Professor Mahnaz Arvaneh
School of Electrical and Electronic Engineering
Professor of Intelligent Human-Machine Interfaces
Full contact details
School of Electrical and Electronic Engineering
Amy Johnson Building
Portobello Street
Sheffield
S1 3JD
- Profile
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Mahnaz received a Ph.D. on Advanced Brain-computer Interface from Nanyang Technological University (NTU), Singapore in 2013. From 2009 to 2013, she was also an attached researcher at the Institute for Infocomm Research, Agency for Science, Technology and Research, Singapore. Thereafter, she moved to University College Dublin where she worked as a lecturer in Biomedical Engineering in 2013. From 2014 to 2015, Mahnaz worked as a research fellow in the Trinity College Institute of Neuroscience. Since September 2015, she has been a lecturer in the Department of Automatic Control and Systems Engineering at the University of Sheffield, in January 2026 Mahnaz was promoted to Professor of Intelligent Human-Machine Interfaces.
Mahnaz’ expertise is in Brain-computer interface, neural signal processing, and their applications in monitoring and enhancing physical and mental health. She is the director of Physiological Signals and Systems Laboratory at University of Sheffield. Her work on neural interfaces has received high-profile media coverage, e.g. BBC Tech Tent, BBC Radio 4, Sky News, etc. She has published more than 50 highly cited papers in both engineering and neuroscience top-ranked journals and conferences. Since March 2018, she has been serving as an associate editor in IEEE transactions on Neural Systems and Rehabilitation Engineering. She also co-edited a book on brain-computer interface in IET, and contributed in Royal Society Neural Interfaces Perspective, launched in September 2019.
- Research interests
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In my research, I combine analytical and experimental techniques and develop novel signal processing and pattern recognition algorithms to better understand how our physiological systems (particularly the nervous system) work in healthy and diseased states. Through this research, I aim to improve our understanding of the human body, both to address fundamental questions in the control of physiological systems and to develop improved therapeutic, assistive, adaptive and rehabilitative technologies for a variety of conditions.
My research interests include:
- Biomedical signal processing, machine learning and pattern recognition
- Statistical and adaptive signal processing, and mathematical modelling of bioelectric signals
- Neural and cognitive process, clinical applications, and understanding
- Brain–computer interface algorithms, systems, adaptation, and applications
- Robotic and BCI-based stroke rehabilitation
- Neuroprosthetic learning and control
- Medical system and device research and development
Pilot funding, feasibility studies and equipment grants
- Woman Academic Return Program (WARP), £10000 funded by University of Sheffield for recruiting a research assistant, Nov 2017-Nov 2018.
- Robotics Capital Equipment Grant for purchasing an exoskeleton, £36000 funded by EPSRC Centre for Innovative Manufacturing in Large-Area Electronics, Nov 2016.
- “Controlling Prosthetic hands”, £1000 travel grant funded by Innovation Impact and Knowledge Exchange (IIKE), Nov 2016-March 2017.
- “Brain-controlled assistive devices”, £3000 small grant funded by Japanese-Anglo Daiwa foundation, June 2016-May 2018.
- “Controlling neuroprosthesis using brain and muscle signals”, £2700 funded by EPSRC Vacation Bursary (PI), June 2016- August 2016.
- “Enhancing Neuroprosthetic Control Using Error Related Brain Activities”, £5000 funded by EPSRC Institutional Sponsorship (CI), Nov 2015-Mar2016
- M. Arvaneh, “Mind controlled computers”, 500€ funded by European Commission in association with EU Researchers’ Night, Sep 2015 (equipment grant)
- M. Arvaneh, I. Robertson, “Analysing brain signals for monitoring and enhancing cognitive performance”, 3600€ funded by Insight (Science Foundation Ireland), March 2015 (for recruiting an intern student)
- M. Arvaneh, A. Martel, I. Robertson, 2000€ funded by European Commission in association with EU Researchers’ Night, Sep 2014 (equipment grant)
- M. Arvaneh, 400 USD IEEE Signal Processing Society Travel Grant for ICASSP 2012
- Publications
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Journal articles
- Expanding the olfactory implant paradigm through recent advances in brain-computer interface technology.. Rhinology.
- Beyond the surface: a review of transcranial temporal interference stimulation for deep brain modulation. Frontiers in Neurology, 16. View this article in WRRO
- Associations between pre-cue parietal alpha oscillations and event related desynchronization in motor imagery-based brain-computer interface. Frontiers in Human Neuroscience, 19. View this article in WRRO
- A machine-learning-based approach to predict early hallmarks of progressive hearing loss. Hearing Research, 464. View this article in WRRO
- A clinical trial evaluating feasibility and acceptability of a brain-computer interface for telerehabilitation in stroke patients. Journal of NeuroEngineering and Rehabilitation, 22. View this article in WRRO
- One hundred years of EEG for brain and behaviour research. Nature Human Behaviour, 8(8), 1437-1443. View this article in WRRO
- Copyright Page. 2024 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), 1-85.
- Opportunities and obstacles in non-invasive brain stimulation. Frontiers in Human Neuroscience, 18. View this article in WRRO
- Editorial: Machine learning and signal processing for neurotechnologies and brain-computer interactions out of the lab. Frontiers in Neuroergonomics, 4. View this article in WRRO
- Bayesian learning from multi-way EEG feedback for robot navigation and target identification. Scientific Reports, 13(1). View this article in WRRO
- Dose Standardization for Transcranial Electrical Stimulation: An Accessible Approach. Scientific Reports.
Conference proceedings
- Neurophysiological Correlates of Human Trust in Machines: EEG-Based Assessment Using Error-Related Potentials and P300. 2025 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) (pp 258-263), 22 October 2025 - 24 October 2025.
- Feasibility and Acceptability of P300-Based Brain-Computer Interface Neurofeedback Training for Cognitive Enhancement. 2025 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) (pp 628-633), 22 October 2025 - 24 October 2025.
- Optimized Spatial Filter Selection for Transfer Learning in Brain-Computer Interface. 2024 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) (pp 1141-1146), 21 October 2024 - 23 October 2024.
- Improving Motor Imagery-Based Brain-Computer Interfaces with Simple EEG Data Augmentation Algorithms: A Comparative Analysis. 2024 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) (pp 423-428), 21 October 2024 - 23 October 2024.
- Analysing and modelling human trust to a navigation robot. 2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) (pp 658-663). Milano, Italy, 25 October 2023 - 25 October 2023. View this article in WRRO
- Predicting Outcomes of Cognitive Behavioral Therapy for Depression Using Data Driven Approaches. 2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Vol. 9 (pp 336-343), 31 October 2023 - 3 November 2023.
- Improving Common Spatial Patterns in Brain-Computer Interface Using Dynamic Time Warping and EEG Normalization. 2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) (pp 1027-1032), 25 October 2023 - 27 October 2023.
- Single-Trial EEG Classification of Semantic Visual Targets in a Novel Oddball Task. IEEE Xplore Digital Library
- SUPER: Augmenting human-machine teaming in defence with biofeedback-enhanced brain-computer interfaces - preliminary results. STO-MP-HFM-MSG-375 Human Digital Twin in the Military: Findings and Perspective
- Expanding the olfactory implant paradigm through recent advances in brain-computer interface technology.. Rhinology.
- Grants
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Current Grants
- Fostering Acceptance and Inclusivity of Non-Invasive Neurotechnology in African Ethnic Minority Communities, EPSRC, 07/2024 - 03/2025, £19,993, as PI
- ElectroTools, RCUK, 07/2023 - 06/2024, £189,978, as PI
- Feasibility study for a single blind randomised control trial on effect of exo-skeleton assisted walking on cardiovascular fitness of persons with gait problems due to multiple sclerosis, MS Society, 05/2022 - 08/2024, £11,277, as PI.
- Transfer Learning for Processing Different Neurological Conditions, Daiwa Foundation, 12/2019 - 07/2024, £8,000, as PI.
- Defence And Security Accelerator - SUPER: Systemic User Performance Enhancement in Real-time, 10/2023 - 02/2025, £204,443 as Co-I
- Innovate UK iCURE-Explore - Accelerating upper limb stroke rehabilitation from home through the power of the brain, 10/2023 - 01/2024, £35,000 as PI
- HALEON UK - Provision of novel methods for accurate quantification of responses to thermal stimuli in patients with dental sensitivity, 08/2023 - 08/2025, £103,685 as Co-I
Previous Grants
- TeleRegain II: Accelerating upper limb stroke rehabilitation from home through the power of the brain, UKRI, 10/2023 - 01/2024, £35,000, as PI
- MindD4AccelCare - Multimodal Intelligent Neural Decoder for Accessible and empowering mental healthcare, RCUK, 10/2022 - 11/2023, £26,819, as PI.
- TeleRegain - The Next Level, Research England, 03/2023 - 07/2023, £9,625, as PI
- Co-design of an Inclusive Upper Limb Telerehabilitation system using Brain-controlled Functional Electrical Stimulation, Research England, 03/2022 - 07/2022, £4,800, as PI.
- TeleBCI-FES: Upper Limb Telerehabilitation using Brain-controlled Functional Electrical Stimulation, MRC, 07/2021 - 11/2022, £70,560, as PI.
- Neurophysiological Biomarkers for Comparative Diagnosis and Prognosis across Neurodegenerative Diseases, Royal Society, 03/2019 - 02/2023, £11,990, as PI.
- Teaching activities
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Current
- BIE3411 Design of Biomedical Devices and Implants
- ACS321 Digital Signal Processing
Past
- MAT3411- Design of Biomedical Devices and Implants (Spring 2016)
- Bioengineering degree Board of Studies (ACSE representative)
- Bioengineering degree, theme leader: Medical Devices and Systems
- Program coordinator of BEng and MEng in Biomedical Engineering, University College Dublin, 2013
- EEEN30160- Biomedical Signals & Images, University College Dublin, 2013 and 2014
- EEEN40350- Rehabilitation Engineering (joint module leader), University College Dublin, 2013 and 2014