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📄 Curriculum Vitae

A Doctor of Artificial Intelligence, specialising in object detection within the contexts of data scarcity and energy efficiency, currently researching at Kingston University. With extensive experience in AI, VR, AR, and game development across multiple platforms including PC, console, and mobile, I have worked with a range of cutting-edge technologies to design and develop innovative solutions. My expertise spans across Unity, Unreal Engine, and other game engines, with a strong foundation in AI methodologies and optimisation techniques. Passionate about pushing the boundaries of intelligent systems, I seek to apply my knowledge to complex challenges in both academia and industry.

🚀 Skills

🔹 DevOps & Systems

  • Experienced in Docker, containerizing AI models based on PyTorch and TensorFlow/Keras, resolving complex dependency and driver issues.
  • Proficient in Linux (Ubuntu, Arch Linux, Void Linux), managing system installations, deployment, and containerization of machine learning applications.
  • Skilled in developing asynchronous backend systems using FastAPI, Celery, and Redis for efficient task processing and scalability.

🔹 Artificial Intelligence & Data Science

  • Strong background in data science, developing AI methodologies with PyTorch, TensorFlow/Keras, NumPy, Pandas, ImageAI, and Streamlit.
  • Hands-on experience in computer vision, implementing deep learning models and optimizing inference pipelines for real-time applications.

🔹 Programming & Software Development

  • Expertise in C/C++, working on PS4 game development, OpenGL and Vulkan graphics programming, and game engines like Unity, Unreal Engine 4, cocos2d-x, and GFC (SDL-based).
  • Proficient in C#, specializing in Unity game and tools development for various projects.
  • Strong knowledge of Python, developing applications for Linux platforms, Raspberry Pi GPIO interactions, KIWI, Neural Networks, scikit-learn, and experimental DNA analysis projects.
  • Experience with web development, using JavaScript, HTML, CSS, and PHP for database interactions and AJAX implementations.

🎓 Education

  • Ph.D. in Artificial Intelligence
    Kingston University (2021 – 2024)

  • M.Sc. in Games Development (Games Programming)
    Kingston University (2019 – 2020)

  • B.Sc. with Honours in Computer Science (Games Programming)
    Kingston University (2015 – 2019)

📚 Publications

  • Enhancing 3D Object Detection in Autonomous Vehicles Based on Synthetic Virtual Environment Analysis
    V. Li, I. Siniosoglou, T. Karamitsou, A. Lytos, I.D. Moscholios, S.K. Goudos, ...
    Image and Vision Computing, 154, 105385
    Year: 2025

  • Evaluating the Energy Efficiency of Few-Shot Learning for Object Detection in Industrial Settings
    G. Tsoumplekas, V. Li, I. Siniosoglou, V. Argyriou, S.K. Goudos, ...
    arXiv Preprint arXiv:2403.06631
    Year: 2024

  • Toward Green and Human-Like Artificial Intelligence: A Complete Survey on Contemporary Few-Shot Learning Approaches
    G. Tsoumplekas, V. Li, V. Argyriou, A. Lytos, E. Fountoukidis, S.K. Goudos, ...
    arXiv Preprint arXiv:2402.03017
    Year: 2024

  • A Closer Look at Data Augmentation Strategies for Finetuning-Based Low/Few-Shot Object Detection
    V. Li, G. Tsoumplekas, I. Siniosoglou, V. Argyriou, A. Lytos, E. Fountoukidis, ...
    2024 IEEE 14th International Symposium on Industrial Embedded Systems (SIES)
    Year: 2024

  • Super Resolution for Augmented Reality Applications
    V. Li, G. Amponis, J.C. Nebel, V. Argyriou, T. Lagkas, S. Ouzounidis, ...
    IEEE INFOCOM 2022 – IEEE Conference on Computer Communications Workshops
    Year: 2022

  • Object Recognition for Augmented Reality Applications
    V. Li, G. Amponis, J.C. Nebel, V. Argyriou, T. Lagkas, P. Sarigiannidis
    Azerbaijan Journal of High Performance Computing, 4(1), 15-28
    Year: 2022

  • Evaluation of Environmental Conditions on Object Detection Using Oriented Bounding Boxes for AR Applications
    V. Li, B. Villarini, J.C. Nebel, T. Lagkas, P. Sarigiannidis, V. Argyriou
    19th International Conference on Distributed Computing in Smart Systems
    Year: 2023

  • A Modular Deep Learning Framework for Scene Understanding in Augmented Reality Applications
    V. Li, B. Villarini, J.C. Nebel, V. Argyriou
    IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology
    Year: 2023

  • Growth-Based 3D Modelling Using Stem-Voxels Encoded in Digital-DNA Structures
    T. Raymond, V. Li, V. Argyriou
    SIGGRAPH Asia 2020 Posters, 1-2
    Year: 2020

🧑‍💼 Work Experience

  • Researcher, Kingston University (2021 – Present)
    Engaged in advanced research in the field of Artificial Intelligence, focusing on object recognition, virtual reality applications, and few-shot learning methodologies.

  • Teaching Assistant, Kingston University (2020 – 2021)
    Assisted in teaching and grading assignments for undergraduate and graduate students, particularly in the domains of computer science and artificial intelligence.

  • Creative Programmer, Kingston University (2020)
    Developed innovative software solutions and interactive experiences for academic projects, with a focus on AI applications and game development.

  • Teaching Assistant, Kingston University (2018 – 2019)
    Provided support for various computer science courses, helping students with course material, assignments, and practical coding exercises.

🚀 Projects Involvement

  • RAIDO
    Kingston University (2023 – 2026)
    Reliable AI and Data Optimization (RAIDO) - an ongoing EU Commission-funded international project focusing on developing innovative solutions for AI model reliability and data optimization in industrial and research applications.

  • TALON
    Kingston University (2022 – 2025)
    Autonomous and Self-organized Artificial Intelligent Orchestrator for a Greener Industry 4.0. This EU Commission-funded international project leverages AI to optimize industrial processes and reduce environmental impact.

  • Leonardo
    Kingston University (2020 – 2022)
    An object detection project for Leonardo, a private company focused on advanced AI techniques for recognizing and analyzing various objects in complex environments, particularly in industrial and aerospace sectors.

🎮✨ Additional Experience & Projects

  • Game Jams

    • 2020 Ludum Dare 47: Loop
    • 2020 Ludum Dare 46: Abducted
    • 2019 inKUbator Game Jam: Winner – Nobel Knight
    • 2019 Bental's Centre Game Jam: Red Boy
    • 2018 inKUbator Game Jam: Winner – Cell Resistence
    • 2016 inKUbator Game Jam: Save the Village

  • Side Projects

    • Peasants Engine – An attempt to implement a single-header legacy game engine.
    • Noname FPS – A collaboration project with Tyler Pope developing an FPS using Unreal Engine 4.23.

Keywords

  • Unity3D, Unreal Engine, cocos2d-x, KIWI, WebGL, Android, PS4, PC, Hololens AR, Oculus Rift VR, HTC Vive VR
  • Visual Studio, Visual Studio Code, C/C++, C#, Python, JavaScript, HTML, CSS, Forex Trading MQL4/5, OOP, ECS
  • Component-based Design, Design Patterns, Engine Architecture, GFC, SDL, OpenGL, Vulkan, Unity Barracuda
  • AI Object Recognition, Perforce, Git