Leonie Boland completed both her Bachelor’s degree in Mathematics and her Master’s degree in Scientific Computing at Heidelberg University. During the later stages of her Bachelor’s studies, she developed a strong interest in data science and machine learning, particularly in their applications to biology and medicine. For her Master’s thesis, carried out in IMSY’s photoacoustics group, she worked on learning to simulate tissue properties from photoacoustic images - a challenging and ill-posed inverse problem. In October 2025, she joined the division as a Ph.D. student, where she continues to combine machine learning methods with medical research.
Outside of her academic work, Leonie enjoys staying active through triathlon (swimming, cycling, and running), gym training, and tennis. She is also passionate about skiing, surfing, traveling, and baking.