معرفی
Matias Quiroz is a Senior Lecturer at the University of Technology Sydney (UTS) in the School of Mathematical and Physical Sciences. He joined UTS in July 2023 after previously serving as a Lecturer (2019–2022) and Senior Lecturer (2022–2023) at Stockholm University. His expertise lies in computational statistics, Bayesian methods, and machine learning. He holds a Ph.D. from Stockholm University (2015) and an M.Sc. in Engineering Mathematics from Lund University (2009).
Research focuses on developing efficient MCMC algorithms for large datasets and variational approximations for high-dimensional models. He has contributed to areas like subsampling MCMC, spectral analysis of time series, and Bayesian inference for complex models. Quiroz is also an Associate Editor for Computational Statistics and Data Analysis and Econometrics and Statistics.
Teaching responsibilities include courses such as Machine Learning: Mathematical Theory and Applications and Programming for Data Analysis. He has supervised students at various academic levels and has held editorial and leadership roles, including serving as the Young Stats representative for the NSW Branch of the Statistical Association of Australia since 2025.
His work bridges Bayesian statistics with machine learning, emphasizing scalable computational methods. Notable research themes include high-dimensional state space models, dynamic linear regression, and algorithmic innovations for big data problems.
