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Tuan D. Pham currently holds a position as Professor of Artificial Intelligence (AI) in Imaging, Diagnostics, and Trauma with Barts and The London School of Medicine and Dentistry, Queen Mary University of London, UK.  He was drawn to the UK with a Global Talent Visa subsequent to receiving a notable Endorsement from The Royal Society for his work on AI and Imaging in Medicine and Health. Additionally, he holds the position of Honorary Professor with Barts Health NHS Trust, solidifying his commitment to bridging academia and practical healthcare.

His primary responsibilities revolve around spearheading and nurturing novel research initiatives specializing in AI for medical imaging and physiological signal analysis and classification.  He is dedicated to fostering collaborative endeavors across the comprehensive spectrum of the Faculty of Medicine and Dentistry, aiming to elevate innovation within his domain.

Prior to his current role, he has held several pivotal positions that have significantly shaped his academic journey.  He served as the Senior Research Professor in AI and simultaneously acted as the Founding Director of the Center for Artificial Intelligence at Prince Mohammad Bin Fahd University, Saudi Arabia.  Before that, his tenure as a Professor of Biomedical Engineering at Linkoping University, University Hospital Campus, Linkoping, Sweden, offered him a diverse and enriching experience.

Furthermore, his contributions extended to Japan, where he held the position of Professor and Leader of the Aizu Research Cluster for Medical Engineering and Informatics, and concurrently led the Medical Image Processing Lab at the University of Aizu.  Preceding his engagements in Japan, he assumed the role of Associate Professor and served as the Bioinformatics Research Group Leader at the University of New South Wales, Canberra, Australia.

Presently, his research efforts remain dedicated to the advancement of AI and machine learning methodologies in the context of image processing, time-series analysis, complex networks, and pattern recognition.  These efforts are deeply rooted in their applications to a diverse range of fields encompassing dentistry, medicine, biology, and mental health.  His commitment to the advancement of academic discourse is evident through his editorial roles as an Associate/Section Editor for various prestigious scholarly journals and conference proceedings.

In terms of his academic output, he has authored 3 impactful research monographs, over 150 peer-reviewed journal articles, along with an array of over 200 peer-reviewed conference papers.  His contribution to the field of AI was acknowledged with the grant of a US patent in 2021, recognizing his pioneering work in developing an efficient deep-learning approach for the classification of physiological signals.

In a testament to his expertise, he was honored with the opportunity to serve as an Expert in Artificial Intelligence for advisory consultation by the U.S. Food & Drug Administration (FDA) Center for Devices and Radiological Health (CDRH) through its esteemed Network of Digital Health Experts Program (NoDEx). This recognition underscores his commitment to fostering advancements at the intersection of technology and healthcare, ensuring the development and implementation of effective AI-based solutions.

His professional trajectory has been characterized by a relentless pursuit of excellence and a passion for leveraging cutting-edge technology to address critical challenges within the fields of healthcare and academia.  He remains dedicated to pushing the boundaries of knowledge and innovation, with an unwavering commitment to creating a positive impact on the broader landscape of AI, imaging, and healthcare.