2020 Audience choice award for my poster "Leveraging external data in Bayesian adaptive designs", 2020 Global Conference in Regulatory Science, Harvard Medical School, Harvard University (Massachusetts, USA).
2019 Savage award granted by the International Society for Bayesian Analysis (ISBA) and the American Statistical Association (ASA) Section on Bayesian Statistical Science (SBSS). Best PhD thesis in the category Applied Methodology: "Factor regression for dimensionality reduction and data integration techniques with applications to cancer data".
2023 BayesComp in Levi Finland, awarded by ISBA.
2022 ISBA World Meeting in Montreal, Canada, awarded by ISBA and the UCLA Department of Biostatistics.
2019 O'Bayes in Warwick, UK, awarded by ISBA
2017 O'Bayes in Texas, USA, awarded by ISBA.
On the media
I am an Universitätsassistentin (Assistant Professor non-tenure track) in the Research Unit of Applied Statistics (ASTAT) at the Vienna University of Technology (TU Wien). I am also an affiliated member at Harvard University in the Harvard-MIT Center for Regulatory Science.
My main goal is to create interpretable and computationally efficient models for large complex data. I aim to give a better understanding of real world problems, and help to provide fast accurate decisions. I am interested in applications to problems in medicine, in particular cancer. I develop statistical methods for large heterogenous data, mainly leveraging Bayesian and probabilistic machine learning algorithms, and focusing on data integration. My main research interests include high-dimensional inference, applied Bayesian statistical modelling, dimensionality reduction, heterogenous data integration, graphical models, and clinical trials.
Before joining TU Wien, I was a research fellow (assegnista di ricerca) at the University of Florence in the Department of Statistics, Computer Science, Applications ''G. Parenti'', working with Prof. Francesco Stingo and Prof. Monia Lupparelli. Prior to the University of Florence, I was a postdoctoral fellow in Statistics at Harvard University in the Harvard-MIT Center for Regulatory Science, and I was also part of Prof. Lorenzo Trippa's group at the Dana-Farber Cancer Institute (DFCI) in the Department of Data Science.
I did my PhD in Statistics on the joint CDT programme between the University of Warwick and the University of Oxford (OxWASP). I worked on statistical methods for genomic data analysis with Prof. David Rossell (UPF) and Prof. Richard Savage (Warwick).
Our "Frontiers of Bayesian Inference and Data Science" conference proposal got selected by the Banff International Research Station for Mathematical Innovation and Discovery (BIRS), to be part of its 2024 sponsor conferences! I am honered to co-organize this with Prof. Peter Mueller, Dr Ma. Fernanda Gil Leyva Villa and Dr Alan Riva Palacio
I am part of the organising committee of BaYSM 2023!
I have been appointed as an Senior Associate Editor of the newly approved ACM Transactions on Probabilistic Machine Learning (TOPML).
I am part of the Harvard-MIT Center for Regulatory Science as an Affiliated Member!
I am part of the scientific committee of BaYSM 2022!
I am the Chair-elect of the Junior Section of ISBA (j-ISBA). It is an honour to work for the new generation of Bayesian researchers!
alejandra.avalos (at) tuwien.ac.at