Category Archives: Student

Student promotions

We have two student promotions to celebrate 🎉

First, Elisabetta Salvai has become a PhD student on Jan 1st 2025 at SODAS and the AI Pioneer Centre, supervised by Roberta Sinatra, after having visited us for many months. Her work centers around applying complex systems methods to uncover and explore bias existing in data and machine learning algorithms. She is currently working on the study of fairness in rankings of networks with binary attributes.

She will continue to visit us regularly. Congratulations Betta!

Second, Anastassia Vybornova has submitted her PhD Thesis by Dec 31st 2024, and since Jan 1st 2025 she is formally Postdoc with us for 3 more months until her PhD defense end of March. So, the real celebration for her will be then, but it is nice that she stays with us for 3 more months. In this time, Anastassia keeps finishing up some bicycle network and sustainable mobility papers.

Anders Aagaard Kristensen has joined NERDS

At NERDS we welcome our latest member: Anders Aagaard Kristensen!

Anders joins us as PhD student, coming from the University of South Denmark, where he was working on machine learning methods.

His PhD project will be about the use of deep learning and generative models to understand leaves of absence in work data. The idea is to predict, simulate and, ultimately, make interventions, so that workers will have less taxing working schedules, leading to fewer leaves for sickness reasons.

Anders will be working jointly with NERDS and the National Research Center for Work Environment (NFA), which finances his fellowship and provides the data. He will be supervised by Michele Coscia at NERDS.

NERDS at the D3A Conference

NERDS group made a strong return to the second edition of the D3A conference, held in Nyborg. Our presence across the sessions was extensive, starting from Toine welcoming us in the opening session.

The workshop “Networks, Data, Society, and AI”, organized by Vedran, Lasse, Anders, Anders, and Arianna, sparked inspiring dialogue on AI’s impact on society from diverse perspectives, and brought together an eclectic mix of speakers from industry, academia, and journalism.

Anastassia co-led the workshop “From Classroom to Career: Data Science Degrees and Early Career Opportunities,” which provided valuable guidance for young data scientists navigating the transition from academic studies to professional paths. (We were especially pleased to see Luca as one of the invited speakers here, adding an extra point of view to the session!)

Clément contributed a visually engaging poster on urban bicycle network planning, sparking plenty of conversations about sustainable city design. Mesut shared his latest research on fair recommendations in job markets in the “Fair Division – Economics, Computational Social Science, and AI” session.

All in all, this year’s D3A conference was a fantastic blend of intellectual exchange, practical workshops, and community building. It’s exciting to see the role NERDS is playing in these developments, and we’re already looking forward to bringing even more insights to next year’s event!

Carlson Büth wins VCD Award for his Master thesis

Carlson Moses Büth, who visited us last year from University of Münster, Germany, won the VCD Award (1st place Special Award) for his master thesis

From Gridlocks to Greenways: Analyzing the Network Effects of Computationally Generated Low Traffic Neighborhoods

that he wrote at ITU, co-supervised by Anastassia+Michael@NERDS. We congratulate Carlson to this achievement! 🎉


Photos from the VCD Award Ceremony by Jan Zappner

The VCD is the “Verkehrsclub Deutschland”, a major non-profit association and traffic club in Germany that is committed to a socially and environmentally friendly transport transition towards mobility for all road users.

Over the course of his master thesis Carlson also initiated the development of the Python package superblockify which we published recently within the JUST STREETS EU Horizon project we are part of. See: superblockify.city, its Github repository, and the accompanying paper at JOSS.

NERDS at ASONAM’24

A bunch of nerds posing in front of the asonam conference logoLuigi Arminio wins the asonam best phd dissertation award

NERDS’ summer sheneanigans continue at ASONAM, in the beautiful and sunny Calabria. Lucio La Cava and Alessia Galdeman held a tutorial on Mining, Modeling, and Analyzing Decentralized Social Media. Alessia Antelmi organized the HyperSci workshop on Theory and Applications of Hypernetwork Science. Luigi Arminio and Daniele De Vinco presented at the PhD Forum. Luca Aiello fulfilled his duties as the conference Program Chair. Luigi won the prize for the best PhD forum contribution!

Welcome Lasse, the latest NERDS PhD Student!

NERDS keeps growing! This month we’re welcoming Lasse Alsbirk as our latest addition to the team!

Lasse is a co-financed PhD student and at the center of a multi-partnered research project! He will work at the intersection of the Danish Police (financial crimes section), the AI Pioneer Center, and NERDS @ ITU. His project will focus on the application and development of network science tools to fight financial crimes. He has valuable abroad experience, having received his master degree in Israel and he will be with us for four years.

Welcome, Lasse!

Three new NERDS papers with our master students: Failing our youngest, superblockify, women on wikipedia

We have 3 new papers that came out over the summer so far, on diverse, very interesting topics. The first authors in all 3 of these papers were our master students – showing how impactful good master projects can be:

  1. Failing Our Youngest: On the Biases, Pitfalls, and Risks in a Decision Support Algorithm Used for Child Protection, by T.M. Hansen, R. Sinatra, and V. Sekara, published at FAccT’24
    Through a freedom of information request, we accessed a new algorithm of Danish child protection services to aid caseworkers in identifying children at heightened risk of maltreatment, named Decision Support, and conduct an audit. We find that the algorithm has significant methodological flaws, suffers from information leakage, relies on inappropriate proxy values for maltreatment assessment, generates inconsistent risk scores, and exhibits age-based discrimination. Given these serious issues, we strongly advise against the use of this kind of algorithms in local government, municipal, and child protection settings, and we call for rigorous evaluation of such tools before implementation and for continual monitoring post-deployment by listing a series of specific recommendations.

    See also our accompanying policy paper published earlier.
  2. superblockify: A Python Package for Automated Generation, Visualization, and Analysis of Potential Superblocks in Cities, by C.M. Büth, A. Vybornova, and M. Szell, published in The Journal of Open Source Software (JOSS)
    superblockify is a Python package designed to assist in planning future Superblock implementations by partitioning an urban street network into Superblock-like neighborhoods and providing tools for visualizing and analyzing these partition results. A Superblock is a set of adjacent urban blocks where vehicular through traffic is prevented or pacified, giving priority to people walking and cycling. The potential Superblock blueprints
    and descriptive statistics generated by superblockify can be used by urban planners as a first step in a data-driven planning pipeline for future urban transformations, or by urban data scientists as an efficient computational method to evaluate potential Superblock partitions.


    The software is available at: superblockify.city
  3. Traces of Unequal Entry Requirement for Illustrious People on Wikipedia Based on their Gender, by L. Krivaa and M. Coscia, published in Advances in Complex Systems
    In this paper, we study issues of fair gender representations for people in history noted by multiple language editions of Wikipedia: are women underrepresented on Wikipedia? We do so via a combination of natural language processing and network science. Our results indicate that there is indeed a higher bar for women to have their own biographical page on Wikipedia: women are only included when they have more significant connections than men to the rest of the network. There are visible effects of the initiatives Wikipedia is taking to fix this issue, showing that the gap is narrowing, which validates our interpretation of the data.

NERDS at IC2S2’24 in Philly!

A tactical squad of 6 NERDS attended this year’s IC2S2 in Philly, and presented 9 works:

We are grateful to the organizers for the great event, and we look forward to IC2S2 coming back to scandinavia in 2025!

New NERDS paper on urban morphology & street network simplification

A new NERDS co-authored paper is out open-access in the Journal of Spatial Information Science (JOSIS): A shape-based heuristic for the detection of urban block artifacts in street networks, by Martin Fleischmann & Anastassia Vybornova.

a) Bridge, Amsterdam; b) Roundabout, Abidjan; c) Intersection, Kabul; d) Motorway, Vienna. Polygons classified as face artifacts are shown in red, and the OSM street network (without service roads) is shown in black. Face artifacts are polygons enclosed by street network geometries (in the case of OSM, lane centerlines) that do not represent morphological urban blocks, but instead are a result of detailed transportation-focused mapping of the streetscape. Map data (c) OpenStreetMap contributors (c) CARTO

a) Bridge, Amsterdam; b) Roundabout, Abidjan; c) Intersection, Kabul; d) Motorway, Vienna. Polygons classified as face artifacts are shown in red, and the OSM street network (without service roads) is shown in black. Face artifacts are polygons enclosed by street network geometries (in the case of OSM, lane centerlines) that do not represent morphological urban blocks, but instead are a result of detailed transportation-focused mapping of the streetscape. Map data (c) OpenStreetMap contributors (c) CARTO

We propose a cheap computational heuristic for the identification of ‘face artifacts’, i.e., geometries that are enclosed by transportation edges but do not represent urban blocks. Sounds cryptic? Just check out the picture – the artifacts (in red) might be painfully familiar to anyone who has worked with street network data. Our proposed heuristic, implemented open-source in momepy, is the first step towards a fully automated street network simplification workflow. Next steps coming up – stay tuned!

NERDS at ICWSM’24

This week, Arianna and Anders are representing NERDS at ICWSM in Buffalo, NY, with two freshly-published papers.

  1. Narratives of Collective Action in YouTube’s Discourse on Veganism, by A. Pera and L.M. Aiello. ICWSM’24.

    We studied vegan narratives on YouTube through the lens of a theoretical framework of moral narratitves. We studied how different narratives elicit different types of responses from video commenters, and found that videos advocating social activism are the most effective at stirring reactions marked by heightened linguistic markers that relate to collective action.
  2. The Persuasive Power of Large Language Models by A.G. Møller and L.M. Aiello. ICWSM’24.

    Can artificial agents interact with each other to reproduce human-like persuasive dialogue? And do the arguments they generate sound persuasive to humans? We used Llama2 to test different persuasion strategies, and asked humans to rate them. We found that arguments that included factual knowledge, markers of trust, expressions of support, and conveyed status were deemed most effective according to both humans and agents.