Hi, I'm Matt.

I'm a machine learning engineer, software engineer and researcher.

With almost a decade of experience, my focus is building interesting products and models. My interests span different areas, but are squarely focused around technology. I acquired a PhD in machine learning in 2023, and have been involved in hardware engineering, machine learning engineering, data science and web development.

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About me.

I am a collaborative and driven machine learning engineer with a strong foundation in technical skills, as well as research and product management. After earning my PhD from Loughborough University, where my research on evidential classification in network security led to high-impact publications, I gained experience in machine learning areas such as neural networks and time-series forecasting. My recent role as a Technical Product Owner for an IoT project allowed me to lead embedded engineering innovations for public transport, utilising my skills in hardware design, machine learning, and stakeholder engagement to improve passenger experience.



In addition to technical expertise, I have completed advanced training in leadership, strategic innovation, and project management, which complement my proficiency in cloud computing, embedded systems, and programming languages like Python and C. I am known for a hands-on approach to problem-solving and continue to contribute to cutting-edge research in Beyond 5G networks, presenting my work at industry conferences and expanding my impact across both academic and commercial domains.

Projects and publications.

Traffic Insight

Developed a traffic aware computer vision system to detect and track vehicle junction usage. Fine-tuned YOLO11 model for better aerial vehicle detection.

  • Pytorch
  • OpenCV
  • Computer Vision
  • Transportation

LR-DS

Developed a feature selection technique for binary classifiers using epistemic uncertainty.

  • Pytorch
  • Classification
  • Feature Selection
  • Uncertainty

NN-DS

Designed a technique to defend against adversarial machine learning attacks using epistemic uncertainty.

  • Pytorch
  • Classification
  • Adversarial Machine Learning
  • Uncertainty

BusMONITOR

Created an embedded IoT system from scratch to gather and predict transportation environment data.

  • Embedded
  • C
  • Hardware
  • Django
  • Pytorch

My skills.

My Experience.

Machine Learning Researcher

Loughborough University, 2024 - Present

Working for Loughborough University, researching utilising Graph Neural Networks in the Beyond 5G networking field - specifically in network slicing.

Technical Product Owner

Vectare Ltd, 2022 - 2024

I worked as a Technical Product Owner, developing embedded devices and integrating with a Django system for machine learning model creation.

Doctoral Researcher

Loughborough University, 2019 - 2022

I started my doctorate programme in 2019, with the aim to research in the machine learning and network security domains.

Research Assistant

Loughborough University, 2018

Assisting in researching scalable micro-data cluster usages for web services. Experimented with web page serving time and data caching, utilising both Docker containerised, and bare-metal services.

Contact me.

Please contact me directly at mattbeechey@gmail.com or by using this form.