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Jingjing Tang

Ph.D. Student
Artificial Intelligence and Music Program, Center for Digital Music, Queen Mary University of London
jingjing.tang (at) qmul.ac.uk


About Me

I am currently in my fourth year as a Ph.D. student in Artificial Intelligence and Music (AIM) program, at the C4DM, QMUL, supervised by Prof. George Fazekas and Prof. Geraint Wiggins. My research is centered around applying deep learning techniques to generate controllable, expressive piano performances, with a specific emphasis on creating pianist-style conditioned outputs. My academic interests span a range of topics, including controllable music generation, modeling of expressive performances, classification of performers, analysis of music performances, and related areas.

Education

Research Interests

News

Publications

  1. ICASSP
    Jingjing Tang, Erica Cooper, Xin Wang, Junichi Yamagishi, George Fazekas
    The 50th IEEE International Conference on Acoustics, Speech, and Signal Processing, 2025 Hyderabad

  2. IEEE Big Data
    Tzu-Ching Hung, Jingjing Tang, Kit Armstrong, Yi-Cheng Lin, Yi-Wen Liu
    The 2nd Workshop on AI Music Generation with AI Music Competition, IEEE Big Data, 2024 Washington DC

  3. CMMR
    Jingjing Tang, Geraint Wiggins, George Fazekas
    The 16th International Symposium on Computer Music Multidisciplinary Research, 2023 Tokyo

  4. CMMR
    Eleanor Row, Jingjing Tang, George Fazekas
    The 16th International Symposium on Computer Music Multidisciplinary Research, 2023 Tokyo

  5. IS2
    Jingjing Tang, Geraint Wiggins, George Fazekas
    The 4th International Symposium on the Internet of Sounds, 2023 Pisa

  6. ISMIR
    Huan Zhang*, Jingjing Tang*, Syed Rafee*, Simon Dixon, George Fazekas (*Co-Primary Author)
    The 23rd International Society for Music Information Retrieval Conference, 2022 India

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Teaching

Demonstration & Supervision


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