| AIM CDT Cohorts |
|---|
| First Cohort - 2019-2024 |
| Second Cohort - 2020-2025 |
| Third Cohort - 2021-2026 |
| Fourth Cohort - 2022-2027 |
| Fifth Cohort - 2023-2028 |
| Sixth Cohort - 2024-2029 |
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 | Perception and analysis of 20th and 21st century popular music |
 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 |
 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 |
 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 | Deep Learning for Time-varying Audio and Parameter 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 |
 Aditya Bhattacharjee | Self-supervision in Audio Fingerprinting |
Fifth AIM cohort students (2023-2028):
| PhD Student | Project title |
|---|---|
 Bradley Aldous | Advancing music generation via accelerated deep learning |
 Keshav Bhandari | Neuro-Symbolic Automated Music Composition |
 Louis Bradshaw | Neuro-symbolic music models |
 Julien Guinot | Beyond Supervised Learning for Musical Audio (in collaboration with Universal Music Group) |
 Zixun (Nicolas) Guo | Towards Tonality-Aware Music Understanding: Modeling Complex Tonal Harmony |
 Adam He | Neuro-evolved Heuristics for Meta-composition (in collaboration with DAACI) |
 Gregor Meehan | Representation learning for musical audio using graph neural network-based recommender engines |
 Marco Pasini | Fast and Controllable Music Generation (in collaboration with Sony SCL) |
 Christos Plachouras | Deep learning for low-resource music |
 Pablo Tablas De Paula | Machine Learning of Physical Models |
 Haokun Tian | Timbre Tools for the Digital Instrument Maker |
 Qing Wang | Multi-modal Learning for Music Understanding |
 Yifan Xie | Film score composer AI assistant: generating expressive mockups (in collaboration with Spitfire Audio) |
 Ece Yurdakul | Emotion-based Personalised Music Recommendation (in collaboration with Deezer) |
 Farida Yusuf | Neural computing for auditory object analysis |
 Qiaoxi Zhang | Multimodal AI for musical collaboration in immersive environments (in collaboration with PatchXR) |
 Shuoyang Zheng | Explainability of AI Music Generation |
 Xavi D'Cruz | Multimodal techniques for the control of procedural audio |
Sixth AIM cohort students (2024-2029):
| PhD Student | Project title |
|---|---|
 Jinwen Zhou | Combining Deep Learning and Music Theory |
 Minhui Lu | Applications of deep learning for improved synthesis of engine sounds |
 Shangxuan Luo | Adaptive Music Generation for Video Game |
 Yorgos Velissaridis | Smart EQ: Personalizing Audio with Context-aware AI using Listener Preferences and Psychological Factors |