Simone Centellegher

📢 Do you want to join our group? We opened **two** calls for a fully funded PhD. Details are in the image and at the following links.

Calls: iecs.unitn.it/education/ad...
PhD Details: iecs.unitn.it/education/ad...

Deadline: August 22nd, 2025, hrs. 04:00 PM (CEST)

We introduce a real-time method to infer individual unemployment using GPS trajectories and survey data.
By analyzing mobility patterns of ~1 million individuals before and after job loss we reveal a sustained contraction in exploration that deepens with time since job loss.

🚀Job loss disrupts individuals’ mobility and their exploratory patterns🚀
Thanks to a great collaboration with @marcodena.bsky.social, @marcotonin.bsky.social, Bruno Lepri and @lorenzolucchini.bsky.social our latest study is finally out in iScience!

So excited to see this come together! 🎉

Our latest study explores the interplay between science and misinformation in public debates during COVID-19 🔍 arxiv.org/abs/2507.01481

👇Take a look

Latest out in PNAS!! Comparative evaluation of behavioral epidemic models using COVID-19 data. Amazing collaboration with @ngozzi.bsky.social and @alexvespi.bsky.social www.pnas.org/doi/10.1073/...

Forecasting Seasonal Influenza Epidemics with Physics-Informed Neural Networks Accurate epidemic forecasting is critical for informing public health decisions and timely interventions. While Physics-Informed Neural Networks (PINNs) have shown promise in various scientific domain...

Forecasting Seasonal Influenza Epidemics with Physics-Informed Neural Networks arxiv.org/abs/2506.03897

Congrats Giovanni!!

New paper alert. "More is different" & the LLMs.
LLMs are usually studied in isolation. But what happens when they start interacting? We explored this by looking at their collective behaviour.
Work with @ariel-flint.bsky.social and @lajello.bsky.social
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We present Epydemix: open-source python package for all stages of epidemic modelling: from models' definition to their calibration via ABC methods. Website: www.epydemix.org. Paper: www.medrxiv.org/content/10.1.... High level summary: www.epistorm.org/activities/e...

Lecturer in Applied Mathematics at City St George’s, University of London An academic position as a Lecturer in Applied Mathematics is being advertised on jobs.ac.uk. Click now to find more details and explore additional academic job opportunities.

*Permanent* position in Applied Mathematics at City. We are - of course - particularly interested in profiles in Computational Social Science, Network Science, Data Science, and related fields. The application deadline is June 1st.

www.jobs.ac.uk/job/DMY889/l...

🎉 New paper out in PNAS! 👇👇👇

Happy to see our work, "Socioeconomic disparities in mobility behavior during the COVID-19 pandemic in developing countries", out in the EPJ Data Science special issue "Data for the Wellbeing of Most Vulnerable".

bit.ly/socioeconomi...

Thanks to the editors and the amazing team for the hard work!

Stylized map of Detroit (MI) showing the highway network, and the network of social connections between urban residents. The connections intersecting highways are sparser than elsewehere. Image credit Karo Berghuber (Insta: @kariot.lines)

"Urban Highways Are Barriers to Social Ties" out on PNAS!
The 1st large-scale measure of how highways weaken social connections between the communities they separate. This barrier effect is strong in the 50 largest US cities--especially for low-income Black communities.
www.pnas.org/doi/10.1073/...

If education is expensive, try ignorance.

Using human mobility data to quantify experienced urban inequalities - Nature Human Behaviour Xu et al. review applications of urban mobility behaviour data and propose a temporal bipartite network that reveals mobility patterns between people and places. It helps to track urban inequalities i...

🎉 Today, our perspective on "Using mobility data to quantify experienced urban inequalities" is finally published in Nature Human Behavior. I am honored to be listed among many stellar coauthors and thankful for their valuable insights.
www.nature.com/articles/s41...

Most tests for LLM biases use questionnaires, asking the model to generate a stance towards a given topic. Sadly, biases can re-emerge when the model is used in the application context. We show that apparently unbiased LLMs exhibit strong biases in conversations.
Preprint: arxiv.org/abs/2501.14844