Xihong Lin, PhD
The data science ecosystem encompasses data fairness, scalable statistical and ML/AI methods and tools, interpretable data analysis, and trustworthy decision making. Rapid advancements in AI have revolutionized data utilization and enabled machines to learn from data more effectively. Statistics, as the science of learning from data while accounting for uncertainty, plays a pivotal role in addressing complex real-word problems and facilitating trustworthy decision-making. In this talk, I will discuss the challenges and opportunities involved in building an end-to-end scalable data science ecosystem that integrates statistics, AI, and genomics and health. I will illustrate key points using the analysis of whole genome sequencing data, electronic health records and biobanks. This talk aims to ignite proactive and thought-provoking decisions, foster collaboration, and cultivate open-minded approaches to advanced scientific discovery.