Decentralized Data Mining & Information Network Analytics
Royal Institute of Technology (KTH), Sweden
Prof. Šarūnas Girdzijauskas
Role Discovery, Analysis of Higher-Order Networks, Machine Learning Networks, Distributed Systems
I am an Early Stage Researcher for the Marie Skłodowska-Curie Actions (MSCA) founded project RAIS: Real-Time Analytics for Internet of Sports. I am currently a Doctoral Student at the Division of Software and Computer Systems (SCS) of the School of Electrical Engineering and Computer Science (EECS) at Kungliga Tekniska Högskolan (KTH) in Stockholm, Sweden.
I earned my Bachelor of Science in Engineering of Computing Systems at Politecnico di Milano (PoliMi) in 2017. I was then accepted to the EIT Digital Master's Programme in Data Science, with a focus on innovation and enterpreneurship. As part of the double master's degree programme, I spent the first year at PoliMi studying Computer Science and Engineering and the second year at KTH studying ICT Innovation.
Data Mining, Machine Learning, Analysis of Networks
Networks are popular data structures that embed relationships between entities in edges between nodes. Although they have many applications, including, but not limited to, Internet of Sports, it is hard to extract insights into the roles of the nodes. Roles are able to capture the higher-order connectivity patterns of the nodes and thus to emphasize the behaviors of the entities.
Within RAIS, I am focusing on role discovery, which has many applications ranging from data anonymization to online anomaly detection. Particularly, I will research into possible ways of carrying out an analysis of roles in networks in a distributed manner.
Currently, I am reviewing the topic of role discovery in order that strengths and weaknesses in current methods may be recognized.