Invited Speakers

Prof. Dr. Partha Pratim Das

Dr. Partha Pratim Das is a Professor at the Department of Computer Science and the Founding Director of the Center of Data Science and Analytics at Ashoka University. He has over 24 years' experience in teaching and research, and about 13 years' experience in Software Industry. He has worked extensively in Digital Geometry, Smart Software Engineering, and Digital Heritage for academic research; and EDA frontend automation and T & M tools in video technology as industrial products. His current interests are Food, Nutrition and Digital Health. In Ashoka, Partha leads the initiative on Ashoka Datalake to host research data for climate, health, social and physical sciences and others, and anchors the project on “Indian food knowledge graph for personalized digital health” in collaboration with Trivedi School of Biosciences at Ashoka and Institute of Future Health @ UCI.

Earlier, Partha had been involved in R & D and education on impact projects using huge volumes of integrated and curated data and tools of AI. From 2015 to 2022, he initiated and led the National Digital Library of India Project of Ministry of Education to create an open educational library having about 100 million+ free contents organized by educational needs of the users. Partha has guided over a dozen doctoral theses and has published over 100 technical papers.
An AI-Driven Interoperable Food Platform for Comprehensive Dietary Management
Food lies at the heart of human life, offering nourishment for the body and joy for the mind. However, the rise of diet-related health challenges – such as malnutrition, hypertension, diabetes, cardiovascular diseases, and anaemia – calls for informed and personalized dietary decisions. These decisions are influenced by factors like availability, affordability, cultural and personal preferences, and specific health conditions, creating a need for an advanced digital platform that unites diverse aspects of food and nutrition knowledge.

This presentation unveils an AI-driven interoperable digital food platform, underpinned by a curated food knowledge graph and a comprehensive food ontology. By harnessing the power of artificial intelligence, large language models (LLMs), and language technologies, the platform curates and synthesizes information from diverse sources, ensuring adaptability and interoperability with similar systems. It also facilitates interaction with conversational agents for personalized and practical end-user applications.

We will conclude by exploring future possibilities, such as university-led initiatives for modelling food-health dynamics, mobile apps for tracking and recommending dietary choices, and integration with food-agro platforms, supply-chain models, and policy frameworks. This holistic approach aims to revolutionize dietary management, addressing both personal health and broader food security challenges on a national scale.

Prof. Dr. Ramesh Jain

Ramesh Jain is a distinguished entrepreneur, researcher, and educator, currently serving as the Emeritus Donald Bren Professor and founding Director of the Institute for Future Health at the University of California, Irvine. With a rich research background spanning control systems, computer vision, artificial intelligence, and multimedia computing, his current endeavors focus on revolutionizing health through cybernetic principles, leveraging advancements in sensors, mobile technology, processing, AI, and storage solutions. A recognized leader in his field, Jain is a Fellow of AAAS, ACM, IEEE, AAAI, IAPR, and SPIE.

His entrepreneurial journey includes co-founding several tech companies, steering them through their formative phases before transitioning them to professional management. Jain thrives on confronting new challenges, employing technology as a tool for solutions, particularly in his latest quest: devising innovative ways to enhance longevity and improve health quality. His work embodies a commitment to tackling some of the most pressing technical challenges of our time, making significant strides towards a future where good health and longevity are within everyone's reach.
Conversational Personal Food Agents
What to eat? This fundamental daily decision impacts our health, happiness, and quality of life. Yet, in our fast-paced world, balancing taste and nutrition remains a persistent, nagging challenge. This talk introduces Food Agents, AI-powered culinary assistants designed to solve the “Palate Puzzle”—the misconception that healthy food lacks flavor while tasty food is unhealthy. By integrating Personal Food Models (PFM), Food Knowledge Graphs (FKG), and Food Availability Atlases (FAA), these digital assistants offer personalized dietary recommendations that satisfy both palate and nutritional needs. These innovative tools can transform our relationship with food, making “delicious nutrition” an everyday reality. Join us to explore how AI-driven solutions can revolutionize food choices, enhancing health outcomes globally. This talk demonstrates technology’s potential to harmonize taste and health in our most fundamental daily decision.

Prof. Dr. George Dedoussis

George Dedoussis is a Professor of Molecular Genetics and Nutrigenetics at the Department of Nutrition and Dietetics of Harokopio University in Athens. He received his Bachelor degree in Biology from the University of Patras, MSc degree from the University of Compiegne, PhD from the Medical School of Athens and has worked as a researcher on a Fulbright scholarship at 'Harvard University'. Having an h-index of 107, he was nominated among the most cited scientists worldwide during the last decade.
Personalized Approaches in Obesity: Updates from the Preventing Obesity Through Biologically Tailored Interventions: BETTER4U Project
A large-scale Genome-Wide Association Study (GWAS) is currently in progress to investigate Body Mass Index (BMI) using data from approximately 250,000 individuals. Comprehensive phenotypic data have been collected and analyzed, targeting the effects of lifestyle and socioeconomic determinants on BMI across a broader sample of over 500,000 individuals. This extensive dataset provides a strong foundation for understanding the complex interplay between genetic, lifestyle, and socioeconomic factors influencing BMI. Additionally, an artificial intelligence (AI) model is being developed and trained to determine optimal lifestyle interventions for weight loss, drawing upon data from large TAUH and HUA datasets. This AI-driven approach aims to provide tailored lifestyle recommendations that could maximize the efficacy of weight management interventions. A pilot study for the identification of the BETTER4U Core Behavioral Indicators associated with lifestyle changes and for the complementary training of the AI is currently in the organization phase, laying the groundwork for a full-scale implementation. In tandem, the innovative BETTER4ALL application and platform are being developed to support personalized interventions. These digital tools will enable remote monitoring of multiple lifestyle parameters, including dietary intake, physical activity, sleep quality, and other relevant health behaviors. The BETTER4ALL intervention aims to create a comprehensive, personalized experience for users, offering scientifically backed insights and real-time feedback to facilitate sustainable lifestyle changes. This integrated approach has the potential to advance obesity management by providing data-driven, biologically tailored interventions directly to individuals.