Scalability and uncertainty quantification in temporal and network data
Staff - Faculty of Informatics
Date: 15 March 2024 / 10:30 - 11:15
USI Campus Est, room D1.14, Sector D
Speaker: Deborah Sulem, Barcelona School of Economics, Pompeu Fabra University
Abstract:
In this talk, I will present topics that I have been investigating in my recent research, mainly focusing on the analysis of temporal and network data. I am developing statistical and Machine Learning methods that are suitable for large and high-dimensional data sets and that can provide uncertainty bounds on the inference results. After a general presentation of my research interests, I will focus on a recent work on high-dimensional Gaussian graphical models with sparse Bayesian algorithms.
Biography:
Deborah is currently a postdoctoral researcher at the Barcelona School of Economics and Pompeu Fabra University in the Department of Business and Economics. Her research interests lies at the intersection between mathematical statistics, data science, machine learning, and artificial intelligence. She previously obtained an Engineering degree at Ecole Polytechnique (Paris) in 2018 and a Ph.D. degree in the Department of Statistics at the University of Oxford in 2023. Her research expertise includes networks, point processes, Bayesian inference, graph deep learning, graphical models and nonparametric statistics. She is also interested in robustness and explainability for machine learning algorithms and natural language processing.
Host: Prof. Ernst-Jan Camiel Wit
