We are offering two fully funded PhD positions within our research group: C4 - Modeling and Simulation of Urban Digital Twins

The position is hosted directly within our research group, ensuring that PhD candidate is fully integrated into a collaborative environment and actively involved in daily research activities.

Application deadline: 27 August 2026

For more details, please refer to the link below.

A new declarative API lets you define a complete model with typed inputs, outputs, and computation logic in a few lines.

This release also introduces:

• Typed model contracts (@inputs, @outputs, @functions)
• Scenario-based what-if analysis
• Automated exploration of thousands of parameter combinations
• Incremental and resumable evaluations
• Faster execution of large models with multiple decision paths
• A cleaner separation between model definition and evaluation
  
  The goal is simple: spend less time on framework boilerplate and more time building models.

Traffic sensors generate a continuous stream of data that cities rely on for monitoring and planning — but sensor failures and maintenance windows regularly break that stream, leaving missing values that can bias analyses and undermine downstream models.

Arianna Burzacchi from the MoST Unit at Fondazione Bruno Kessler presented a new approach to this problem at SIS-FENStatS 2026, held at Sapienza University of Rome (June 22–25, 2026). The key idea: not all missing values are the same, and treating them differently makes a real difference.

The work by Marko P'yeshchyk, Arianna Burzacchi, and Marco Pistore is available as a conference paper, alongside an open-source implementation at github.com/fbk-most/ts-missing-values.

MoST joined the Digital Society center at FBK to present four of our recently started projects advancing Digital Twin technology—with our distinctive focus on social dynamics and participatory science.

Our team and collaborators unveiled:

• TERRAE — Digital Twins-Enabled Rural Resilience in Agriculture and Forestry
• HARMONIE — Health Assessment Refinement for Mitigating Noise and Air Quality Effects
• AIxPA 2026 — Artificial Intelligence for Public Administrations
• ECHO TWIN — Edge-Cloud-HPC Optimized Twins Based on Workflow-Enhanced Inference Networks

These initiatives explore how digital technologies can address real-world challenges—from rural sustainability to air quality monitoring to public sector innovation. The common thread? Bridging computational sophistication with practical, human-centered outcomes.

We're genuinely excited about what lies ahead and look forward to sharing progress with you!

Andrea Mauro joins the MoST research unit as an intern, where he will contribute to research on policy impacts in Civic Digital Twins.

His work will focus on statistical and machine-learning algorithms to identify policy effects on the urban mobility.

We recently hosted Prof. Andrew Mondschein, University of Virginia and Visiting Scholar at the University of Bologna, for a seminar exploring urban mobility as a human experience. His presentation highlighted the need to move beyond traditional traffic and accessibility metrics to better understand how streets and urban environments influence attention, emotions, cognition, and wellbeing.

The seminar also sparked discussion on the role of civic digital twins, including the Bologna Digital Twin, in supporting more human-centered approaches to transport planning.

We thank Prof. Mondschein for his inspiring contribution and looks forward to future opportunities for collaboration and exchange!