Metin Akay

Dr Metin Akay
John S Dunn Endowed Professor,
Biomedical Engineering,
University of Houston

Dr Akay is the John S Dunn Endowed Professor of the Biomedical Engineering Department at the University of Houston. He earned his BS and MS degrees in Electrical Engineering (EE) from Bogazici University, Istanbul, Turkiye. Then, he pursued and obtained his PhD in Biomedical Engineering (BME) from Rutgers University, NJ, the United States.

He received honorary doctorates from Aalborg Silesian and Pécs Universities and professorship from the Technical University of Crete. He has authored more than 20 books and 180 journal papers, along with 200 conference papers and abstracts and delivered over 200 keynote and plenary talks at respected international conferences, including IEEE ICASSP twice.

He is a recipient of the IEEE EMBS Career, Early Career and Service Awards, an IEEE Third Millennium Medal, and the prestigious Zworykin Award from the International Federation for Medical and Biological Engineering (IFMBE). He is a life fellow of IEEE, fellow of the Institute of Physics (IOP), the International Academy of Medical and Biological Engineering (IAMBE), the American Institute for Medical and Biological Engineering (AIMBE), and the American Association for the Advancement of Science (AAAS).

His research focusses on the development of novel therapeutics for the treatment of cancer, neurotechnology for addiction and pain, brain cancer chips, and coronary occlusion.

Presentation Synopsis
Keynote Lecture: Healthcare Engineering: AI-Based Neural Biomarkers for Acute and Chronic Pain
Healthcare engineering is a rapidly evolving discipline at the intersection of engineering and healthcare and medicine. It aims to address critical and unmet needs in healthcare by fostering technological innovation to enhance patient outcomes, improve the efficiency and accessibility of care, and ultimately elevate quality of life. This field spans a broad spectrum—from the development of intelligent medical devices and novel therapeutics for the treatment of cancer, addiction, neurological diseases and pain.

This presentation highlights recent advances in healthcare engineering at the intersection of data science, neurotechnology and pain research. Specifically, we explore how artificial intelligence (AI) and implantable microimaging devices can be used to detect and characterize pain in a quantifiable, objective manner. Chronic pain affects world population, yet current clinical assessments largely rely on subjective self-reporting, which can be unreliable and inconsistent.

To address this gap, we present an AI-driven approach for identifying and isolating localized pain signals in the brain during both acute and chronic phases. Central to this work is our development of a novel implantable microimaging system, enabling real-time monitoring of neural activation within key brain subregions involved in pain processing. By applying Matching Pursuit decomposition to Local Field Potential (LFP) recordings from the Anterior Cingulate Cortex (ACC), Nucleus Accumbens (NAc), and Prelimbic Cortex (PrL), we extract latent signal components that reflect pain-induced changes in high- and low-frequency oscillatory dynamics.

Our preliminary findings reveal that: specific LFP components act as primary drivers of observable changes in brain activity during various pain states. Tracking these components over time provides insight into the cellular and circuit-level mechanisms underlying the transition from acute to chronic pain. Furthermore, consistent signal patterns across regions may indicate pathways of pain propagation through the thalamocortical circuitry. These findings offer a window into the interplay between pain and the brain’s reward systems, potentially informing novel pharmacological targets for both pain management and substance abuse intervention.

In conclusion, this research underscores the transformative role of healthcare engineering in neuroscience. By combining AI, neurotechnology, and systems neuroscience, we move closer to developing objective neural biomarkers for pain—tools that promise to reshape diagnostics, enable precision medicine, and expand therapeutic frontiers in chronic pain and addiction science.

In collaboration with Profs. M Ohsawa, J Ohta, Y Ohta and YM Akay, Dr. D Lloyd, D Yao, Dr. A Ganaway and TY Chen.

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