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Inaugural Lecture: AI-Powered Neurotechnology and Intelligent Human-Machine Interfaces with Professor Mahnaz Arvaneh

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What to expect

Join the University of Sheffield for Professor Mahnaz Arvaneh's inaugural lecture exploring the intersection of artificial intelligence and neurotechnology, and discover how AI is transforming brain-computer interfaces from laboratory concepts into real-world applications.

From Brain Signals to Real-World Impact

Professor Arvaneh will share insights from her research journey, addressing a fundamental question: how can we make neurotechnology more useful in everyday life? This lecture traces the evolution of her work from early brain signal processing and brain-computer interfaces to cutting-edge AI-driven rehabilitation systems, brain stimulation techniques, and inclusive design frameworks.

What You'll Learn

The lecture will explore how artificial intelligence is helping bridge the gap between laboratory research and practical applications in neurotechnology. Topics covered include:

  • Developing adaptive systems that respond to individual users and accommodate variability in brain signals
  • Reducing lengthy calibration processes that currently limit practical deployment
  • Applying closed-loop neurotechnology, transfer learning, and generative AI to stroke rehabilitation
  • Creating home-based rehabilitation systems that extend beyond clinical settings
  • Designing accessible, inclusive neurotechnology grounded in real human needs

Professor Arvaneh will highlight both the scientific progress achieved and the barriers that remain in bringing intelligent human-machine interfaces to widespread use. Through examples from projects like TeleRegain and StimDose, attendees will gain insight into high-TRL (Technology Readiness Level) research that moves neurotechnology closer to real-world impact.

About the Speaker

Professor Mahnaz Arvaneh serves as Professor of Intelligent Human-Machine Interfaces at the University of Sheffield's School of Electrical and Electronic Engineering. Her research combines artificial intelligence, brain-computer interfaces, neurostimulation, and rehabilitation engineering to develop personalised, user-centred closed-loop neurotechnologies. She has published over 90 peer-reviewed papers and contributes to shaping policy and standards through work with the Royal Society, British Standards Institution, ISO/IEC working groups, and the UK Regulatory Horizons Council. In 2025, she was recognised as a finalist for the UK Women in Neuroscience interdisciplinary research award.

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