The TAS group participates in national and international research projects funded by the European Commission, Swiss foundations, and institutional programs.
Projects
AutoMoTIF – Automation towards Multimodal Transportation and Integration of Freight
Funding: EU Horizon Europe (HORIZON-CL5-2023-D6-01)
Call: Safe, Resilient Transport and Smart Mobility services for passengers and goods
Grant Number: 101147693
TAS Team: F. Flammini
Research on automation and AI for multimodal transportation systems, focusing on freight integration, safety, and efficiency.
Website: automotif-project.eu
Academics4Rails – Building a Community of Railway Scientific Researchers
Funding: EU Horizon Europe (HORIZON-ER-JU-2022-ExplR-04)
TAS Team: F. Flammini
Building a community of railway scientific researchers and academia for EU-Rail and enabling a network of PhDs. The project connects academic institutions with industry partners across Europe.
Website: academics4rail.eu
REXASI-PRO – REliable & eXplAinable Swarm Intelligence for People with Reduced mObility
Funding: EU Horizon Europe (HORIZON-CL4-HUMAN-01)
Grant Number: 101070028
TAS Team: J.Guzzi, F. Flammini
The REXASI-PRO project aims to release a novel engineering framework to develop greener and Trustworthy Artificial Intelligence solutions. The project will develop in parallel the design of novel trustworthy-by-construction solutions for social navigations and a methodology to certify the robustness of AI-based autonomous vehicles for people with reduced mobility.
Website: rexasi-pro.spindoxlabs.com
PhDs EU-Rail – Extending the Rail Networks of PhDs in Europe’s Rail Joint Undertaking
Funding: European Commission, Horizon Europe
Grant Number: 101175856
Program: Europe’s Rail Joint Undertaking
TAS Team: F. Flammini
Extending and strengthening the network of PhD researchers working on railway innovation across Europe.
Website: academics4rail.eu/phdseu-rail
ToSMADeL – Towards Scalable Multimodal cAusal Deep Learning
Funding: Hasler Stiftung 2024
TAS Team: A. Termine
Collaboration: Computer Systems Institute, University of Italian Switzerland (USI)
Research on scalable causal deep learning methods for multimodal data, focusing on explainability and robustness.
Bridging the Gap: Empowering Teachers about AI Education
Funding: SNSF Agorà Grant
TAS Team: A. Termine
Collaboration: SUPSI Dipartimento Formazione e Apprendimento / University of Teacher Training
A project focused on AI education and empowering teachers to understand and teach artificial intelligence concepts.
B4EAI – Best for Ethical AI
Funding: SUPSI internal fund for exploratory research programme 2023–2024
TAS Team: A. Facchini
Exploratory research on ethical AI, focusing on human-centered machine learning, design principles, and social impact assessment.
MaLESCaMO – Machine Learning Explanation by Surrogate Causal Models
Funding: Hasler Stiftung 2023
TAS Team: A. Antonucci
Developing surrogate causal models to explain machine learning predictions, bridging the gap between black-box models and interpretable explanations.
EUonAIR – European University Alliance on AI Curricula
Funding: European University Alliance (Swiss partnership supported by MOVETIA)
TAS Team: A. Facchini
European collaboration on AI curricula development, smart university initiatives, and academic mobility programs.
Formal Reasoning on Neural Networks
Funding: Hasler Foundation
TAS Team: N. Sharygina
Research on formal methods for verifying neural network properties and providing formal explanations for AI decisions.
Cross theory rigorous program verification using Constrained Horn clauses
Funding: SNSF
TAS Team: N. Sharygina
Developing a novel, efficient CHC-based software verification framework that combines complementary solver technologies to enable scalable, precise automated verification of real-world programs, with a particular emphasis on Ethereum smart contracts.
Technical Committees, Societies & Working Groups
- Robust Machine Learning Interest Group, The Alan Turing Institute, UK
- ELLIS (European Laboratory for Learning and Intelligent Systems) network of excellence
- AI Readiness Expert Group under the AI for Good Innovate for Impact initiative, International Telecommunication Union (ITU)
- Working Group on FAIR Cities (Foster AI for Inclusive and Responsible cities), United Nations University
- IEEE C/AISC Framework for Defining and Evaluating AI Risk, Safety, Trustworthiness and Responsibility
- IEEE CIS Technical Committee on Ethical, Legal, Social, Environmental and Human Dimensions of AI/CI (SHIELD)
- European AI Alliance – Trustworthy AI in Practice
External Collaborations
- AI Legal & Strategy Consulting AG – legality and liability in AI systems
- Artificial Intelligence group and Cambridge Centre for AI in Medicine, University of Cambridge, UK – explainability in LLM for diagnostics and Graph Neural Network modeling (contact: Prof. Pietro Liò)
- Complex Systems & Security Lab, UCBM – University of Rome Campus Biomedico – AI for cyber-physical systems security
- Department of Philosophy, University of Bristol, UK – Philosophy of AI (contact: Prof. Emanuele Ratti)
- Digital Society Initiative, University of Zurich – digital ethics, trust in AI systems (contact: Dr Felix Gille)
- Digital Solutions, Alstom Italy – AI for driver fatigue detection and predictive maintenance in railways
- Engineering Resilient Systems (EReS), Linnaeus University, Sweden – safety integrity through self-adaptation
- Flycatcher, USI Startup Center – robust infrastructure anomaly detection (contact: Dario Mantegazza)
- H-UTokyo Lab, The University of Tokyo, Japan – data analytics for railway infrastructure resilience (contact: Dr. Hangli Ge)
- Intelligent Systems Ethics Group, EPFL – Trust in AI for healthcare (contact: Prof. Marcello Ienca)
- KnowMIS Lab, University of Salerno, Italy – situation awareness and decision support systems (contacts: Prof. Matteo Gaeta, Dr. Giuseppe D’Aniello)
- LAMIH UMR CNRS 8201, UPHF – Université Polytechnique Hauts-de-France – driver fatigue detection in semi-autonomous trains
- LEJEP, CY Cergy Paris Université – AI systems and product liability (contact: Dr. Marta Giuca)
- LUCI Lab, University of Milano – Trustworthy AI, Philosophy of AI (contact: Prof. Giuseppe Primiero)
- MobiliarLab, ETHZ – Ethics of AI (contact: Dr Andrea Ferrario)
- PICUSlab, University of Naples Federico II – Deep Learning for Railway Safety and Maintenance
- RCL: Resilient Computing Lab, University of Florence, Italy – trustworthy AI for resilient systems-of-systems
- ReCEPL – Research Centre of European Private Law, University Suor Orsola Benincasa – legal framework for autonomous vehicles
Z-Inspection® Initiative
The TAS research group is affiliated with the Z-inspection® initiative.
Z-Inspection® is a holistic process for evaluating the trustworthiness of AI-based technologies at different stages of the AI lifecycle. It focuses on identifying and discussing ethical issues and tensions through the development of socio-technical scenarios.
The process has been published in IEEE Transactions on Technology and Society and is listed in the OECD Catalogue of AI Tools & Metrics.
Funding Sources
- European Commission – Horizon Europe Programme
- Europe’s Rail Joint Undertaking – Railway Research
- Hasler Foundation – Swiss ICT Research
- Swiss National Science Foundation (SNSF)
- SUPSI – Internal Research Funds
- MOVETIA – Swiss Exchange and Mobility
Collaboration Opportunities
We are open to new collaborations with academic institutions and industry partners. If you are interested in working with us on trustworthy AI, autonomous systems, or related topics, please contact:
Prof. Francesco Flammini
Email: francesco.flammini@supsi.ch