Research interests

My field of study is at the interaction of Machine Learning, structured data analysis (graphs, time series) and optimization. A common theme of my research consists in analyzing the impact of structure in data (spatial proximity, time dependency or item correlations) and using it for ML purposes (training large-scale machine learning models, improving low-dimensional representations of graphs, identifying patterns from malware traces, or predicting the outcome of information cascades).