As a Research Scientist at SINTEF’s Smart Data group, I work closely with Dumitru Roman on the Graph-Massivizer project. Here, we aim to develop a high-performance, scalable, and sustainable platform capable of processing and reasoning about extreme data through massive graph representation. By leveraging serverless computing, our project empowers various organizations to efficiently manage extreme data via massive graph programming and processing.
At the same time, I am involved in the enRichMyData project. In this initiative, we’re crafting a new paradigm for building rich, high-quality, valuable, and FAIR-compliant datasets, which are vital for the success of Big Data Analytics and Artificial Intelligence applications. We focus on streamlining the specification and execution of data enrichment pipelines, a critical but often time-consuming process which involves data discovery, cleaning, transformation, and integration. Our goal is to make these steps more accessible and cost-effective for a broad range of organizations, particularly those facing challenges in delivering suitable data due to a lack of usable tools or expertise in managing data enrichment pipelines.
In my capacity as an Associate Professor at the Oslo Metropolitan University, I’m part of the DD-MAC project. This project is committed to understanding the role of social media in conflict regions of sub-Saharan Africa. Here, I’m privileged to collaborate with Kristin Skare Orgeret, Bruce Mutsvairo, and Mirjam de Bruijn. Our efforts center on collecting empirical evidence from Ethiopia and Mali to understand the influence of digital communication on conflict development and mediation. By employing a multi-disciplinary approach and diverse methodologies, we study social media usage dynamics, the spread of disinformation and hate speech, the role of diasporas in conflicts, and the relationship between digital and traditional media in regions with low internet connectivity.
During my postdoc in Simula’s Department for High Performance Computing, I worked with Johannes Langguth, Xing Cai, and Fredrik Manne. Here, we focused on the development of a new computational framework for Graph Neural Networks with the goal of extending deep learning capabilities to unstructured data.
Under the supervision of Professor Odej Kao from the Technical University of Berlin, in collaboration with Carsten Griwodz, Pål Halvorsen, and Michael Riegler from the Simula Metropolitan Center for Digital Engineering, I received my PhD as part of Johannes Langguth’s UMOD project. This project centered on understanding and monitoring of digital wildfires or the rapid spread of online misinformation with the goal to identify harmful misinformation early, analyze its potential threat, and devise effective prevention and preparedness strategies.