Network science saw a booming interest in recent years. A network (or graph) is a data structure that allows to express complex relationships in a compact and elegant way. But is it possible to leverage hidden relationships in the network for machine learning purposes? Join us in the May edition of the Data & Drinks event series taking place at Xomnia's HQ in the heart of Amsterdam to know more about graph data and machine learning. This event is suited for network science enthusiasts, data scientists, MLEs and anyone who is curious about new exciting applications of machine learning. Our guest speakers will discuss the basics of the theory behind this new field and some of the most interesting applications, from automatic drone driving to recommender systems.
About the speakers
Machine Learning Engineer
Matteo is a machine learning engineer with a computer engineering and data science background. As a consultant at Xomnia, he worked for Adidas on supply chain optimization and is currently working with Tata Steel on creating a time series anomaly detector at full length of its lifecycle.
Bianca has a background in computer science and data science and an interest in networking problems and Natural Language Processing. At VodafoneZiggo, she worked on several data focused projects across different departments of the company, and currently works within the Advanced Analytics team focusing on customer churn modelling.
Assistant Professor in the Multimedia Computing Group
Elvin carries a Ph.D. degree in Signal Processing from TU Delft, and his research interests focus on graph signal processing, graph neural networks, graph-time analysis of network dynamics, network systems, and stochastic analysis of graph processes.