Dr. Zag ElSayed of University of Cincinnati

The convergence of neuroscience, artificial intelligence, and advanced sensing technologies is transforming how humans interact with machines. At the center of this transformation is the ability to decode the brain’s dynamic electrical activity. This talk introduces NeuralDNA, a framework that describes structured patterns of neural activity that encode learning, spatial cognition, and decision-making in the human brain. Understanding these neural patterns opens new possibilities for translating brain signals into computational models that enable more natural and adaptive human–machine interaction.

The talk explores how modern Brain Computer Interfaces (BCIs) are evolving from simple signal acquisition systems into intelligent platforms capable of learning from neural data in real time. By integrating machine learning, neural data science, and advanced signal processing, researchers can extract meaningful information from complex EEG signals and develop adaptive systems that respond to cognitive states. It will highlight recent research on auditory neural stimulation and EEG biomarker discovery aimed at improving cognitive engagement and learning capability in individuals with neurodevelopmental conditions such as Fragile X syndrome and autism spectrum disorders. By analyzing brainwave responses to controlled stimulation frequencies, these studies reveal neural patterns associated with enhanced cognitive states and demonstrate how machine learning can help optimize stimulation strategies.

Beyond clinical applications, emerging BCI technologies are enabling innovations in assistive systems, cognitive enhancement, mental health monitoring, and human–AI collaboration. As neural interfaces advance, they bring both opportunities and challenges, including ethical considerations related to neural data privacy and the responsible integration of AI. By uncovering the hidden architecture of neural activity, what we call NeuralDNA, this talk explores how integrating biology and engineering may redefine learning, cognition, and the future of intelligent systems.

Biography:

Dr. Zag ElSayed is an Assistant Professor in the School of Information Technology at the University of Cincinnati and a Research Affiliate at Cincinnati Children’s Hospital Medical Center. His interdisciplinary research lies at the intersection of Brain Computer Interfaces (BCI), EEG signal analysis, artificial intelligence (AI), industrial Internet of Things (IIoT), and cybersecurity, with applications in mental health, biomedical signal processing, and intelligent healthcare systems. His work focuses on leveraging advanced computational methods to decode neural activity and develop adaptive, intelligent systems that improve human health, cognitive performance, and secure cyber physical infrastructures. Dr. ElSayed earned his Ph.D. in Computer Engineering from the University of Louisiana and holds multiple M.Sc. and advanced degrees in Computer Science, Computer Engineering, and Automatic Control Engineering, as well as specialized studies in Neuroinformatics. Prior to academia, he accumulated over 12 years of industry experience in Industrial IT solutions, bringing strong practical expertise to the design of scalable and secure intelligent systems.

His research contributions span cybersecurity, automation, machine learning, EEG-based neural decoding, adaptive AI models for neurological and cognitive disorders, and motor rehabilitation technologies, as well as the development of secure, low-power intelligent sensing systems. Dr. ElSayed has authored numerous interdisciplinary peer-reviewed publications and actively contributes to the global research community as an IEEE Senior Member, keynote speaker, and reviewer for the National Science Foundation (NSF) and leading international journals and conferences. As an educator and mentor, Dr. ElSayed develops and teaches graduate and undergraduate courses in data-driven cybersecurity, sustainable computing infrastructure, and neural systems design, neurophysiology to uncover patterns in brain activity that can inform adaptive and personalized neurotechnology, integrating cutting-edge technologies with hands-on, experiential learning to prepare students for emerging challenges at the intersection of AI, cybersecurity, healthcare, applied neurotechnology and intelligent sensing systems. He shared this vision in a TEDx talk, https://youtu.be/BvYRSQNZ67c.

Email:

Address:Cincinnati, Ohio, United States