معرفی
Dr Hugo Maruri-Aguilar is a Lecturer in Statistics at Queen Mary University of London, affiliated with the School of Mathematical Sciences and the Centre for Probability, Statistics and Data Science. His research focuses on algebraic statistics, computer experiments, and statistical modeling using likelihood and penalized likelihood techniques. He explores design of experiments through algebraic methods and develops emulators for computer experiments using polynomial models regularized by smoothness.
His research interests include Lasso regression, topological data analysis, and applications in music generation and healthcare. Recent work emphasizes model selection and sparse polynomial prediction. He has collaborated on projects ranging from biomarker prognostic models in heart failure to AI-driven music composition.
Dr Maruri-Aguilar has contributed to over 15 peer-reviewed publications across journals like Statistical Papers, Annals of the Institute of Statistical Mathematics, and Technometrics. His methodologies address challenges in optimal design, computational topology, and interdisciplinary applications in music and medicine.
