Alejandra Avalos-Pacheco
Awards
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".
Travel awards:
2024 ISBA World Meeting in Venice, Italy, awarded by ISBA and G-RESEARCH.
2023 International Conference on Statistics and Data Science in Lisbon Portugal, awarded by IMS & Industry Friends of IMS
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.
grants
2024-2027 EULiST Alliance Research and Innovation Doctoral Funds, and the LUT School of Engineering Sciences, Finland
Role: co-PI
Other PIs: Prof. Lassi Roininen (Lappeenranta-Lahti University of Technology, Finland) and Dr Matt Moores (University of Wollongong, Australia).
Project: Bayesian inference for water hyacinth's spatio-temporal dynamics.
€130,000.00 (approximately) covering the salary of one PhD student, travels and research visits.
2023-2024 European Union - Next GenerationEU, and the University of Florence. Young Independent Researchers Call
Original role: team leader (withdrawn)
Current role: external collaborator
Original team members: Dr V. Ballerini & Dr M. Pedone
Grant no. B008-P00634
Project: Bayesian Methods for Clinical and Observational Studies (BayesMeCOS).
€236,000.00 covering the salary of three researchers, travels and research visits.
On the media
About me
I am an Universitätsassistentin (Assistant Professor non-tenure track) in the Research Unit of Applied Statistics (ASTAT) at the Technische Universität Wien (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).
News
I was granted a visiting position allowing me to engage with the researchers at the University of Sydney (Dr Clara Grazian), the University of Wollongong (Dr Matt Moores), and Monash University (Dr Jack Jewson). This was awarded by the Scientific Advisory Committee of The University of Sydney Mathematical Research Institute (SMRI), as part of their International Visitor Program!
I am part of the Complex Graphical Models for Biological Network Science (COMBINERS) grant team, lead by Prof. Francesco Stingo. This project, funded by the European Union - Next GenerationEU and the Italian Ministry of Education, concerns the development of novel principled statistical tools for the analysis of complex networks under non-standard experimental setups. It is developed by the collaborative efforts of four research units based at the University of Florence, Università Cattolica del Sacro Cuore, University of Padova and University of Palermo.
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!
Email
alejandra.avalos (at) tuwien.ac.at
Address
TU Wien
Institute of Statistics and Mathematical Methods in Economics
Wiedner Hauptstraße 8-10/105, 4. floor, yellow area
Office: DB04B08
1040 Wien, Austria