About

Me after climbing most of Akrafjall

I am an audio software engineer and researcher from the UK, with a PhD in Artificial Intelligence and Music. With over a decade of experience spanning DSP algorithm development, embedded systems, and pioneering work in AI/ML for audio, I am passionate about translating complex signal processing and machine learning concepts into innovative real-world applications for the creative industries and beyond.

My background includes bringing numerous products in professional and consumer electronics to fruition, from active noise-cancelling headphones and video encoders to guitar/bass amplifiers. My recent research in edge AI, including the development of the MEML framework for on-device training, has deepened my focus on the potential and challenges of deploying small, efficient AI models for real-time signal manipulation and gesture recognition. The HITar, an AI-augmented acoustic guitar and international award winner, exemplifies my commitment to designing responsive, intimate, and cutting-edge musical interactions. I thrive on leveraging deep technical expertise to create impactful and engaging user experiences.

💼 Recent Work History

June 2024 Present (end Oct 2025)	University of Sussex – Brighton, UK Research Fellow in Musical Instrument Design and Creative Machine Learning
	Research Musically Embodied Machine Learning and train AI models through musical interfaces in real time on RP2350 and XMOS Xcore.ai embedded platforms. Create meMLP, an edge AI library with support for RL and on-device training.

September 2023 Present (end Jul 2025)	Queen Mary University of London – London, UK Research Assistant – Impact Fund grant “HITar”
	Spearhead commercialisation of the HITar: protect IP, devise business model and sales funnel, and drive customer engagement. Exhibit the HITar at trade shows (Music China 2023, NAMM 2024).

September 2017 December 2019	ams AG (Semiconductors and sensors) – Stokenchurch, UK Digital Signal Processor Software Engineer
	Implement adaptive hybrid Active Noise Cancellation (ANC) algorithms. Develop Automatic Leakage Compensation on the proprietary AS3460 chip. Drive product development from research simulation to finished product within one year, collaborating closely with acoustical engineering.

March 2015 September 2017	Blackstar Amplification Ltd – Northampton, UK DSP Engineer
	Conduct R&D of non-linear digital audio processing algorithms. Bring impactful products to market: ID:Core digital amps: polyphonic octaver, looper, chorus/flanger, envelope filter. Venue MkII hybrid amps: reverb, power amp simulation. Unity bass amps: completely new design, bass distortion simulator, feedback compressor.

October 2013 March 2015	ITDev Ltd – Southampton, UK Graduate Software Engineer
	Develop software projects using PHP, Python, JS, Perl, and embedded C. Serve as SCRUM master. Embedded development on video encoder systems.

🛠️ Skills and Achievements

Languages:

C++ C Python ARM Assembly

Javascript PHP Perl

Ruby Rust Coffeescript

Hardware platforms:

ARM Cortex-M XMOS x86

Xtensa HiFi3 ARM Cortex-A SHARC

AI platforms

Pytorch Torchlib

Keras ONNX TFLite-micro

DSP Concepts:
- Fixed-point signal chains
- Filtered-X LMS
- Optimised fixed-point STFT
- Multi-rate processing
Audio Effects:
- Pitch shifting, reverb, fuzz
- Model analogue gain stages
- Feedback/feed-forward compressors
- Complex real-time chains on constrained DSPs
Toolchains & Testing:
- Unit testing: microunit, catch2, unity
- Continuous integration: Jenkins
- Automated DSP testing with CI pipelines
- Native C++ &leftrightarrow; Python integration via Boost::Python, PyBind11
ML/AI Concepts:
- ML from scratch in embedded C++: backpropagation, optimisation
- CNNs, CRNNs, VAEs in embedded real-time AI
- Reinforcement learning: deep deterministic policy gradient (DDPG)
- Multi-threaded deployment into VST, Max/MSP, ARM-based edge platforms
Acoustics:
- FF/FB noise cancellation
- Room modelling (FDTD, FEM, Digital Waveguide)
- Spatial hearing and psychoacoustics
- Acoustic simulation: MATLAB, CATT-Acoustic, COMSOL

🎓 Education and Qualifications

PhD Artificial Intelligence and Music

Queen Mary University of London, Centre for Digital Music September 2019 – April 2025

Thesis: “Augmenting an acoustic guitar for percussive fingerstyle”

MSc Sound and Vibration Studies (with Merit)

University of Southampton, Institute of Sound and Vibration Research September 2012 – September 2013

Dissertation: Refining an FDTD acoustic model for room auralisation with OPSODIS Ltd

BSc Informatica Musicale (Musical Information Technology)

Università degli Studi di Milano September 2009 – September 2012

Grade: 110/110 cum laude
Dissertation: Further evidences of the contribution of the ear canal to directional hearing

🏊 Other Interests

Extrovert and excellent communicator, confident in public speaking.
Keen cyclist, swimmer, runner; passionate cook.

📚 Publications

Martelloni, A. and Kiefer, C., 2024. Musically Embedded Machine Learning (MEML) Demo. In CHIME 2024

Kiefer, C. and Martelloni, A., 2024. Musically Embedded Machine Learning Workshop. In CHIME 2024

Armitage, J., Shepardson, V., Privato, N., Pelinski, T., Benito Temprano, A.L., Wolstanholme, L., Martelloni, A., Caspe, F.S., Reed, C.N., Skach, S. and Diaz, R., 2023, August. Agential Instruments Design Workshop. 4th International Conference on AI and Music Creativity (AIMC).

Martelloni, A., McPherson, A. and Barthet, M., 2023, November. Real-Time Percussive Technique Recognition and Embedding Learning for the Acoustic Guitar. In ISMIR 2023

Reed, C.N., Nordmoen, C., Martelloni, A., Lepri, G., Robson, N., Zayas-Garin, E., Cotton, K. and McPherson, A., 2022, June. Exploring experiences with new musical instruments through micro-phenomenology. In NIME 2022.

Martelloni, A., McPherson, A. and Barthet, M., 2021, April. Guitar augmentation for Percussive Fingerstyle: Combining self-reflexive practice and user-centred design. In NIME 2021.

Martelloni, A., McPherson, A. and Barthet, M., 2020. Percussive Fingerstyle Guitar through the Lens of NIME: an Interview Study. In NIME 2020.

Martelloni, A., Mauro, D.A. and Mancuso, A., 2013, June. Further evidences of the contribution of the ear canal to directional hearing: design of a compensation filter. In Proceedings of Meetings on Acoustics (Vol. 19, No. 1). AIP Publishing.

Andrea Martelloni