Jingjing Tang

About Me

I am currently in my final 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 expressive piano performances. My academic interests span a range of topics, including expressive music generation, music synthesis, music performance analysis, music information retrieval, and machine learning for music.

Education

• [Sep. 2020 - Now] Ph.D. Student in Artificial Intelligence and Music (AIM) program, at Queen Mary University of London
• [Sep. 2016 - May 2020] Bachelor of Science in Statistics (Data Science Branch), at Chinese Univeristy of Hong Kong, Shenzhen

Research Interests

• Automated Music Generation: controllable music generation, music style transfer, expressive performance rendering and synthesis, music genration evaluation
• Music Information Retrieval: music performer/composer/style classification, music performance analysis, music transcription, music alignment algorithms
• Machine Learning: deep generative models, contrastive learning, transfer learning, language models for music, self-supervised learning

News

• [Feb. 2026] Our paper “Visualising Pianists’ Touch: Transcribing Expressive Piano Performance from Audio to Piano Key Motion” by Jingjing Tang, Shinichi Furuya, Hayato Nishioka, Momoko Shioki, Geraint Wiggins, George Fazekas, and Vincent K.M. Cheung gets accepted by CHI 2026, more details will be announced soon.
• [Aug. 2025] Our late breaking demos will be presented at AIMLA 2025 and ISMIR 2025:
  • “S2H2S: Modelling Expressive Piano Performances via Continuous Piano Key Motion Signals” by Jingjing Tang, Shinichi Furuya, George Fazekas, and Vincent K.M. Cheung at ISMIR 2025
  • “Towards Intelligent Music Education: Score-Informed Transcription and Performance Assessment” by Aikaterini Maria Primenta, Jackson Loth, Jingjing Tang, Xavier Riley, Simon Dixon, and Emmanouil Benetos at AIMLA 2025 and ISMIR 2025
  • “Transformer-Based Sustain Pedal Reconstruction for Expressive Piano Performance MIDI” by Wenhao Liu, George Fazekas, and Jingjing Tang at AIMLA 2025.
• [Jun. 2025] Our paper “MIDI-VALLE: Improving Expressive Piano Performance Synthesis Through Neural Codec Language Modelling” gets accepted by ISMIR 2025, more details will be announced soon.
• [Apr. 2025] I started my internship at Sony CSL, Japan.
• [Dec. 2024] Our paper “Towards An Integrated Approach for Expressive Piano Performance Synthesis from Music Scores” gets accepted by ICASSP 2025.
• [Nov. 2024] Our paper “EME33: A Dataset of Classical Piano Performances Guided by Expressive Markings with Application in Music Rendering” gets accepted by AIMG 2024 Workshop, at IEEE Big Data 2024.
• [Sep. 2024] I transfer to writing-stage now!
• [Feb. 2024] I started my research internship under supervision of Prof. Yamagishi Junichi at National Institute of Informatics.
• [Nov. 2023] Our papers about reconstructing human expressiveness in piano performances and a dataset of jazz variations for jazz standards were presented in the oral sessions at CMMR 2023, Japan.
• [Oct. 2023] Our paper about a pianist identification system was presented in the poster session at IS2 2023, Italy.
• [Dec. 2022] We released a large-scale dataset of the automatic transcribed expressive piano performances in ISMIR 2022, India.

Publications

Services

Reviewers

• IEEE International Joint Conference on Neural Networks (IJCNN), 2025
• International Society for Music Information Retrieval Conference (ISMIR), 2023-2025
• IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024-2025
• AES International Conference on Artificial Intelligence and Machine Learning for Audio (AIMLA), 2025
• EURASIP Journal on Audio, Speech, and Music Processing
• Transactions of the International Society for Music Information Retrieval (TISMIR)

Teaching

• Teaching Fellow: ECS607U - Data Mining 2024-2025 Semester A
• Demonstrator: Research Methods and Responsible Innovation (ECS7007P) 2024-2025 Semester A
• Demonstrator: Research Methods (ECS7029P) 2024-2025 Semester A
• Demonstrator: ECS607U - Data Mining 2022-2023 Semester A
• Demonstrator: ECS766P - Data Mining 2022-2023 Semester A
• Supervisor: EECS MSc Project 2022-23, for 10 students
• Supervisor: EECS MSc Project 2024-25, for 5 students

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