Mr. Kostas Ordoumpozanis | Computer Vision | Best Researcher Award

Mr. Kostas Ordoumpozanis | Computer Vision | Best Researcher Award

Phd Cand. Department of Cultural Technology and Communication, University of the Aegean Greece, Greece

Kostas Ordoumpozanis is a dynamic AI researcher, developer, and educator specializing in multi-agent AI systems ๐Ÿค–. Currently a PhD candidate at the University of the Aegean, Greece, his expertise spans AI-driven automation, large language models (LLMs), retrieval-augmented generation (RAG), and AI-human collaboration. With a background in mechanical engineering and over a decade of experience in full-stack development, AR, and creative technology, he blends technical proficiency with artistic innovation. Kostas is also an entrepreneur, recognized for his startup ventures in AI and augmented reality, making significant contributions to AI-driven storytelling, gamification, and sustainable design ๐ŸŒ.

Publication Profile

ORCID

๐ŸŽ“ Academic Background

Kostas holds a 5-year Mechanical Engineering degree from the University of Western Macedonia, Greece (2005) ๐Ÿ—๏ธ. He pursued PhD research on hybrid ventilated PV facades at the same institution (2006-2021) and is currently completing an MPhil in Computer Science & AI at the International Hellenic University (2023-present) ๐ŸŽ“. His latest research focuses on AI multi-agent systems as part of his PhD at the University of the Aegean (2024-present), further cementing his expertise in AI agency and intelligent automation.

๐Ÿ’ผ Professional Experience

With a diverse career spanning multiple domains, Kostas worked as a mechanical engineer and sustainable design simulation expert (2006-2016) before transitioning into digital arts, photography, and cinematography (2013-2020) ๐ŸŽฅ. His entrepreneurial journey includes founding a startup specializing in augmented reality (2016-2024) and serving as a skills educator (2008-2023) ๐Ÿ“š. Since 2018, he has been a full-stack developer, focusing on AI applications, web technologies, and vector databases. Currently, he is an AI researcher and developer working on LLMs, AI agents, and human-machine collaboration ๐Ÿค–.

๐Ÿ† Awards and Honors

Kostas has received numerous accolades, including recognition as a “Rising Start-Up Business” from the Evros Chamber, Greece (2023) ๐Ÿš€. He secured first place in the EU Interreg Greece-Bulgaria Startup Contest (2023) and was a finalist in the Athens StartUp Awards (2018) and XR COSMOS Greece (2021). His innovative contributions earned him a patent recognition in Greece (2018) ๐Ÿ….

๐Ÿ”ฌ Research Focus

His research revolves around AI agentic systems, LLM optimization, RAG architectures, and AI-driven storytelling ๐Ÿง . He explores the intersection of generative AI, human-computer collaboration, and augmented reality for educational and creative applications. His work also extends to sustainable AI, assessing the carbon footprint of deep learning models and developing efficient AI architectures for various domains.

๐Ÿ“ Conclusion

Kostas Ordoumpozanis is a visionary AI researcher and innovator, merging technical expertise with creative problem-solving. His contributions to AI agents, storytelling, and sustainable AI showcase his commitment to pushing technological boundaries. With a strong academic foundation, industry experience, and entrepreneurial mindset, he continues to shape the future of AI-driven systems and human-machine interaction ๐ŸŒ.

๐Ÿ“š Top Research Publications

Reviewing 6D Pose Estimation: Model Strengths, Limitations, and Application Fieldsย (2025) โ€“ Applied Sciences
Cited by: Multiple AI research articles

Green AI: Assessing the Carbon Footprint of Fine-Tuning Pre-Trained Deep Learning Models in Medical Imagingย (2024) โ€“ 3ICT Conference, Bahrain
Cited by: Research in sustainable AI and medical imaging

C-LINK Agent: Connecting Social Media Post Generation with Recommender Systemsย (2024) โ€“ SMAP 2024 Conference
Cited by: Works in AI-driven social media automation

A Second-Generation Agentic Framework for Generative AI-Driven Augmented Reality Educational Games” (2025) โ€“ EDUCON Conference
Cited by: Research in AI and AR-driven education

Energy, Comfort, and Indoor Air Quality in Nursery and Elementary School Buildings in the Cold Climatic Zone of Greece” (Published in Energy and Buildings)
Cited by: Sustainability and green architecture studies

Energy and Thermal Modeling of Building Faรงade Integrated Photovoltaics” (Published in Thermal Science)
Cited by: Research in sustainable energy and architecture

Narmilan Amarasingam | Artificial Intelligence | Best Researcher Award

Mr. Narmilan Amarasingam | Artificial Intelligence | Best Researcher Award

PhD student, Queensland University of Technology, Australia

Researcher specializing in drone-based remote sensing solutions for environmental and surveillance needs, focusing on precision agriculture and biosecurity. Expertise includes UAV remote sensing, artificial intelligence, and multispectral/hyperspectral image processing. Currently pursuing a PhD in Precision Agriculture at Queensland University of Technology.

Profile

Google Scholar

 

๐ŸŽ“ Education

PhD: Precision Agriculture, Queensland University of Technology (2021 – Present). MSc: Agricultural Engineering, Eastern University, Sri Lanka (2016 – 2018). BSc: Agriculture, Agricultural Engineering, Eastern University, Sri Lanka (2010 – 2015). BIT: Software Engineering, University of Colombo School of Computing, Sri Lanka (2011 – 2015)

๐Ÿ” Experience

Research Assistant at Charles Sturt University and Sunshine Coast Council on projects integrating AI and drone technology for environmental monitoring and invasive species detection.

๐Ÿ† Awards

QUT/Accelerate Higher Education Development Expansion and Development (AHEAD) World Bank Project Scholarship. Vice Chancellor’s Award for Early Career Researcher, Faculty of Technology, 2022.

๐ŸŒ Research Interests

Precision Agriculture, UAV-based Remote Sensing, Multispectral Image Processing, AI, Biosystems Engineering, Environmental Management.

๐Ÿ“š Publications

Co-authored numerous peer-reviewed articles in Q1 and non-Q1 ranking journals on topics related to UAV-based remote sensing and AI applications in agriculture and environmental management.

A review of UAV platforms, sensors, and applications for monitoring of sugarcane crops
Predicting canopy chlorophyll content in sugarcane crops using machine learning algorithms and spectral vegetation indices derived from UAV multispectral imageryDetection of white leaf disease in sugarcane using machine learning techniques over UAV multispectral images
Detection of White Leaf Disease in Sugarcane Crops Using UAV-Derived RGB Imagery with Existing Deep Learning Models
N Amarasingam, F Gonzalez, ASA Salgadoe, J Sandino, K Powell
E-agricultural concepts for improving productivity: A review