This track focuses on foundational science, experimental design, and new methodologies that advance Artificial Intelligence and Machine Learning. Presentations may include mechanistic studies, model systems, computational approaches, and validation strategies that set the stage for translation.
Sessions encourage debate on reproducibility, benchmarking, and how emerging tools change what we can measure and infer.
