Original news article from: https://www.ercim.eu/news/532-2023-cor-baayen-early-career-researcher-award-for-rianne-de-heide
The ERCIM Selection Committee for the Cor Baayen Young Researcher Award unanimously selecteds Rianne de Heide, nominated by CWI, as the winner for 2023. An honorary mention is given to Denis Merigoux from Inria.
Dr. Rianne de Heide's research activity stands out for its quality and breadth. Her work covers a wide variety of topics within the general field of mathematical statistics, with focus on learning from data. In her work, Bayesian learning is used as a tool, sometimes critically evaluated, sometimes extended, always with a strong mathematical-theoretical component. Her work reaches breadth by (a) the aspects of learning from data/statistics that are studied: optional stopping, misspecification (statistics with incorrect but useful models), philosophical problems in induction, bandits, and (b) the scope across various other disciplines: philosophy and logic, psychology, and machine learning and AI.
Particularly worthy of attention is her work on optional stopping/safe testing, describing a new statistical method for hypothesis testing. This work is highly innovative and has a considerable scientific and societal potential in reducing the percentage of incorrect conclusions published in applied sciences.
Her more recent work delves into the field of explainable machine learning, where she promises to continue her interesting work. Simultaneously, she is working on a new theory for hypothesis testing with e-values, currently in the context of multiple testing.
Her independent and original ideas led and are leading to publications across different subfields at top venues. Her work is having a clear impact on the community, it is well-cited and is the foundation for numerous follow-up papers by others in the field. In her publications Dr. de Heide manages to switch between clearly explaining mathematical ideas to a non-mathematical audience and developing highly technical mathematics for peers.
We also commend Dr. de Heide for her interest and active role in teaching. Already during her PhD, she developed a successful master's course on Machine Learning Theory for the Dutch MasterMath program.
Rianne is currently employed at Vrije Universiteit Amsterdam. She obtained her PhD in 2021 from Leiden University. The work was partly carried out at CWI. The title of her thesis is "Bayesian Learning: Challenges, Limitations and Pragmatics". The work was supervised by P.D. Grünwald and J.J. Meulman. Her PhD was awarded the W.R. van Zwet Award 2022, for the best Dutch dissertation in the field of mathematics and operations research, Dutch Society for Statistics and Operations Research.
Photo by Chantal Bekker.