Role
Dr. Pedro Machado holds an MSc in Electrical and Computer Engineering from the University of Coimbra (2012) and a Ph.D. in Computer Science from Nottingham Trent University (2022).
A Senior Lecturer in Computer Science, Dr. Machado combines expertise in neuromorphic engineering, edge computer vision, and bio-inspired computing to pioneer AI-driven solutions for aquatic ecosystems. He leads the EnviroBrain Impact Case Study, is the MSc in Artificial Intelligence Course Leader, and IEEE CertifAIEd lead assessor, AdvanceHE fellow, and the 1st secretary for the IEEE Systematic Innovation Special Interest Group (SISIG).
At the heart of his research is machine perception, developing vision-language models (VLMs) and audio-language models (ALMs) to decode underwater animal behaviour with unprecedented precision. By integrating large language models (LLMs) with neuromorphic sensors and spiking neural networks, his systems can:
- Interpret complex behaviours (e.g., stress, predation, mating) in aquaculture, conservation and wild life,
- Fuse multi-modal data (visual, acoustic, environmental) to predict disease outbreaks or invasive species spread,
- Model biological nervous systems to enhance robotic underwater monitoring.
Dr Machado's work extends to robotics and autonomous systems, where neuromorphic hardware enables real-time analysis in harsh marine environments. The goal: transform how we safeguard endangered species, optimise sustainable aquaculture, and preserve global aquatic biodiversity, before critical thresholds are crossed.
Research areas
Pedro is a member of the Computational Intelligent and Applications group.
Research interests:
Neuromorphic engineering, edge computer vision, bio-inspired computing, robotics and intelligent sensors, retinal cell understanding, biological nervous system modelling, spiking neural networks, robotics and autonomous systems, and neuromorphic hardware, aquaculture, endangered/invasive underwater species.
PhD supervision:
Miss Chloe Boulter (Director of Studies) - 2024 ~ Now
Mr Dennis Monari (Director of Studies) - 2023 ~ Now
Mr Feliciano Domingos (Director of Studies) - 2023 ~ Now
Mr James Edward Brereton (Supervisor) - 2024 ~ Now
Mr Jack Lewton (Supervisor) - 2024 ~ Now
Mr Joseph Origbo (Supervisor) - 2024 ~ Now
Dr Michael Gibbs (Supervisor) - 2022 ~ 2025
PhD Vivas:
Ms. Faiza Guerrache (Internal Examiner) - 2024
Mr John Doherty (External Examiner - University of Ulster) - 2024
Mohammadreza Lalegani Dezaki (Chair) - 2024
Mr James Hall (Chair) - 2024
Mr Victor Okenyi (Chair) - 2024
Income Generation:
- AI-AFS - Funded through InnovateUK (£575,000) (Principal Investigator) - [2025 ~ 2027]
- SAMACT – Bionic Prosthetic Arm Funded by the DAIWA Foundation (£8000) (Principal Investigator) - [2024 ~ 2025]
- 11x Postgraduate Scholarships for the MSc Artificial Intelligence conversion Course funded by the OfS (£110,000) (Principal Investigator) - [2024/2025]
- NeuroLiquidFilter: Advancing Bio-Inspired Filtering with Neuromorphic Intelligence Funded by the Intel Corporation (£20,000 in-kind contribution) (Principal Investigator) - [2024-2025]
- STEM 4.0: Advancing Technology Education through AI-Driven and Adaptive Learning, Funded by the British Council (£29,374) (Co-Investigator) - [2025 - 2026]
- SmartBerry: Artificial Intelligence to Enhance Strawberry Farming In Developing Countries. Funded by Innovate UK grant agreement 10071867 (£245,725), (Co-Investigator) - [2024 - 2026]
- To Create an Innovative AI Approach for Enhancing Data Quality through Data Augmentation in the Finance Sector. Funded by Innovate UK (£235,710), (Co-Investigator) - [2024 - 2027].
- 10x Postgraduate Scholarships for the MSc Artificial Intelligence conversion Course funded by the OfS (£100,000) (Principal Investigator) - [2023/2024]
- Field Companion project, Grant agreement 600359 funded by the InnovateUK (£214,714) (Principal Investigator) [2018-2021].
Active Projects:
- Centopeia cluster initiative [2025 - NOW]- Reimagining computing through sustainability! ♻️ We are aiming to use 100x more recycled computer nodes.
- SAMACT – Bionic Prosthetic Arm Funded by the DAIWA Foundation (£8000) (Principal Investigator) - [2025]
- NeuroLiquidFilter: Advancing Bio-Inspired Filtering with Neuromorphic Intelligence Funded by the Intel Corporation (£20,000 in-kind contribution) (Principal Investigator) - [2024-2025]
- STEM 4.0: Advancing Technology Education through AI-Driven and Adaptive Learning, Funded by the British Council (£29,374) (Co-Investigator) - [2025 - 2026]
- SmartBerry: Artificial Intelligence to Enhance Strawberry Farming In Developing Countries. Funded by Innovate UK (£245,725), (Co-Investigator) - [2024 - 2026]
- To Create an Innovative AI Approach for Enhancing Data Quality through Data Augmentation in the Finance Sector. Funded by Innovate UK (£235,710), (Co-Investigator) - [2024 - 2027].
Past projects:
AQUABRAIN (PI) [March 2024 - July 2024]
Internet of Water (IoW) (PI) [August 2022 - July 2023]
Underwater Plastic Detection (PI) [January 2022 ~ July 2022]
Teaching:
Pedro is the course leader of the MSc AI course and the Independent End Point Assessor for the L7 Degree Apprenticeship at the NTU.
Pedro is currently the Module Leader of
- SOFT40051: Advanced Software Engineering.
- COMP40731: Artificial Cognitive Systems.
- COMP40771: Computational Intelligence
Pedro is currently teaching as Lab Tutor/Supervisor:
- COMP40321: Research Methods | COMP40311: Major Project
- COMP30151: Final Year project
Pedro's teaching experience includes:
- COMP20091: Systems Software (2020 ~ 2025)
- COMP30271: Cognitive Computing (2023-2024)
- SOFT37001: Advanced Analysis and Design (DTS) (2021-2023)
- SOFT27002: Software Engineering (DTS) (2021-2023)
- SOFT27001: Software Design and Implementation (DTS) (2021-2023)
- ISYS30221: Artificial Intelligence (2020 - 2021)
- SOFT20091: Software Design & Imp (2015 - 2021)
- COMP40321: Research Methods | COMP40311: Major Project (2015 - Now)
- COMP10082: Foundations of Comp & Tech (2018)
- COMP30151: Full Year project (2015 - Now)
- ITEC40091: Embedded Systems (2015 and 2016)
- SOFT20101: Info and Database Engineering (2015)
Publications
Journals:
KOBIR, M.I., MACHADO, P., LOTFI, A., HAIDER, D. and IHIANLE, I.K., 2025. Enhancing multi-user activity recognition in an indoor environment with augmented Wi-Fi channel state information and transformer architectures.Sensors, 25 (13): 3955. ISSN 1424-8220
KRISHNA, M.S., MACHADO, P., OTUKA, R.I., YAHAYA, S.W., NEVES DOS SANTOS, F. and IHIANLE, I.K., 2025. Plant leaf disease detection using deep learning: a multi-dataset approach.J, 8 (1): 4. ISSN 2571-8800
ALEX, A.J., BARNES, C.M., MACHADO, P., IHIANLE, I., MARKÓ, G., BENCSIK, M. and BIRD, J.J., 2025. Enhancing pollinator conservation: monitoring of bees through object recognition.Computers and Electronics in Agriculture, 228: 109665. ISSN 0168-1699
DOMINGOS, F.P.F., LOTFI, A., IHIANLE, I.K., KAIWARTYA, O. and MACHADO, P., 2024. Underwater communication systems and their impact on aquatic life—a survey.Electronics, 14 (1): 7. ISSN 2079-9292
IHIANLE, I.K., MACHADO, P., OWA, K., ADAMA, D.A., OTUKA, R. and LOTFI, A., 2024. Minimising redundancy, maximising relevance: HRV feature selection for stress classification.Expert Systems with Applications, 239: 122490. ISSN 0957-4174
FONTES, L., MACHADO, P., VINKEMEIER, D., YAHAYA, S., BIRD, J.J. and IHIANLE, I.K., 2024. Enhancing stress detection: a comprehensive approach through rPPG analysis and deep learning techniques.Sensors, 24 (4): 1096. ISSN 1424-8220
FERREIRA, J.F., PORTUGAL, D., ANDRADA, M.E., MACHADO, P., ROCHA, R.P. and PEIXOTO, P., 2023. Sensing and artificial perception for robots in precision forestry: a survey.Robotics, 12 (5): 139. ISSN 2218-6581
MACHADO, P., FERREIRA, J.F., OIKONOMOU, A. and MCGINNITY, T.M., 2023. NeuroHSMD: neuromorphic hybrid spiking motion detector.ACM Transactions on Reconfigurable Technology and Systems, 16 (3): 36. ISSN 1936-7406
MURRAY-HILL, N., FONTES, L., MACHADO, P. and IHIANLE, I.K., 2023. Secure video streaming using dedicated hardware.Journal of Signal Processing Systems. ISSN 1939-8018
MAGALHÃES, S.C., SANTOS, F.N., MACHADO, P., MOREIRA, A.P. and DIAS, J., 2023. Benchmarking edge computing devices for grape bunches and trunks detection using accelerated object detection single shot multibox deep learning models.Engineering Applications of Artificial Intelligence, 117 (Part A): 105604. ISSN 0952-1976
MACHADO, P., OIKONOMOU, A., FERREIRA, J.F. and MCGINNITY, T.M., 2021. HSMD: an object motion detection algorithm using a Hybrid Spiking Neural Network Architecture.IEEE Access. ISSN 2169-3536
YU, Z., MACHADO, P., ZAHID, A., ABDULGHANI, A.M., DASHTIPOUR, K., HEIDARI, H., IMRAN, M.A. and ABBASI, Q.H., 2020. Energy and performance trade-off optimization in heterogeneous computing via reinforcement learning.Electronics, 9 (11): 1812. ISSN 2079-9292
COSTALAGO-MERUELO, A., MACHADO, P., APPIAH, K., MUJIKA, A., LESKOVSKY, P., ALVAREZ, R., EPELDE, G. and MCGINNITY, T.M., 2018. Emulation of chemical stimulus triggered head movement in the C. elegans nematode.Neurocomputing. ISSN 0925-2312
See the full list in the DBLP database.