About
Adam Wynn is a PhD student in the Department of Computer Science at Durham University. He completed an integrated Masters degree in Computer Science from Durham University in 2022. He is interested in AI in education, automatic feedback, adaptive learning and educational technology. Adam's research is currently focused on using technology to enhance the learning experience and aims to develop systems that provide personalised feedback and support to students in real-time.
Research
My research explores the intersection of AI and education. Current projects include multilingual speech emotion recognition, confidence classification from voice, speech synthesis and style transfer, and automatic feedback systems.
Featured Publication
Abstract: Understanding speaker confidence is crucial in educational settings, as it can enhance personalised feedback and improve learning outcomes. This study introduces a novel framework for detecting speaker confidence by integrating human-engineered features with embeddings from the Whisper encoder. To address data limitations, a pseudo-labelling technique is employed to expand the labelled dataset, allowing the model to learn from both human-annotated and model-generated labels. The framework combines traditional speech features including pitch, volume, rate of speech, and the presence of disfluencies and stress, with Whisper embeddings, and uses a co-attention mechanism to fuse these representations and achieve an overall accuracy of 75%. This study contributes to advancing speech analysis, enabling applications that support person-alised learning and speaking skill development.
All Publications
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Semi-Supervised Speech
Confidence Detection Using Pseudo-Labelling and Whisper Embeddings
Wynn, A., Wang, J., Tan, X. (2025). In Artificial Intelligence in Education (AIED 2025). Lecture Notes in Computer Science, vol 15882, Springer, Cham. -
Unravelling Emotional Nuances:
A Cross-Linguistic Analysis of Sentiment Differences in Multilingual Movie Versions
Wynn, A., Wang, J., & Li, X. (2025). In Generative Systems and Intelligent Tutoring Systems. ITS 2025. Lecture Notes in Computer Science, vol 15723. Springer, Cham. -
A Topic Map Based Learning Management System to
Facilitate Meaningful Grammar Learning: The Case of Japanese Grammar Learning
Wang, J., Wynn, A., Mendori, T., & Hwang, G.-J. (2024). Smart Learning Environments, 11(1), 53. -
Simplifying Multimedia Programming for Novice
Programmers: MediaLib and Its Learning Materials
Wynn, A., Wang, J., & Valente, A. (2024). In Proceedings of the 2024 Innovation and Technology in Computer Science Education V. 2 (ITiCSE 2024). ACM. -
Analysing
Learner Behaviour in an Ontology-Based E-learning System: A Graph Neural Network Approach
Wynn, A., Wang, J., Sun, Z., & Shimada, A. (2024). In Companion Proceedings of the 14th Learning Analytics and Knowledge Conference (LAK '24). -
Multiplayer Serious Games Supporting Programming
Learning
Wynn, A., Wang, J., Han, R., & Hsu, T.-C. (2023). Proceedings of the 17th European Conference on Games Based Learning, 721–729. Academic Conferences and Publishing International. -
BETTER: An Automatic feedBack systEm for
supporTing emoTional spEech tRaining
Wynn, A., & Wang, J. (2023). In Artificial Intelligence in Education (pp. 746–752). Springer. -
An AI-Based Feedback Visualisation System for
Speech Training
Wynn, A. T., Wang, J., Umezawa, K., & Cristea, A. I. (2022). In Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium (pp. 510–514). Springer.
Teaching
I have demonstrated for the following undergraduate and master's level modules at Durham University:
- Introduction to Computer Science – MSc Business Analytics (2023–Present)
- Computer Systems – Level 1 BSc/MEng Computer Science (2020–2022)
Conference/Meetings/Workshops Attendance and Presentations
- MultimodalAI'25 Workshop - London (Speaker)
- AIED 2025 - Palermo (Speaker / LBR PC Chair)
- ITS 2025 - Alexandroupolis (Speaker (Online))
- ITiCSE 2024 - Milan (Speaker)
- LAK 2024 - Kyoto (Poster)
- 7th Meet-up of The Turing Interest Group on Knowledge Graphs - London (Participant)
- AIED 2023 - Tokyo (Speaker/Volunteer)
- MultimodalAI'23 Workshop - Sheffield (Speaker)
- MediaLib Workshops - Durham, Kolding, Bochum and Kyoto (Speaker)
- AIED 2022 - Durham (Poster/Volunteer)
- EDM 2022 - Durham (Volunteer)
Education
PhD in Computer Science (AI in Education)
- Durham University | 2022 - 2026
- Research Interests: AI in Education, Automatic Feedback, Speech Processing
MEng Computer Science
- Durham University | 2018 - 2022
- 1st Year (1st Class); 2nd Year (1st Class); 3rd Year (1st Class)
- Advanced Project: An AI-based speech feedback system for second language learners
- Awards: Best Science Communication & Outstanding Achievement in Level 4 Prizes
Community Engagement, Contributions and Other Relevant Experience
- Senior Program Committee Member and Reviewer (Late Breaking Results Track) – AIED 2025, Palermo
- Student Employee of the Year Nominee – Durham University, 2024
- Travel Scholarship Recipient - AIED 2023, Tokyo
- Volunteer Leader – AIED 2022, Durham and AIED 2023, Tokyo
- Research Assistant – Developed the MediaLib official website; analysed user data using Google Analytics (Oct 2022 – Jul 2023)
- Durham Code Club Volunteer – Teaching children to code using Scratch and Python (2019 – 2022)
Contact
University Email:
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Personal Email:
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LinkedIn: linkedin.com/in/adamtwynn