Bridge Events
Organization of events that make the bridge between academia and the industry, e.g., demonstrators, conferences/workshops, or summits.
DeliverablesEvents
AIDI · CIDMA · Universidade de Aveiro
Applied research that reaches the industry.
AIDI turns business problems into models, studies, software, automation, edge devices, prototypes and demonstrable systems by combining mathematics, machine learning and advanced computing.
01Applied mathematics
02Machine learning
03Automation & edge
04Advanced computing
Purpose
From mathematics to industrial impact
The Research and Development Area for Industry (AIDI) is a thematic area within the Center for Research and Development in Mathematics and Applications (CIDMA) at the Department of Mathematics of the University of Aveiro.
Our mission is to bring mathematical and computational research closer to concrete business needs. We work on problems that require quantitative rigour, technology development, automation and validation in real-world settings.
The goal is not only to produce knowledge, but to turn it into decisions, code, devices, prototypes and transferable results, with data security and confidentiality treated as cross-cutting requirements.
How we engage
Six ways to turn a challenge into a results
Industrial in-House Intensive Training Courses
AIDI's teams go to your company and give a 8x3h specialized course, with data-driven applications.
DeliverablesCourses
Consulting and Studies
Quantitative analysis, mathematical modelling, statistics, optimisation and solution assessment for concrete business problems.
DeliverablesReport
From Theory to Computational Frameworks
Implementation of computational frameworks based on recent and relevant mathematical results.
DeliverablesReport + framework
Advanced Code
Scientific and industrial software, machine-learning algorithms, APIs, automation, edge devices and robust computational components, with data security considered from the architecture stage.
DeliverablesReport + software
Public–private funded projects
Coordination and participation in collaborative project work packages, from technical definition through validation and demonstration.
DeliverablesReports, prototypes and/or products
Data security
Data security from the design stage
Industrial data, intellectual property and operational knowledge require control. We design architectures around data minimisation and security, access control, local/edge processing where appropriate, isolated environments and controlled integration.
Data minimisation
Local / edge processing
Access control
See security principles →From research to operation
A lab designed to experiment, automate, integrate and demonstrate
We work across mathematical models, data, software, HPC, computer vision, IoT, automation, sensors and edge devices to shorten the distance between research and industrial adoption.
Explore our lab
Selected work
Projects, prototypes and applied systems
ILLIANCE W1.3 — Manufacturing analytics and AI
Applied R&D for heat-pump manufacturing, including the development and integration of data, machine-learning, diagnosis and demonstration components.
Scope
AIDI work included coordination and development activities around automated data analysis, process-factor modelling, computer vision, fault diagnosis, data storage and processing, forecasting and application integration.
ManufacturingAIIndustrial data
NEXUS W2.1 — Port logistics
Collaborative project focused on analytics and artificial intelligence for maritime-port logistics.
AIDI participation was framed as R&D coordination, connecting modelling, data and computational development to operational needs in the port ecosystem.
Maritime logisticsAnalyticsAI
NEXUS W2.2 — Multimodal networks
R&D project dedicated to multimodal logistics networks, combining data analysis, modelling and artificial intelligence to support decisions and service integration.
AIDI participated in coordination and technical development, focusing on transferring quantitative methods to complex logistics scenarios.
Multimodal logisticsOptimisationAI
NEXUS W5.4 — Last-mile delivery
Collaborative project focused on last-mile logistics, applying analytics, modelling and artificial intelligence to planning and operational problems.
AIDI participated in R&D coordination and in the development of quantitative and computational components for distribution scenarios.
Last mileOptimisationAnalytics
Applied outputs
From algorithms to devices and systems
IL3.2A · ILLIANCE
PEPELP Smart Workbench for Production-Line Trials
Operational reduced-scale production-line prototype at AIDI, combining object detection, human and hand movement tracking, edge sensing and retroprojection with visual feedback.
Edge devicesComputer visionPrototype
NXW2.1P03 · NEXUS
High-Fidelity Digital Twin for Container Terminals
Python-based digital twin using discrete-event simulation, battery charge/discharge models and optimisation to compare terminal scenarios and stress-test resilience across quay, yard and landside operations.
Digital twinSimulationOptimisation
NXW2.1P04 · NEXUS
Smart and Trustworthy Root Cause Analysis Tool for Maritime Ports
Web application combining machine learning and explainable AI for prediction, root-cause analysis and actionable recommendations, including SHAP, PDP and ICE visualisations and external weather data.
Machine learningExplainable AIRoot cause analysis
NXW5.4P02 · NEXUS
Green Cargo Quotation System
Multimodal freight quotation engine that evaluates direct and multi-leg alternatives using cost, CO₂ emissions and transit time, with interoperable APIs and provider plugins.
MultimodalCO₂Optimisation
Trust and governance
Intellectual property is part of the project design
AIDI is part of CIDMA and the University of Aveiro. Work follows the applicable UA rules and procedures, including intellectual property, confidentiality, contracting and knowledge valorisation.
Learn more →Start a conversation
Do you have an industrial problem that deserves a scientific approach?
Send us the context, the data available and the expected outcome. The first conversation is used to understand the problem and identify the most suitable engagement model.