Invited & Keynote Speakers
Meet our keynote and invited speakers presenting cutting-edge research on safe, ethical, and trustworthy AI for health.
Professor at Carnegie Mellon University
This talk explores ethical and responsible AI in AgeTech and neuroscience. Drawing from real-world deployments and neuro-AI platforms, Dr. Fang will highlight how interpretable, robust models enable personalized care while maintaining trust and safety.
Cofounder & CEO, ChemT Biotechnology
Virtual cells act as decision-support systems in modern biomanufacturing. This talk discusses uncertainty-aware AI, robustness under distribution shift, and closed-loop validation as safety backbones for industrial deployment.
Professor of CS, BITS Goa · Adjunct AIISC, USA
This talk analyzes adversarial prompting, alignment drift, retrieval poisoning, and long-term degradation in clinical LLMs, and proposes systematic safety evaluation and repair strategies for trustworthy medical AI.
University of British Columbia · National Institute for Mathematical Sciences, Korea
We study curve-fitting problems for noisy data generated by processes governed by differential equations. By incorporating differential equation constraints into nonparametric kernel smoothing, bias can be reduced while preserving flexibility. Large Language Models are used to assist in repeated differentiation and parameter tuning. Applications include simulated stochastic SIR models and real influenza-like illness data, enabling detection of departures from classical epidemiological models.