Category Archives: Student

Anastassia Vybornova has joined NERDS

We are excited to welcome Anastassia Vybornova to our research group!

Anastassia joins us as PhD student from Vienna, Austria. She recently completed her Master degree jointly supervised at KU, BOKU Vienna, and at ITU by Michael Szell, accomplishing an outstanding thesis on Identifying and classifying gaps in the bicycle network of Copenhagen. She has won a competitive, ITU-supported PhD grant and will therefore be with us for (at least) 3 years. 

Anastassia’s background is a crazy mix of physics, environmental science, and transcultural communication, and she is educated in complex systems and network science – all of which makes her fit perfectly into NERDS.

Her PhD topic at NERDS will be Network analysis of urban transport networks: for a green transition from car-centricity to cycling, with Michael Szell as supervisor, for which her ideal combination of skills from physics, sustainability science, and programming will be indispensable. To taste an hors d’oeuvre of her work, see her talk in two weeks at CRBAM.

Yanmeng Xing has joined NERDS

We are thrilled to welcome Yanmeng Xing to our research group!

Yanmeng joins us as a visiting PhD Student for one year. Yanmeng is a PhD student in Complexity Science at Beijing Normal University who won a prestigious Chinese fellowship to spend one year abroad.

At NERDS he will be working on Science of Science topics, specifically investigating the effects of the pandemic on scientific collaborations and career dynamics.

 

Funding for bicycle network analysis by the Danish Ministry of Transport

Today we received the happy news that the Danish Ministry of Transport is funding our project Netværksanalyse af den danske cykelinfrastruktur (“Network analysis of the Danish cycling infrastructure”): https://www.trm.dk/nyheder/2021/aftale-om-nye-cykelstier-i-alle-dele-af-landet/

This funding will allow us to hire cycling network and urban planning/spatial data expert Ane Rahbek Vierø for a 3-year PhD on the topic, to start Jan 2022, supervised by Michael Szell. Our bicycle network research so far has focused on urban bicycle networks, so this funding will finally allow us to widen our perspective to the regional and national scale. We are looking forward to welcoming Ane in January and to help improving the (already quite good but certainly not perfect) Danish bicycle network!

In more detail, our plans for this project are the following:

In this research project we will apply state of the art metrics and tools from network analysis on Danish open data bicycle infrastructure networks collected from e.g. OpenStreetMap, and additionally incorporate knowledge from cycling planners and mobility researchers, to develop a scientific, evidence-based framework to suggest where to add new network connections or other interventions for improving sustainable bicycle infrastructure. While there are generally good cycling conditions in Denmark, there are many areas that have a quite poor connectivity. Using access to everyday amenities as a baseline can also show that it is not enough to install bicycle lanes – they need to be in the right location and connect to the right places. This research will explore weighting the network according to different attributes to get a more detailed understanding of how connectivity and accessibility might vary for different types of cyclists (in line with Levels of Traffic Stress). We will also use this weighted network to examine cyclists’ access to everyday amenities and facilities, in order to, for example, identify areas where you cannot comfortably cycle to basic amenities (inspired by the 15-minute city). Further, we will explore the effect of high stress intersections on network connectivity for vulnerable road user demographics such as children, and incorporate the distribution of people and workplaces in the analysis. Finally, we aim to develop an interactive web mapping tool that visualizes the results and has the ability to run analyses based on individual demographic variables or preferences of cyclists.

Release of GrowBike.Net to explore growing urban bicycle networks

Recently we released GrowBike.Net, accompanying our preprint “Growing Urban Bicycle Networks“. The interactive data visualization platform was developed by NERDS Master students Cecilia Laura Kolding Andersen and Morten Lynghede as part of their thesis “Developing an Interactive Visualization of Bicycle Network Growth” with Michael Szell.

GrowBike.Net lets you explore how to grow bicycle networks from scratch in 62 cities worldwide. Choose a city and grow the bike network, connecting places efficiently step by step.

The growth process creates a cohesive bicycle network – something that every modern city should have. Studying these synthetic networks informs us about the geometric limitations of urban bicycle network growth and can lead to better designed bicycle infrastructure in cities. GrowBike.Net also allows to compare the grown networks with your city’s existing bicycle network.

Although our approach here is not yet aiming to provide concrete urban design solutions, it could be useful for planning purposes for easily generating an initial vision of a cohesive bicycle network – to be re-fined subsequently.

The platform also features a media page where over 1000 videos and plots can be downloaded: http://growbike.net/download

Have fun exploring growing bike networks in your city!

Open Positions

With NERDS winning grants and growing, we have added a Positions page at https://nerds.itu.dk/positions/, 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. 🤓

Obaida Hanteer’s PhD defense “A Practical and Critical Look at the Problem of Community Discovery in Multilayer Networks”.

On June 11th, virtually in front of the Examination Committee – headed by Barbara Plank (IT University of Copenhagen) and with members Vito Latora (Queen Mary University of London) and Luca Aiello (Nokia Bell Labs) – Obaida Hanteer successfully defended his PhD.
Well done!

Obaida’s research took first a practical approach to community detection in the context of multilayer networks (mainly working with social media data [link, link]) and then, it stepped back and looked with a critical eye at the tools and the (often implicit) assumptions made by multilayer community detection methods [link, link]. His research, as acknowledged by the committee, was brave – in challenging the status quo and the assumptions of many well-established methods – and compelling helping us remembering the importance of asking questions about the tools and the methods we use.

After his experience at ITU Obaida accepted another interdisciplinary challenge by joining the Novo Nordisk Foundation – Center for Basic Metabolic Research at the University of Copenhagen where he’ll be working on applying multi-layer networks concepts to the interactions of human’s gut microbiome. We wish Obaida all the best for his future career!