Dexter Shepherd

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Outreach and International Teaching

Some of the outreach programs I have been involved with organising. In addition my international teaching experience.

Projects Past and Present

Python Libraries

Check out the Python libraries/modules I have made for you to use in your own projects.

Robotics

See more of the robots I have worked on (Gallery).

Tutorials

Setting up some of the software I made in past projects

Publications

Check out my publications and public datasets.

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Dexter Shepherd

I am a PhD student at the University of Sussex, researching tactile sensors for robotic locomotion. My work spans both hardware and software development, with extensive experience using platforms such as Arduino and Raspberry Pi Foundation systems. I have worked across a broad range of artificial intelligence methodologies, from statistical machine learning to deep learning, reinforcement learning, and evolutionary algorithms. My research focuses on understanding how different sensing modalities and learning approaches can enable more robust and adaptive robot behaviour. Beyond academia, I am passionate about widening access to AI and robotics education. I have worked in schools across the UK and helped establish training programs in Africa to support hands-on learning in data science, electronics, and intelligent systems. This website serves as a living portfolio, a space to document my projects, research, and technical explorations over time.

Qualifications

PhD in Bio-Robotics and Artificial Intelligence

University of Sussex, Brighton, United Kingdom

Oct 2022 – Present (Expected completion: March 2026)

  • Research focus on machine learning for tactile sensing and bio-inspired robotic locomotion.
  • Development of optical and electrical tactile sensors alongside spatial-temporal AI models.
  • Application of reinforcement learning, evolutionary algorithms, and embedded AI systems.

BSc in Computer Science and Artificial Intelligence (First Class Honours)

University of Sussex, Brighton, United Kingdom

Sept 2019 – May 2022

  • Specialised in machine learning, robotics, and software engineering.
  • Awarded highest mark in cohort for AI dissertation project.
  • Strong foundation in algorithms, data science, and embedded systems.

Experience

Volunteer Course Instructor / Course Convenor

TReND in Africa, Sussex AI, BioRTC, LUANAR (Malawi), Yobe State University (Nigeria)

Dec 2023 – Present

  • Delivered postgraduate machine learning courses in Malawi covering data analysis, regression, classification, and deep learning.
  • Led an online Python crash course, coordinating a team of five instructors and developing video content and worksheets.
  • Directed African operations in 2025, managing logistics, curriculum design, and deployment of ML and data-logging hardware courses.
  • Delivered machine learning workshops for computational neuroscience in Yobe State, Nigeria.

Head of Student Mentor Scheme

University of Sussex – School of Engineering and Informatics

Aug 2022 – Dec 2025

  • Led a student mentoring team delivering academic and welfare support sessions.
  • Coordinated workshops and provided regular briefings to senior faculty on student needs.
  • Doubled student participation during tenure through improved engagement and support structure.

Senior Teaching Assistant

University of Sussex – School of Engineering and Informatics

Oct 2022 – May 2025

  • Taught over eight modules in AI, robotics, and computer science.
  • Designed assessments involving evolutionary agents for real-world robots.
  • Led construction of 200+ Python-controlled robots.
  • Developed open-source machine learning and robotics libraries for embedded systems.

Research Assistant

University of Sussex – CoNNeCT Group

May 2021 – Jul 2021, May 2022 – Aug 2022

  • Built low-cost 3D-printed robotic platforms using Jetson Nano controllers.
  • Investigated ant-inspired navigation algorithms in real-world environments.
  • Integrated GPS and mobile signal tracking systems for outdoor robotics experiments.

Reserve Infantry Soldier

British Army – Princess of Wales Royal Regiment

Oct 2019 – Oct 2022

  • Completed advanced first aid and combat training.
  • Developed resilience, teamwork, and leadership under high-pressure conditions.