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Dr. Bärbel Finkenstädt Rand is a professor specializing in the development of statistical machine learning methodologies with a focus on Bayesian and parametric approaches. Her research spans a range of areas including epidemiology, molecular genetics, and the modeling of oscillatory dynamics. She has worked extensively on change point detection and dynamic regime transitions, with the goal of creating data-driven methodologies that provide insights in the biomedical sciences. Her current focus involves the exploration of large-scale physiological datasets gathered from wearable sensors, collaborating with the Chronotherapy Group at the University of Warwick and Université Paris-Saclay. Through her research, Dr. Finkenstädt Rand aims to optimize cancer therapy timing based on individuals' circadian rhythms, ultimately supporting personalized treatment plans. Her extensive publication record includes multiple influential papers that demonstrate her contributions to understanding circadian rhythms and their implications in health care.
Includes General, Mechanical, Civil, Electrical, Biomedical, and Manufacturing Engineering. Most programs fall under English Band A.