Role
Dr. Pedro Machado holds an integrated MSc in Electrical and Computer Engineering from the University of Coimbra (2012) - Portugal and a Ph.D. in Computer Science from Nottingham Trent University (2022) - UK. Dr. Machado is a Senior Lecturer in Computer Science whose work spans neuromorphic computing, spiking neural networks, and intelligent systems. Research activities focus on the design of cognitive and distributed AI architectures capable of operating reliably in complex and data-rich environments. Academic leadership includes directing the EnviroBrain Impact Case Study, serving as MSc Artificial Intelligence Course Leader, acting as an IEEE CertifAIEd Lead Assessor, holding Fellowship of AdvanceHE, and contributing as First Secretary of the IEEE Systematic Innovation Special Interest Group (SISIG).
Research on machine perception and cognitive systems that integrate neuromorphic computing with modern AI pipelines. Development of intelligent systems combines spiking neural networks, agentic AI, and multi-agent systems to create adaptive architectures capable of interpreting complex environmental signals. Work also incorporates MLOps practices and distributed systems to ensure scalable deployment of AI models across edge and cloud infrastructures. Methodological contributions focus on systems that coordinate multiple intelligent agents and sensors to support collective intelligence. Integration of visual, acoustic, and environmental data streams enables AI systems to detect behavioural patterns, anticipate environmental change, and support autonomous monitoring platforms. Such architectures enable real-time analysis and decision-making in dynamic ecosystems.
Applications extend to autonomous robotics, environmental monitoring, and large-scale sensing infrastructures where neuromorphic and distributed AI approaches enable resilient operation in challenging environments. Long-term objectives include advancing intelligent systems capable of collaborative perception and decision-making, supporting sustainable ecosystem management and next-generation AI-driven monitoring technologies.
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:
Mr Feliciano Domingos (Director of Studies) - Elevating Internet of Things Devices for Underwater Communication Applications Employing Highly-Efficient Artificial Cognitive Devices –October2023 ~ Now [Writing stage]
Mr Dennis Monari (Director of Studies) –Pioneering Biodiversity Monitoring: Harnessing AI/ML with a Cognitive Sensor Network and Internet of Water (IoW) Devices – February 2023 ~ Now
Miss Chloe Boulter (Director of Studies) - Real-Time Stress and Anxiety Detection using Spiking Neural Networks (SNNs) for Efficient Healthcare Expenditures Reduction - October2024 ~ Now
Mr Jack Lewton (Co-Supervisor) – Using AI to monitor captive animal welfare. October 2024 ~ Now
Mr James Brereton (Co-Supervisor) – Wildlife Cryoconservation: Development of biobanking strategies to halt and reverse biodiversity loss. October 2024 ~ Now [Writing stage]
Mr JOSEPH ORIGBO - An interdisciplinary and inclusive co-designed solution for an autonomous musculoskeletal surgical platform. October 2024 ~ Now
Mr Daniel Shabanianalavi - Advancing Health and Well-Being with Smart Sensing and Computational Intelligence. July 2025~ Now
Mr Anthony Nonso Chimezie - Leveraging Artificial Intelligence and Process Mining to Enhance Governance and Compliance in Healthcare Sector: A Predictive and Explainable Approach. April 2026 ~ NOW
PhD Completions:
Dr Michael Gibbs (Co-Supervisor) – AI at the Edge for robotic development and applications. October 2022~May 2025
PhD Vivas:
Chair
- Dr Abha (2025)
- Dr Omoyemi Rebecca Ojo (2025)
- Dr Mohammadreza Lalegani Dezaki (2024)
- Dr James Hall (2024)
- Dr Victor Okenyi (2024)
Internal Examiner
- Dr Faiza Guerrache (2024)
External Examiner
- Dr Dominique Sanderson (Brunel University) (2025)
- Dr John Doherty (University of Ulster) (2024)
MPhil Vivas:
Mr Connor Farrell (Chair) - 2025
Income Generation:
- RehabAI: Guiding Therapy with Data-Driven Insights - Funded through EPSRC (Co-Investigator) (£49,000)- [2026 ~ 2027]
- 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:
- RehabAI: Guiding Therapy with Data-Driven Insights - Funded through EPSRC (Co-Investigator) (£49,000)- [2026 ~ 2027]
- 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]
- 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:
- SmartBerry: Artificial Intelligence to Enhance Strawberry Farming In Developing Countries. Funded by Innovate UK (£245,725), (Co-Investigator) - [2024 ~ 2026]
- SAMACT – Bionic Prosthetic Arm Funded by the DAIWA Foundation (£8000) (Principal Investigator) - [2025]
Peer Review College Memberships:
- EPSRC
- BBSRC
- NERC
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.