INESC TEC
INESC TEC
INESC TEC
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TSP2Net

INESC TEC

About the Project

Acronym

TSP2Net

Responsible

Vanessa Freitas Silva

Status

active

Starting Date

January 1, 2025

Ending Date

January 31, 2026

Effective End Date

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Global Budget

€49,229.40

Funding

€49,230.00

Website

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Datasheet

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Dissemination

INESC TEC has a unique and differentiating management model, improved over its 35 years of history. Reflecting its unique position between academia and industry, the management at INESC TEC carefully balances, in a hybrid model, the academic culture of scientific freedom and dialogue with a culture of efficiency and responsibility in management.

Associated Centres

Advanced Computing Systems

The Centre for Advanced Computing Systems (CRACS) strives for scientific excellence in the areas of programming languages, parallel and distributed computing, information mining, security and privacy, focusing on developing scalable software systems for multidisciplinary applications in Engineering, Life Sciences, Social Networks, the Internet of Things, and more. We explore deep theoretical and practical knowledge related to the design and development of programming languages and middleware for advanced computing systems - including parallel, distributed, high-performance, cloud, wireless, and IoT systems -, while mastering the concepts and methodologies that underpin trust, privacy, and security in computing systems. Our research environment brings together talented junior and senior researchers, most of whom are university lecturers. Together, they form the critical mass and scientific expertise required to fulfil our mission.

Advanced Computing Systems

Artificial Intelligence and Decision Support

Our Laboratory of Artificial Intelligence and Decision Support (LIAAD) conducts research in the fields of Artificial Intelligence, Machine Learning, Data Science, and Modelling. These areas are cross-cutting and apply to all sectors of society and the economy. The vast amounts of data being collected, alongside the ubiquity of digitalisation and sensorisation, are increasingly creating opportunities and challenges for automating decision support. The combination of Machine Learning and complex models is transforming the economy, healthcare, justice, industry, science, public administration, and education. This encourages us to invest in diverse technological and scientific approaches and perspectives. Our overarching strategy is to explore the flow and diversification of data, and to invest in research lines that will lead to the development of applied Artificial Intelligence foundations and models that are responsible and human centred.

Artificial Intelligence and Decision Support