Academic Awards 2025 booklet

79 General comments about the works submitted The TU/e community can take pride in the fantastic work being done by our PhD students. The jury was greatly impressed by the ambition level of the projects that were carried out by all nominated candidates, reflecting the rich variety of exciting impactful projects in our PhD programs, as well as direct coupling to and impact on important and timely challenges faced in society and industry. The quality of the nominated theses varied from “very good” to “excellent”. The excellent reports not only presented a clear view on the work that has been done, but also demonstrated solid grounding in the relevant scientific communities and the current state of the art. In addition, these reports demonstrated how the candidates have actively and critically assessed during the project intermediate results in the light of the user requirements and project objectives and adapted dynamically the project if necessary. In all cases, the work was very well received by the clients, and often more widely beyond the direct project team. Winner(s) of the award Out of the 8 excellent contributions, 2 stood out – one PhD thesis and one technological design. The PhD thesis is from Iris Huijben (Electrical Engineering), entitled “Uncovering sleep structure through discrete representation learning” . The technological design is from Juliëtte van Haren (Industrial Design) for her work on “Materialising Futures for Perinatal Life Support Technology” . The jury suggest awarding two prizes this year, one for the best PhD thesis 2025 and one for the best Technological Design 2025. The jury is well aware about this change; however, it also wants to recognize the possibility of a thesis about a technological design. The technological design is about the novel design of an artificial womb. The novel contribution is in making an actual device that really can test the theoretical work. The results will increase the survival rate of premature infants. The PhD thesis of Iris Huijben presents methods to gaining a better understanding in both healthy and disordered sleep which can improve diagnosis and treatment of sleep disorders. Although the proposed solutions are highly innovative for the sleep field, she manages to make clear connections to gold standard methods, this way she secures understanding and acceptance by the clinical community. Laudatio Iris Huijben The clinical standard for sleep diagnostics recommends monitoring someone’s sleep by measuring a multitude of physiological signals. A full-night recording with these measurements is called a polysomnography (PSG), which yields vast amounts of high-dimensional data. Dimensionality reduction is a common technique to gain actionable insights from high-dimensional data.  REPORT OF THE JURY