Dr Gaetano Di Caterina

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Electronic and Electrical Engineering

Personal statement

I am an academic in the Department of Electronic and Electrical Engineering, and Fellow of the HEA. In particular, I am the Leonardo Lecturer on a joint programme (2023-2027) between Strathclyde and the global security company Leonardo UK Ltd.

Having completed a PhD in video analytics for smart surveillance, in the Centre for Signal & Image Processing (CeSIP), within the EEE Department at Strathclyde, my background and areas of expertise reside in signal, image and video processing. My current research interests are Neuromorphic Engineering, Machine Learning and Deep Learning, Digital Signal Processing and Embedded Systems.

I am Director of the Neuromorphic Sensor Signal Processing Lab, within the CeSIP group, supervising PhD students and PostDoc researchers working on various research projects and applications within these broad research areas.

I am Course Director of the MSc in Machine Learning and Deep Learning, which is a joint MSc programme between the EEE Department and the Computer and Information Sciences Department at Strathclyde.

And I am also Adviser of Studies for Year 1 of the undergraduate degree programme Computer and Electronic Systems, joint between EEE and CIS Departments.

Expertise

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Prize And Awards

Best Paper Award: Recipient; 27/8/2022
IEEE Brain Data Bank Challenges and Competitions: Recipient; 31/10/2017

More prizes and awards

Publications

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Publications

Resonate-and-fire neurons meet EMG : enhancing gesture classification with spiking neural networks: Manna Davide Liberato, Bihl Trevor, Di Caterina Gaetano; 2026 IEEE International Conference on Acoustics, Speech, and Signal Processing (2026)
A biopsy/non-biopsy approach to voice disorder classification using deep learning: Conway Frank, Perry Ross, Di Caterina Gaetano, Cohen Wendy, Wynne David M; 2025 IEEE Symposium on Computers and Communications (ISCC) IEEE International Conference on ICT Solutions for eHealth IEEE Symposium on Computers and Communications (ISCC) (2026); https://doi.org/10.1109/ISCC65549.2025.11325982
Addressing the lack of neuromorphic data in low SNR scenarios: Perry Ross, Di Caterina Gaetano, Bihl Trevor J, Combs Kara; Hawaii International Conference on System Sciences (2026)
Encoding time series on an FPGA, with an efficient Izhikevich neuron implementation: Borrill Thomas, Crockett Louise, Thomas Kevin, Di Caterina Gaetano; Hawaii International Conference on System Sciences (2026)
Editorial : Theoretical advances and practical applications of spiking neural networks, Volume II: Di Caterina Gaetano, Zhang Malu, Liu Jundong; Frontiers in Neuroscience (2026)
Advancing utility pole and sign detection through deep learning: Dickinson Carl, Di Caterina Gaetano; 36th British Machine Vision Conference 2025 (2025)

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Research

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Research Interests

Neuromorphic Engineering and Technologies
Machine Learning and Deep Learning
Image and Video Processing
Video Analytics for Surveillance
EMG Signal Processing
Speech Processing
Medical Image Processing
DSP Embedded Systems

Professional Activities

Strategic Themes: Applied AI Workshop: Participant; 17/1/2025
Ian O'Neil: Host; 9/12/2024
Strathclyde researchers seek diagnostic tool for respiratory condition: Contributor; 26/11/2018
Faculty Robotics and Automation Users Group Discussion: Participant; 10/10/2017

More professional activities

Projects

Neuromorphic sensor signal processing for spatio-temporal tracking in low SNR | Musulin, Sven: Di Caterina, Gaetano (Principal Investigator) Clemente, Carmine (Co-investigator) Musulin, Sven (Research Co-investigator); 01-Jan-2025 - 01-Jan-2029
Neuromorphic processing applied to adaptive control for sensor performance optimisation: Di Caterina, Gaetano (Principal Investigator); 01-Jan-2025 - 31-Jan-2029
UKRI Centre for Neuromorphic Technologies - Photonics focus - Aston lead - Period 1: Hurtado, Antonio (Principal Investigator) Di Caterina, Gaetano (Co-investigator) Porte Parera, Javier (Co-investigator); 01-Jan-2025 - 31-Jan-2029
Leonardo Lab Phase 0 Activity: Di Caterina, Gaetano (Principal Investigator) Clemente, Carmine (Co-investigator); 01-Jan-2025 - 30-Jan-2025
Neuromorphic Sensor Fusion for Under Water Object Detection: Patil, Chaitanya (Principal Investigator) Di Caterina, Gaetano (Co-investigator); The project aims to develop a protocol of multimodal data collection through neuromorphic sensors for underwater object detection.
The underwater object detection is very tricky phenomenon due to variability of environmental
changes like wave motion, salinity as well as visibility under water. Various sensors with different
ranges and properties can be deployed to overcome the adverse environmental conditions for object detection. However, increasing number of sensors increases the data processing power, noise and uncertainty in the process rendering the data fusion from these sensors difficult. The proven neuromorphic methods introduce a paradigm shift in handling these sensor uncertainties through sensor fusion and increasing the autonomy of the data management and decision making within the operating envelope of all the sensors used for the object detection task.; 01-Jan-2024 - 01-Jan-2025
Neuromorphic sensor signal processing for spatio-temporal tracking in low SNR: Di Caterina, Gaetano (Principal Investigator); 01-Jan-2023 - 31-Jan-2026