Maksim Kitsak (Delft University of Technology) Geometric Representations of Complementarity-Driven Networks Abstract: Complementarity-driven networks are routinely embedded into latent metric spaces with the purpose of data analysis. We argue that these traditional geometric representations, where connected nodes are embedded close to each other in the latent space, are not applicable to complementarity-driven networks due […]
Quantifying the dynamics of impact in science and art (Remote Colloquium)
(Event in Italian) Giovedì 11 febbraio 2021, con inizio alle ore 15:00, in occasione dell'International Day of Women and Girls in Science, il Dipartimento di Fisica e Astronomia "Ettore Majorana", in collaborazione con il Centro Siciliano di Fisica Nucleare e Struttura della Materia #CSFNSM, ospiterà (online) l'incontro con due scienziate per esplorare percorsi di donne […]
Luca Aiello, ITU (NERDS): Towards Health Surveillance with Social Media In today’s heavily interconnected world, health crises develop rapidly and spread afar. Health crises burden not only people’s biological health but also their psychological and social spheres. By monitoring the population’s behavior and health conditions, public health bodies can plan prevention campaigns, promptly deploy targeted […]
Project Market for Research Projects for K-CS and K-SD students at ITU
The NERDS seminar continues Wednesday (22/09/2021) with an exciting talk by Helge Pfeiffer, Assistant Professor at ITU, titled: “Everything is Connected - Leveraging Graphs in Software Engineering Research”. Please join us from 12:30-13:30 in person at EHK-2F12 (or via Zoom - regular link - for virtual attendance). The presentation abstract and presenter’s bio are below. […]
TITLE: Quantifying biases in science ABSTRACT: Every day our life is made easier by efficient measures and algorithms that search and rank scientific information. Yet, these algorithms have an issue: they are trained on citations, which are ingrained with human biases. Therefore the output is inherently biased too, creating inequalities, raising concerns of discrimination, […]
Analysing cyclist behavior at signalized intersections using computer vision Artificial intelligence, in particular deep learning and computer vision, is a promising new tool for automated video analysis in traffic studies. It allows for facilitated extraction of detailed data from video recordings at higher efficiency and lower costs, improved precision of obtained data, and reduced errors […]