Title: Human-centred collaboratIVE MultI-ageNt framework for accelerating software Development and maintenance

Grant agreement ID:  101189745 

Dates: January 2025 - December 2027

Goal: Promote responsible software engineering practices that accelerate all stages of the software development lifecycle, leveraging novel AI and data technologies to design and develop an adaptive LLM-based multi-agent framework.

more information...

Title: Continuous and Efficient Evolution of ML Systems: an Ecosystem-driven Approach (MLEvol)

Identifier:  PID2024-156019OB-I00

Dates: September 2025 - August 2029

Main Goal: To develop Software Engineering (SE) methods, practices and tools to foster the continuous and efficient evolution of MLS and the subsequent adaptation of their MLOps life cycle considering the highly dynamic ML ecosystem.

more information...

Title: FIREPRIME

Dates: February 2024 - January 2026

Consortium: UPC (Universitat Politècnica de Catalunya), PCF (Pau Costa Foundation), RISE (Research Institutes of Sweden), UOC (Universitat Oberta de Catalunya), BOKU (University of Natural Resources and Life Sciences, Vienna)

GESSI main role(s): Development of FIREPRIME App

GESSI Participants: Marc Oriol, Lidia López, Xavier Franch, Huihui Xu

Description: Wildfires are increasingly problematic in Europe, with recent unprecedented events causing extensive damage near Wildland-Urban Interface settlements. These fires pose complex civil protection challenges, highlighting a lack of awareness and preparedness among affected communities. Inspired by successful international frameworks like Firewise and FireSmart, FIREPRIME aims to establish an EU-wide program promoting fire resilience in WUI communities. It will develop a toolkit including a smartphone app, guidelines, and educational materials, aimed at enhancing wildfire resilience in three critical targets: households, communities, and infrastructure. It will be tested in three European regions: Barcelona (Spain), Tyrol (Austria), and Gothenburg (Sweden). The project prioritizes inclusivity and collaboration with local stakeholders to ensure responsiveness to diverse needs. Lessons learned will inform a strategic plan for sustainable project handover and exploitation in other fire-prone European regions.

more information ...

Title: PRAISE - Platform for Creating Energy-efficient AI Systems

Identifier:  CPP2024-011447

Program: Proyectos en colaboración público-privada, Plan Estatal de Investigación Científica, Técnica y de Innovación 2024-2027, MICINN

Dates: 2024-2027

Technical Coordinator: Xavier Franch

Project total funding: 1.057.051,02 Euros. UPC funding: 317.119,02 Euros.

Title: Cost Optimization of Artificial Intelligence Systems with Sustainable Practices (GAISSA-Optimizer)

Funding Entity: Producte (AGAUR), 2025-PROD-00236.Technology transfer.

Dates: 16/9/2025 to 15/3/2027.

Participation: Silverio Martínez-Fernández (principal investigator), Santiago del Rey (entrepreneurial scientist), Vincenzo De Martino, Joel Castaño, Alexandra González, Violeta Bonet

Transfer Manager: Marta Villarroya

Mentor: Andreas Jedlitschka

more information ...

Title: AgileDashboard

Funding Entity: Producte (UPC), PROD-UPC-2024-04. Technology transfer.

Dates: February 2025 - December 2025.

Participation: Carles Farré, Xavier Franch (principal investigator), Lidia López, Marc Oriol

Description: The project aims to create a dashboard that consolidates development and agile process metrics into scientifically validated strategic indicators, using AI-based forecasting, alerts, and gamification to support teams in applying agile best practices and making informed decisions that improve performance, communication, and sustainability.

Title: Learning Dashboard

Funding Entity: UPC,  2021 Call for Educational Innovation Projects

Dates: Started on September 2021

Participation: Project coordinators Prof. Carles Farré and Prof. Xavier Franch

Goal: To gather data generated by the software development tools used by students, mainly code version management and project management tools, in order to define learning metrics, factors, and indicators that are integrated, visualized, and monitored in an analytic dashboard.

more information...