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Human-Centered Computing and Information Science

HumanISE is an interdisciplinary centre focused on research at the forefront of human-centred computing (HCC) with broad and deep expertise in computer science (CS) and information science (IS).

At HumanISE, engineers, scientists and designers focus on research and development of software systems, methods, and tools, capable of leveraging human abilities and practices within their communities and environments, involving high technical and managerial complexity, due to large scale, high heterogeneity, high uncertainty, high integrity, strict compliance to standards and legal frameworks, or domain-specific organisational issues.

Our mission is to pursue high-quality research, innovation, consultancy, and technology transfer, impactful, in close cooperation with academic and industrial partners. We focus on five main research areas - Computer-Human Interaction, Computer Graphics and Interactive Digital Media, Information Management and Information Systems, Software Engineering, and Large Scale and Special Purpose Computing Systems, Languages and Tools - and four innovation areas - Personalised Health Research, Earth, Ocean and Space Science, Geospatial Information Systems Engineering, and Information Systems and Applied Computing.

Furthermore, at HumanISE, we are also strongly committed to training young researchers and professionals, with a significant track record in the supervision of master and PhD students.

Presently, our researchers originate from the University of Porto (UP), Polytechnic of Porto (IPP), University of Trás-os-Montes e Alto Douro (UTAD), Universidade Aberta (UAb) and University of Minho (UM).

Latest News
Computer Science and Engineering

Portugal’s semiconductor dialogue takes shape with contributions from INESC TEC – six months after the kick off of the Competence Centre

Portugal’s position within the semiconductor ecosystem was one of the topics discussed at an event promoted by the Portuguese Competence Centre for Semiconductors (POEMS) – which features INESC TEC as a partner.

21st November 2025

Computer Science and Engineering

INESC TEC and Águas do Douro e Paiva sign collaboration protocol

On 31 October, INESC TEC signed a new collaboration protocol with Águas do Douro e Paiva (AdDP) at AdDP’s facilities in Lever.

06th November 2025

Computer Science and Engineering

Seniors training with Artificial Intelligence? The future (really is) today

The project is called IATOS and it aims to make remote physical training safer, more effective, and accessible for older adults. Led by a consortium including INESC TEC, AGIT TECH, and the University of Trás-os-Montes and Alto Douro, the initiative seeks to create a digital platform for AI-assisted physical training, specifically designed for people over 65.

29th September 2025

Power and Energy Systems

There are innovative technological solutions to be developed for local energy markets – with contributions from INESC TEC

The delay in generating synthetic data for time series – fundamental elements in energy forecasting scenarios – was one of the motivations for GENESIS, a project that aims to provide local electricity markets with contextual synthetic data and reliable artificial intelligence models.

22nd September 2025

Computer Science and Engineering

INESC TEC researchers organised an international conference on computer vision and computer graphics

The VISIGRAPP 2025 - 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - took place in Porto, in late February. It brought together more than 380 researchers and professionals interested in keeping up with and discussing theoretical advances and applications in Computer Vision, Computer Graphics, Human-Computer Interaction, and Information Visualisation - the main themes of the co-located conferences VISAPP, GRAPP, HUCAPP, and IVAPP, respectively. One of the co-chairs of this conference was INESC TEC researcher A. Augusto de Sousa.

27th March 2025

Team
003

Laboratories

Information Systems Laboratory

Laboratory of Software Engineering

Laboratory of Computer Graphics and Virtual Environments

Publications

HumanISE Publications

View all Publications

2026

Immersion for AI: Immersive Learning with Artificial Intelligence

Authors
Morgado, L;

Publication
IMMERSIVE LEARNING RESEARCH NETWORK, ILRN 2025

Abstract
This work reflects upon what Immersion can mean from the perspective of an Artificial Intelligence (AI). Applying the lens of immersive learning theory, it seeks to understand whether this new perspective supports ways for AI participation in cognitive ecologies. By treating AI as a participant rather than a tool, it explores what other participants (humans and other AIs) need to consider in environments where AI can meaningfully engage and contribute to the cognitive ecology, and what the implications are for designing such learning environments. Drawing from the three conceptual dimensions of immersion-System, Narrative, and Agency-this work reinterprets AIs in immersive learning contexts. It outlines practical implications for designing learning environments where AIs are surrounded by external digital services, can interpret a narrative of origins, changes, and structural developments in data, and dynamically respond, making operational and tactical decisions that shape human-AI collaboration. Finally, this work suggests how these insights might influence the future of AI training, proposing that immersive learning theory can inform the development of AIs capable of evolving beyond static models. This paper paves the way for understanding AI as an immersive learner and participant in evolving human-AI cognitive ecosystems.

2026

An Explosion of the Uses of Immersive Learning Environments: A Mapping of Reviews Update

Authors
Beck, D; Morgado, L; O'Shea, P;

Publication
IMMERSIVE LEARNING RESEARCH NETWORK, ILRN 2025

Abstract
Since the publication of the 2020 paper, Finding the Gaps About Uses of Immersive Learning Environments: A Survey of Surveys, the landscape of immersive learning environments (ILEs) has continued to evolve rapidly. This update aims to revisit the gaps identified in that previous research and explore emerging trends. We conducted an extensive review of new surveys published after that paper's cut date. Our findings reveal a significant amount of new published reviews (n = 64), more than doubling the original corpus (n = 47). The results highlighted novel themes of usage of immersive environments, helping bridge some 2020 research gaps. This paper discusses those developments and presents a consolidated perspective on the uses of immersive learning environments.

2026

NonVisual Pong: Enhancing Digital Accessibility Through Audio and Haptic Gaming for the Visually Impaired

Authors
Rocha, TDJVD; Nunes, RR; Barroso, JMP;

Publication
Lecture Notes in Networks and Systems

Abstract
The video game industry has grown to become one of the largest in the market, surpassing even the film industry over a decade ago (Statista in Video game industry revenue worldwide 2000–2020). However, the development of games designed with visually impaired players in mind is still almost non-existent when compared to the sheer number of games released yearly. NonVisual Pong is our approach to addressing this challenge, providing blind players with a way to engage in competitive fun through gaming. We took the original Pong game from 1972 and fully adapted it to be played using only a controller—no visual display required. Following the development process, we tested our implementation with experts, discovering that, overall, our game was easy to pick up, required no overly complex setup, and successfully delivered the intended experience. Players enjoyed a balanced challenge and immersion, facilitated by audio cues and the controller’s vibrations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

2026

Software Testing Education and Industry Needs - Report from the ENACTEST EU Project

Authors
Saadatmand, M; Khan, A; Marín, B; Paiva, CR; Asch, NV; Moran, G; Cammaerts, F; Snoeck, M; Mendes, A;

Publication
Lecture Notes in Computer Science

Abstract
The evolving landscape of software development demands that software testers continuously adapt to new tools, practices, and acquire new skills. This study investigates software testing competency needs in industry, identifies knowledge gaps in current testing education, and highlights competencies and gaps not addressed in academic literature. This is done by conducting two focus group sessions and interviews with professionals across diverse domains, including railway industry, healthcare, and software consulting and performing a curated small-scale scoping review. The study instrument, co-designed by members of the ENACTEST project consortium, was developed collaboratively and refined through multiple iterations to ensure comprehensive coverage of industry needs and educational gaps. In particular, by performing a thematic qualitative analysis, we report our findings and observations regarding: professional training methods, challenges in offering training in industry, different ways of evaluating the quality of training, identified knowledge gaps with respect to academic education and industry needs, future needs and trends in testing education, and knowledge transfer methods within companies. Finally, the scoping review results confirm knowledge gaps in areas such as AI testing, security testing and soft skills. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

2026

Comparing and extending satisfiability solution methods for the resource-constrained project scheduling problem

Authors
Coelho, J; Vanhoucke, M;

Publication
COMPUTERS & OPERATIONS RESEARCH

Abstract
This paper solves the resource-constrained project scheduling problem (RCPSP) with a satisfiability problem (SAT) solver. This paper builds further on various existing SAT models for this well-known project scheduling problem and extends them with two methods to satisfy the resource constraints. Specifically, we use the wellknown minimal forbidden sets and compare them with the so-called covers that are traditionally used in SAT implementations. Moreover, we also implement an existing binary decision trees approach under various settings and extend the model with networks with adders, so far never used for solving the RCPSP, to guarantee that resource constraints are satisfied. The algorithms are tested under different settings on a set of 13,413 project instances with diverse network and resource structures, and the experiments demonstrate that a combination of these approaches help in finding better solutions within a reasonable time. Moreover, 393 new lower bounds, 62 new upper bounds, and 290 optimally solved instances (including 18 from the PSPLIB) have been discovered, which, to the best of our knowledge, had not been found before. The strong performance of the new algorithm motivated additional experiments, and the preliminary results suggest several promising directions for future research.