Future Health: Harnessing Multimodal Data and GenAI for Health Promotion


Event details

Date 30.08.2024
Hour 11:00
Speaker Amir M. Rahmani, PhD, MBA Affiliation: Professor of CS, EECS, and Nursing, Co-Director of the UCI Institute for Future Health, University of California, Irvine, USA

Amir M. Rahmani is the founder of the Health SciTech Group at the University of California, Irvine (UCI) and the co-founder and Co-Director of the Institute for Future Health, a campus-wide Organized Research Unit at UCI. He is also a lifetime docent (Adjunct Professor) at the University of Turku (UTU), Finland.

His research includes AI in healthcare, ubiquitous computing, AI-powered bio-signal processing, health informatics, and big health data analytics. He has been leading several NSF, NIH, Academy of Finland, and European Commission-funded projects on Smart Pain Assessment, Community-Centered Care, Family-centered Maternity Care, Stress Management in Adolescents, and Remote Elderly and Family Caregivers Monitoring.
He is the co-author of more than 350 peer-reviewed publications and the associate editor-in-chief of ACM Transactions on Computing for Healthcare and Frontiers in Wearable Electronics journals and the Editorial Board of Nature Scientific Reports. He is a distinguished member of the ACM and a senior member of the IEEE.
Category Conferences - Seminars
Event Language English
“Future Health” emphasizes the importance of recognizing each individual’s uniqueness, which arises from their specific omics, lifestyle, environmental, and socioeconomic conditions. Thanks to advancements in sensors, mobile computing, ubiquitous computing, and artificial intelligence (AI), we can now collect detailed information about individuals. This data serves as the foundation for creating personal models, offering predictive and preventive advice tailored specifically to each person. These models enable us to provide precise recommendations that closely align with the individual’s predicted needs.

In my presentation, I will explore how AI, including generative AI, and wearable technology are revolutionizing the collection and analysis of big health data in everyday environments. I will discuss the analytics used to evaluate physical and mental health and how smart recommendations can be made objectively. Moreover, I will illustrate how leveraging Large Language Models (LLMs)-powered conversational health agents (CHAs) can integrate personal data, models, and knowledge into healthcare chatbots.

Additionally, I will present our open-source initiative on developing OpenCHA. This integration allows for the creation of personalized chatbots, enhancing the delivery of health guidance directly tailored to the individual.