Luca Resti
PhD Researcher in Acoustic Signal Processing
Dept. of Computer Science | AudioLab, School of Physics, Engineering and Technology | University of York, UK
Website • Google Scholar • ORCID • LinkedIn • GitHub
Education
PhD in Computer Science | University of York, UK
Sound Interactions in the Metaverse Centre for Doctoral Training (SIM CDT), AudioLab
MSc in Information and Communications Engineering | FAU Erlangen-Nürnberg, Germany
BSc in Engineering of Computing Systems | Politecnico di Milano, Italy
Research Experience
Assistant Researcher - 2026-2027 | Forensic Speech Science Group, University of York
- Project title: Developing a Forensic Methodology for Deepfake Audio Detection
- In collaboration with the Metropolitan Police Serivce (London)
Doctoral Researcher – 2023-2027 | AudioLab, University of York | Dept. of Computer Science, University of York
- Industrial partner: Electronic Arts (EA) SEED
- Developing objective audio-visual signal quality assessment methodologies for interactive multimedia applications.
- Focused on acoustic scene complexity metrics (SASE, MAV-C) and non-intrusive diffuseness estimation for ambisonic signals (SHADE).
Research Associate – 2022-2023 | Fraunhofer Institute for Integrated Circuits IIS
- Contributed to the development of the next-generation MPEG-H audio format.
- Researched intelligibility metrics to predict preferred speech-to-background loudness differences in source-separated audio.
Research Intern – 2021 | International Audio Laboratories Erlangen
- Investigated the noise shaping properties of a novel perceptual audio codec.
- Supervisor: Prof. Bernd Edler
Grants & Funding
EPSRC Impact Acceleration Account (IAA) Grant – 2026 | Grant Ref: EP/X525856/1
Role: Principal Investigator
Selected Publications
- Resti, L. et al. "Spherical Acoustic Spatial Entropy: Predicting Acoustic Scene Complexity in Virtual Environments." IEEE Open Journal of Signal Processing (OJ-SP), 2026.
- Resti, L. et al. "MAV-C: A Framework for the Joint Objective Estimation of Audio-Visual Complexity in Immersive Virtual Environments." AES AVARIG 2026: Audio for Virtual and Augmented Reality and Immersive Games · Paper 494 · June 2026.
- Resti, L. et al. "An Information-Theoretic Measure for the Diffuseness and Complexity of Ambisonic Signals" IEEE Transactions on Audio, Speech, and Language Processing (TASLP) (Submitted).
- Heritage, B., Resti, L. et al. "XSQ-AST: An Explainable Audio Spectrogram Transformer Framework for Localising Synthetic Speech Artifacts." arXiv preprint arXiv:2609.24770, 2026 (Submitted to ICASSP 2027).
- Resti, L. et al. "Predicting Preferred Dialogue-to-Background Loudness Difference in Dialogue-Separated Audio." 2023 15th International Conference on Quality of Multimedia Experience (QoMEX).
Open-Source Software
- synth-speech-eval: Public tool for localizing quality artifacts in synthetic speech using explainable audio transformers.
University Teaching
Qualification: Associate Fellow (AFHEA) – 2025 | AdvanceHE (certificate)
Guest Lecturer – 2026 | University of York, UK
- Intelligent Systems: Machine Learning and Optimisation (Dept. of Computer Science)
Graduate Teaching Assistant – 2023-2026 | University of York, UK
- Mathematics (for engineers, School of Physics, Engineering and Technology)
- Theory 1 - Mathematical Foundations of Computer Science (Dept. of Computer Science)
- Professional and Academic Development (Dept. of Computer Science)
- Intelligent Systems: Machine Learning and Optimisation (Dept. of Computer Science)
Outreach
Coming soon
Extracurriculars
Postgraduate Researcher Representative – 2024-2026 | York Branch Executive, University and College Union (UCU)
Local Chair - 2026 | ACM CHI PLAY 2026
Guest Editor - 2023 | IEEE Communications Society, MMTC Communications Frontiers, Special Issue on Quality of Experience in the Metaverse
Awards
Siemens ICT Award for Excellent Master's Degrees | FAU Erlangen, Nuremberg, Germany (certificate)