced Network for Aerial Disaster Recognition

APR 2024📜Paper Accepted at DeLTA2024 - Closing the Sim-to-Real Gap: Enhancing Autonomous Precision Landing of UAVs with Detection-Informed Deep Reinforcement Learning

MAR 2024 🥇 New Funded Proposal under Horizon Europe - GuardAI (~€5M)

MAR 2024📜Paper Accepted at IEEE TNNLS - Towards Efficient Convolutional Neural Networks with Structured Ternary Patterns

FEB 2024 🗣  New paper presented at AAAI - Convolutional Channel-wise Competitive Learning for the Forward-Forward Algorithm - arxiv

Past NEWS

Edge Vision and AI 

"My research centers around machine learning and computer vision with a focus on developing efficient and robust representation learning algorithms for intelligent systems that are able to operate in dynamic and uncertain environments, perceive the world through multiple modalities in an adaptive fashion, and autonomously act in it in a way that both trustworthy and safe for humans."

EmergencyNet: Efficient Aerial Image Classification for Drone-Based Emergency Monitoring

YOLOpeds: Efficient real-time single-shot pedestrian detection for smart camera applications

C^3 Net: End-to-end deep learning for active smart camera control 

AirCamRTM: Enhancing Vehicle Detection for Efficient Aerial Camera-based Road Traffic Monitoring

HIGHLIGHTED ARTICLES

Toward Efficient Convolutional Neural Networks With Structured Ternary Patterns

This paper presents work toward utilizing static convolutional filters generated from the space of local binary patterns (LBPs) and Haar features to design efficient ConvNet architectures. These are referred to as Structured Ternary Patterns (STePs) and can be generated during network initialization in a systematic way instead of having learnable weight parameters thus reducing the total weight updates. 

TNNLS 2024

Spatiotemporal Object Detection for Improved Aerial Vehicle Detection in Traffic Monitoring

This work presents advancements in multiclass vehicle detection using unmanned aerial vehicle (UAV) cameras through the development of spatiotemporal object detection models. 

TAI 2024

PROJECTS and EVENTS

CONTACT ME

KIOS Research and Innovation Center of Excellence

1 Panepistimiou Avenue, 2109 Aglantzia,

Tel: (+357) 22 893450 / 22 893451

Email: ckyrkou@gmail.com

Email: kyrkou.christos@ucy.ac.cy