First AIM cohort students (2019-2024):
PhD Student | Project title |
---|---|
![]() Adan Benito | Beyond the fret: gesture analysis on fretted instruments and its applications to instrument augmentation |
![]() Berker Banar | Towards Composing Contemporary Classical Music using Generative Deep Learning |
![]() Marco Comunità | Machine learning applied to sound synthesis models |
![]() David Foster | Modelling the Creative Process of Jazz Improvisation |
![]() Lele Liu | Automatic music transcription with end-to-end deep neural networks |
![]() Ilaria Manco | Deep learning and multi-modal models for the music industry in collaboration with Universal Music Group |
![]() Andrea Martelloni | Real-Time Gesture Classification on an Augmented Acoustic Guitar using Deep Learning to Improve Extended-Range and Percussive Solo Playing |
![]() Mary Pilataki-Manika | Polyphonic Music Transcription using Deep Learning in collaboration with Apple |
![]() Saurjya Sarkar | New perspectives in instrument-based audio source separation |
![]() Pedro Sarmento | Guitar-Oriented Neural Music Generation in Symbolic Format in collaboration with Holonic Systems Oy. |
![]() Elona Shatri | Optical music recognition using deep learning in collaboration with Steinberg Media Technologies GmbH |
![]() Cyrus Vahidi | Perceptual end to end learning for music understanding in collaboration with MUSIC Tribe Brands UK Limited |
Second AIM cohort students (2020-2025):
PhD Student | Project title |
---|---|
![]() Corey Ford | Artificial Intelligence for Supporting Musical Creativity and Engagement in Child-Computer Interaction |
![]() Max Graf | AI-Based Musical Co-Creation in Extended Realities: PERFORM-AI |
Madeline Hamilton | Improving AI-generated Music with Pleasure Models |
![]() Benjamin Hayes | Perceptually motivated deep learning approaches to creative sound synthesis |
![]() Jiawen Huang | Lyrics Alignment For Polyphonic Music |
![]() Harnick Khera | Informed source separation for multi-mic production in collaboration with BBC |
![]() Yin-Jyun Luo | Industry-scale Machine Listening for Music and Audio Data in collaboration with Spotify |
![]() Luca Marinelli | Gender-coded sound: A multimodal data-driven analysis of gender encoding strategies in sound and music for advertising |
![]() Xavier Riley | Digging Deeper - expanding the “Dig That Lick” corpus with new sources and techniques |
![]() Eleanor Row | Automatic micro-composition for professional/novice composers using generative models as creativity support tools |
![]() Shubhr Singh | Audio Applications of Novel Mathematical Methods in Deep Learning |
![]() Christian Steinmetz | Deep learning for high-fidelity audio and music production |
![]() Jingjing Tang | End-to-End System Design for Music Style Transfer with Neural Networks |
![]() Lewis Wolstanholme | Real-time instrument transformation and augmentation with deep learning |
![]() Yixiao Zhang | Machine Learning Methods for Artificial Musicality in collaboration with Apple |
Third AIM cohort students (2021-2026):
PhD Student | Project title |
---|---|
![]() Katarzyna Adamska | Predicting hit songs: multimodal and data-driven approach |
![]() Sara Cardinale | Character-based adaptive generative music for film and video games using Deep Learning and Hidden Markov Models |
![]() Franco Caspe | AI-assisted FM synthesis for sound design and control mapping |
Ruby Crocker | Time-based mood recognition in film music |
![]() Carlos De La Vega Martin | Neural Drum Synthesis |
Bleiz MacSen Del Sette | The Sound of Care: researching the use of deep learning and sonification for the daily support of people with Chronic Pain |
![]() Rodrigo Mauricio Diaz Fernandez | Hybrid Neural Methods for Sound Synthesis |
![]() Andrew Edwards | Computational Models for Jazz Piano: Transcription, Analysis, and Generative Modeling |
![]() Oluremi Samuel Oladotun Falawo | Embodiment in Intelligent Musical Systems |
![]() Mariam Fayaz Torshizi | Music mood modelling using Knowledge graphs and Graph Neural Nets |
![]() Yazhou Li | Virtual Placement of Objects in Acoustic Scenes in collaboration with Sonos |
![]() Jackson Loth | Time to vibe together: cloud-based guitar and intelligent agent in collaboration with Hyvibe |
![]() Teresa Pelinski Ramos | Sensor mesh as performance interface in collaboration with Bela |
![]() Soumya Sai Vanka | Smart Channel strip using Neural audio processing in collaboration with Steinberg |
![]() Chris Winnard | Music Interestingness in the Brain |
![]() Xiaowan Yi | Composition-aware music recommendation system for music production in collaboration with Focusrite |
![]() Huan Zhang | Computational Modeling of Expressive Piano Performance |
Fourth AIM cohort students (2022-2027):
PhD Student | Project title |
---|---|
![]() James Bolt | Intelligent audio and music editing with deep learning |
![]() Carey Bunks | Cover Song Identification in collaboration with Apple |
![]() Adam Garrow | A computational model of music cognition using statistical learning of structures |
![]() Ashley Noel-Hirst | Latent Spaces for Human-AI music generation |
![]() Louise Thorpe | Using Signal-informed Source Separation (SISS) principles to improve instrument separation from legacy recordings |
Alexander Williams | User-driven deep music generation in digital audio workstations in collaboration with Sony |
![]() Yinghao Ma | Self-supervision in machine listening in collaboration with Bytedance |
![]() Jordan Shier | Real-time timbral mapping for synthesized percussive performance in collaboration with Ableton |
![]() David Südholt | Machine learning of physical models for voice synthesis in collaboration with Nemisindo |
![]() Tyler McIntosh | Expressive Performance Rendering for Music Generation Systems in collaboration with DAACI |
![]() Christopher Mitcheltree | Representation Learning for Audio Production Style and Modulations |
![]() Ioannis Vasilakis | Active learning for interactive music transcription |
![]() Chin-Yun Yu | Neural audio synthesis with expressiveness control |
![]() Ningzhi Wang | Generative models for music audio representation and understanding in collaboration with Spotify |