Postdoc wanted on Science of Science and Algorithmic fairness

We are looking for a postdoc in data/network science, to start in fall 2021: Read more and apply at the official call page

The postdoc will work in the NEtwoRks, Data, and Society (NERDS) group at IT University of Copenhagen with Roberta Sinatra on the topic of Science of Science and Algorithmic fairness. The group currently focuses on quantitative projects at the boundary of computational social science and network science, including science of science, social dynamics, urban sustainability, data visualization, and fundamental questions in complex systems.

The postdoc position is part of a large project aimed to uncover the bias mechanisms that drive scientific impact, and to use them to create fair algorithms. The project will involve the analysis of large-scale datasets, running controlled experiments, and modelling social dynamics in science. Our priority is to attract technically strong researchers who are interested in asking bold, new questions with data. The team executing the project is composed of the PI, two postdocs, and one PhD student.

The position is in the NERDS group in the Computer Science Department. Both salary and working conditions are excellent. The group is a down-to-earth and fun place to be. Copenhagen is often named as the best city in the world to live in, and for good reasons. It’s world-renowned for food, beer, art, music, architecture, the Scandinavian “hygge”, and much more. In Denmark, parental leave is generous, and child-care is excellent and cheap.

The position is a full-time position, funded for 24 months.  See more details and apply in the official call. If you are interested feel free to reach out to Roberta Sinatra at

New Paper on Sampling Social Media + Call for Abstract @ Networks21 Satellite

NERDS member Michele Coscia is having a busy March!

He published a new paper in the TKDD journal titled “Noise Corrected Sampling of Online Social Networks“. The paper focuses on a new way to perform topological network sampling, i.e. to explore a network by following its edges such that the explored (sub)network is as similar as possible to the whole structure. In this paper, the method uses a Bayesian framework to estimate the amount of novel information a new connection brings about into the currently explored sample.

He is also organizing a satellite for the Networks21 conference. The satellite is titled “Complex Networks in Economics and Innovation”. The organizers are looking for contributed abstracts on network applications on research about economic development and innovation. Read more on the official website, or submit your abstract to the submission site.

Bojan Kostic has joined NERDS

We are thrilled to welcome Bojan Kostic to our research group!

Bojan joins us as Postdoc. He previously worked at the Technical University of Denmark (DTU), in the Machine Learning for Smart Mobility group (MLSM), on the application of Data Science and Machine Learning in transport and mobility.

At NERDS he will be applying his skills in traffic data analytics and video processing using machine learning and computer vision, to deepen our understanding of interlinked human behavior in urban traffic.

NERDS paper out: How unique is your app fingerprint?

We have a new exciting paper out: Temporal and cultural limits of privacy in smartphone app usage by Vedran Sekara et al. published in Nature Scientific Reports, asking:

How unique is your app fingerprint?The paper looks into which apps people use and creates app-fingerprints for 3.5 million individuals. Similar to forensic science where you need 12 points to distinguish between fingerprints we ask how many apps do we need to distinguish between two users? We find people’s smartphone app behavior is very unique and 3 apps are enough to identify more than 90% of all individuals. But app-fingerprints change over time and are different between countries. We find that people have more unique app-fingerprints during summer because we use more unique apps, and Americans have the most unique fingerprints (need the fewest apps to identify them) while Finns are the least unique (need more apps to identify their fingerprint). Why is this important? Because the work highlights problems with current policies intended to protect user privacy and emphasizes that policies cannot directly be ported between countries.

Open Positions

With NERDS winning grants and growing, we have added a Positions page at, currently featuring 2 open calls at ITU that are directly relevant to us as they can lead to NERDS positions. If your research overlaps with ours and you are interested get in touch!

1) PhD Open Call 2021

The ITU-wide PhD Open Call 2021, deadline March 10th, features 2 potential PhD projects by NERDS members:
1) Michael: Network analysis of urban transport networks for a green transition from car- centricity to cycling
2) Michele+Luca: Modelling Complex Social Systems to Handle Disinformation

2) Asst./Assoc. Professor in data science and machine learning

This computer science department wide call, deadline March 29th, is looking for applicants in any of these areas, including NERDS topics:

  • Data mining, large-scale data analysis, data visualization
  • Machine learning
  • Natural language processing
  • Network science, analysis of large (social and other) networks
  • Bioinformatics
  • Computer vision, signal analysis
  • Computational social science
  • Fairness and accountability in data science and machine learning
  • Statistics, computational statistics, probabilistic modelling

Watch this space and stay tuned for more. 🤓

International Day of Women and Girls in Science 2021

On yesterday’s International Day of Women and Girls in Science, Roberta took part in a corresponding event organized by her alma mater, University of Catania, Dipartimento di Fisica e Astronomia “Ettore Majorana”, delivering a keynote talk on the topic and on her research.

The event was in Italian, it can be watched here:

Link to event:


Luca Maria Aiello has joined NERDS

We are thrilled to welcome Luca Maria Aiello to our research group!

Luca joins us as Associate Professor, coming from industry. He conducts interdisciplinary research at the intersection of computational social science, digital health, network science, and urban informatics, using large-scale digital data to quantify people’s well-being and build systems that can improve it. Currently, he is focusing on Natural Language Processing to quantify social and psychological experiences from text.

He had a few past professional roles: Senior Research Scientist at Bell Labs in Cambridge, UK; Research Fellow of the ISI Foundation in Turin; Research Scientist at Yahoo Labs Barcelona and London; visiting scientist at the Center for Complex Networks and Systems at Indiana University.

Check out Luca’s cool Webpage and find him on Twitter.

Roberta Sinatra wins Villum Young Investigators grant

Roberta Sinatra was one of the 19 recipients of this year’s Villum Young Investigators grant!

The Villum Young Investigator programme (YIP) focuses on attracting and retaining talented young Danish and international researchers at Danish universities. The aim is to support the development of high-level international research environments in the universities.

Roberta’s winning proposal was awarded with DKK 6M:
Bias Explained: Pushing Algorithmic Fairness with Models and Experiments 

Algorithms for ranking scientific information have an issue: they use citations, which are ingrained with human biases. Therefore, their output is also biased, creating inequalities and raising concerns of discrimination. This project aims to uncover the mathematical bias mechanisms that drive different citation trajectories given same quality, and to use them for creating fair algorithms.

We are overwhelmed with joy for Roberta’s success, and are looking forward to her future groundbreaking research. The grant will allow the recruitment of one PhD student and two postdocs – so stay tuned for upcoming job calls.


The Atlas for the Aspiring Network Scientist

In the past two years,  NERDS member Michele Coscia has been working on a textbook for the Network Analysis class he teaches at ITU. This “Atlas for the Aspiring Network Scientist”, has now reached version 1.0, and 760 pages, and is available for anyone to read for free:


The Atlas aims at being broad, not deep, to be a pointer to the things you need to know about Network Science rather than a deep explanation of those things.

Consider this a v1.0 of a continuous effort. There are many things to improve: language, concepts, references, figures. Please contact Michele with any comments.

Michele also plans to have interactive figures on the website in the future. Version 1.0 was all financed using his research money and time. For the future, Michele will need some support to do this in his free time. If you feel like encouraging this effort, you can consider becoming a member on Patreon.

Find a more detailed explanation of The Atlas for the Aspiring Network Scientist on Michele’s page:

Explore multilayer networks in Virtual Reality

Click for a video demo of MNET-VR

Click for a video demo of MNET-VR

Multilayer networks are an increasingly popular way to model complex relations between various types of entities and they have been applied to a large number of real-world data sets. Their intrinsic complexity makes the visualization of this type of network extremely challenging and still an open research area. To help the visual exploration of complex multilayer network structures, today we are releasing MNET-VR. MNET-VR is the output of a research project carried on with Leonard Maxim and supported by the Digital Design Department. MNET-VR explores the potential of Virtual Reality to visualize this type of network structure.

MNET-VR offers basic functions to visualize and filter multilayer network structures. MNET-VR does not offer, at this stage, the possibility to manipulate the network layout. A proper 3D layout of the network can be obtained through the R package multinet. While its primary goal is to explore multilayer networks, MNET-VR can also be used to visualize single layer networks using igraph and multinet. The export of of the files for visualization is done through two simple R functions that we make available on the website. MNET-VR is designed for Oculus Rift/Oculus Quest with Link.