Valentina is currently finishing her master’s degree in Theoretical Physics at “La Sapienza” University of Rome, her hometown. During her studies, she developed a great interest in statistical mechanics, stochastic process, graph theory, networks, and complex systems. She studied and worked on developing algorithms on graphs to extract meaningful information from real systems. For her bachelor’s thesis, “Graph Analysis in Terms of k-Cores”, she studied the k-core decomposition of a real network, based on a mapping of the internet. During her master’s degree studies, she worked on networks of proteins, using algorithms on graphs to find hydrophobicity cores in a set of disordered proteins. She also worked on networks in the financial market, studying the correlations between the S&P indices before and after the 2008 financial crisis. She spent one year at “Denis Diderot” University of Paris, and then took a few years off, focusing on her other great passions: photography and the darkroom. During this time, she collaborated with the SHL Group (IT), which specializes in employment assessment and testing, and she created hundreds of physics tests and quizzes for them.
She loves spending time in the darkroom (when she can), developing and printing black-and-white photos. She finds it like a Zen exercise; “it is like sculpting the light”.
Project: What Does Popularity Tell Us about a Wikipedia Sub-Graph?
Wikipedia is a dense network with a hierarchical structure; it has an average of 550 million visited pages and 150 million visitors per day. Wolfram|Alpha has collected this data over time, and now we want to see how the diffusion of a user’s traffic in the network is related to the distribution of the links. We will have nodes that are related by a causal connection, but that don’t have a link that connects them. The correlations between pages imply a graph, what is its structure like? Does it have the same structure of the graph of the links, or a totally different structure?
Favorite Four-Color, Four State Turing Machine