Graduate MSc Programmer with an experience in PC, console, VR, AR, AI game development using Unity. Currently, pursuing a PhD in Artificial Intelligence at Kingston University, focusing on Object Detection in the context of Data Scarcity, and Energy Efficiency.

• Docker - containerised various AI models based on PyTorch and Tensorflow/Keras solving dependency/driver issues.
• Linux - developing and working on Linux-based distributives like Ubuntu and Arch Linux to run machine learning algorithms. From installation to deployment/containerisation.
• Data Science - experience developing AI methodologies using modern tools like PyTorch, Tensorflow/Keras, NumPy, Pandas, ImageAI, Streamlit.
• C/C++ – 9 years of experience. PS4 games development, OpenGL and Vulkan graphics programming, custom and commercial game engines: Unity, Unreal Engine 4, cocos2d-x, GFC (SDL based).
• C# – 8 years of experience of Unity games and tools development for various types of projects.
• Python – Linux platform, Raspberry Pi and external motherboard interactions via GPIO library. KIWI, Neural Networks, scikit, experimental DNA project.
• JavaScript, HTML, CSS, PHP – basic web development, database interactions and AJAX techniques.

• 2015 – 2024: Kingston University, Kingston, London, UK
  • Doctor of Philosophy Artifical Intelligence
    • Embarking on my AI PhD journey has been an intellectually rewarding experience, with my primary focus centered on conducting a comprehensive analysis of various methodologies within the dynamic field of Computer Vision. Specifically, my research has delved into advanced Object Detection techniques, highlighting the innovative You Only Look Once (YOLO) methodology. Navigating through the intricacies of Few-Shot Learning Techniques has deepened my understanding, allowing for effective object recognition with limited training data. This exploration has not only strengthened my theoretical foundation but also fostered a holistic perspective on AI applications, contributing to the interdisciplinary nature of the field. As I continue this journey, my aim is to not only expand the theoretical knowledge in computer vision but also to offer meaningful insights into the diverse methodologies that shape the landscape of artificial intelligence.
  • Master's Degree Games Development (Games Programming)
    • 3D Games Programming (80, A), Digital Studio Practice (82, A), Media Specialist Practice (90, A+), Machine Learning and Artificial Intelligence (83, A), Digital Media Final Project
  • Bachelor’s Degree with Honours Computer Science (Games Programming)
    • Year 3: Individual Project (88, A+), Game Creation Processes (74, A), Optimised Programmings for Game Devices (74, A), Internet Security (77, A)
    • Year 2: Database Application Development, 3D Graphics Programming, High Level Game Development, Network and Operating Systems
    • Year 1: Business Analysis and Solution Design (75, A), Object-Oriented Programming (91, A+), Game Science (92, A+), Games Technology (94, A+)
    • Year 0: Technical Investigation & Skills (69, B+), Mathematics for Computing (89, A+), Computer Systems (85, A+), Computer Programming (89, A+)

• International Conference on Distributed Computing in Sensor Systems - Evaluation of Environmental Conditions on Object Detection Using Oriented Bounding Boxes for AR Applications. (Authors: Vladislav Li, Barbara Villarini, Jean-Christophe Nebel, Thomas Lagkas, Panagiotis Sarigiannidis, Vasileios Argyriou)
• IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology - A Modular Deep Learning Framework for Scene Understanding in Augmented Reality Applications. (Authors: Vladislav Li, Barbara Villarini, Jean-Christophe Nebel, Argyriou Vasileios)
• IEEE INFOCOM 2022 - IEEE Conference on Computer Communications Workshops - Super Resolution for Augmented Reality Applications. (Authors: Vladislav Li, George Amponis, Jean-Christophe Nebel, Vasileios Argyriou, Thomas Lagkas, Savvas Ouzounidis, Panagiotis Sarigiannidis)
• Azerbaijan Journal of High Performance Computing - Object Recognition for Augmented Reality Applications. (Authors: Vladislav Li, Georgios Amponis,Jean-Christophe Nebel, Vasileios Argyriou, Thomas Lagkas and Panagiotis Sarigiannidis)
• SIGGRAPH Asia 2020 - Growth-based 3D modelling using stem-voxels encoded in digital-DNA structures. (Authors: Prof. V. Argyriou, T. Raymond, V. Li).

• 2021 - Present: Researcher at Kingston University
• 2020 - 2021: Teaching Assistant at Kingston University
• 2020 - 2020: Creative Programmer at Kingston University
• 2018 - 2019: Teaching Assistant at Kingston University

• TALON - Autonomous and Self-organized Artificial Intelligent Orchestrator for a Greener Industry 4.0
• vladislav.li - personal portfolio.

• 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.

• 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.