Senior Lecturer in Creative AI

  • Academic
  • Creative Education
Dr Ronald Mo

Dr Ronald Mo is a Senior Lecturer in Creative AI at UCA. His research focuses on Machine Learning, Audio Signal Processing, Singing Voice Analysis, and Generative AI. He works closely with industry and academic partners to develop innovative AI solutions and support student success in Higher Education.

Bio

Ron is an experienced academic whose work brings together education, research, and industry in equal measure. He collaborates closely with academic and professional services teams and industry partners to deliver high-quality learning experiences and support student success, with involvement in curriculum design and student recruitment.

He holds a PhD in Computer Science and Engineering from the Hong Kong University of Science and Technology (2017), where his doctoral research explored the relationship between music and emotion. This work was presented at the International Computer Music Conference and published in the Journal of the Audio Engineering Society. Before joining UCA, he held senior research roles at Tencent Music Entertainment and Huawei Hong Kong, as well as served as a Lecturer in Computer Science and Programme Leader for the BSc (Hons) Game Development at the University of Sunderland. He has accumulated around 20 peer-reviewed publications across his career.

His research sits at the intersection of computing and music, a field he approaches not only as a scientist but also as a professional musician and music producer. His recent work centers on developing intelligent systems that can analyze and interpret human voice and singing performance to better understand vocal characteristics, support music education, and advance human-computer interaction. He has also contributed to several Innovate UK-funded projects and other collaborations that bring scientific ideas into real-world use.

For Ron, education is about helping students develop not just the skills to use technology, but the analytical thinking to question it and the confidence to apply it in ways that matter. Whether working with undergraduate or postgraduate students, he places equal emphasis on rigorous learning and personal development, preparing students to navigate a rapidly evolving AI-driven world while ensuring that every student, regardless of background or experience, feels genuinely supported and challenged to reach their potential.

 

Research statement

Ron’s research sits at the intersection of computing and music, with a focus on Machine Learning and Music Information Retrieval. He is particularly interested in analyzing human music performance using signal processing and Deep Learning approaches. This work not only helps understand vocal characteristics and expressive nuances, but also opens avenues into broader Computer Science and HCI challenges such as Deepfake Voice Detection and music education for students with SEN. Ron also collaborates with academic and industry partners to translate findings into practical tools that advance understanding of human expression and broaden access to music education for underserved communities.

Research supervision

Ron welcomes enquiries from prospective postgraduate researchers with interests in AI and Music. He is particularly interested in supervising projects related to Music Information Retrieval and AI-assisted music education. Prospective students are encouraged to reach out with a brief outline of their research interests.

Professional Membership, Affiliation and Consultancy

  • Member of IEEE
  • Fellow of Advance HE
  • Best Poster Runners-Up, the 54th Voice Foundation Annual Symposium, Philadelphia, USA (May 28th – June 1st, 2025).
  • Best Presentation Award, the 8th IEEE International Conference on Information Communication and Signal Processing (IEEE ICICSP 2025), Xi’an, China (September 12th – 14th, 2025).

Grants

  • AI-assisted Vocal Coach, Accelerated Knowledge Transfer (AKT), Innovate UK, UK (Apr 2024 – Aug 2024).
  • Market Entry Strategy and Prototype Development for Vocal Health Solutions in the Education Sector, Feasibility Studies for AI Solutions: Series 2, Innovate UK, UK (Sep 2024 – Mar 2025).
  • Market Entry Strategy and Prototype Development for Vocal Health Solutions in the Education Sector, DCMS Create Growth Programme Competition 3, Innovate UK, UK (Oct 2024 – Mar 2025).
  • CASBI AI: Taking Care of Vocal Health with AI Innovation, AI Solutions to Develop AI Competencies in Key Sectors, Innovate UK, UK (May 2025 – Feb 2026).
Dr Ronald Mo

Media enquiries

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