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About

About

Hugo Paredes (M) received B.Eng. and Ph.D. degrees in Computer Science from the University of Minho (2000 and 2008), and the Habilitation title from the University of Tras-os-Montes e Alto Douro - UTAD (2016). He was software engineer at SiBS, S.A. and software consultant at Novabase Outsoursing, S.A. Since 2003, he has been at UTAD, where he is currently Full Professor. In 2017 he co-founded Robocode Generation, Lda, a start-up company, UTAD spin off, where he is scientific consultant. During 2017 he was a visiting faculty at Human Computer Interaction Institute at Carnegie Mellon University. He was Pro-Rector for Digital Transition and Administrative Transformation at UTAD from May 2021 to September 2023.

He is a Senior Researcher at the Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), he was Assistant Coordinator of the Centre for Computer Graphics and Information Systems (CSIG) from 2020-2021. His main research interests are in the domain of Human-Computer Interaction, namely the topic of Human-AI applied to climate change, accessibility, health and active and healthy ageing. He is a member of the J.UCS board of editors, was guest editor of four Special Issues in journals indexed by the Journal Citation Reports and collaborates with the organization of several international conferences. He has authored or co-authored more than 150 refereed journal, book chapters and conference papers. He is one of the inventors of a granted patent and a patent pending request. He participated and lead several projects, including national and international projects, with public and private funding.

Details

Details

  • Name

    Hugo Paredes
  • Role

    Senior Researcher
  • Since

    01st June 2012
018
Publications

2024

A Gamification-Based Tool to Promote Accessible Design

Authors
Lorgat, MG; Paredes, H; Rocha, T;

Publication
Lecture Notes in Networks and Systems

Abstract
The human population with disability is rapidly expanding, more than 15% of people worldwide suffer from a disability and, despite the availability of accessibility guidelines, the websites are still inaccessible. Moreover, professionals with knowledge of accessibility and design abilities are hard to come by. Therefore, the current paper addresses the introduction of accessibility to the Software Engineering students through AccessCademy, a gamification-based tool, in a fun way. The activity is delivered via a Web-based learning environment, that presents bad accessibility scenarios or failures based on the Web Content Accessibility Guidelines (WCAG), and then encourages the students to solve them. Furthermore, a case study will be presented that evaluated the learning effectiveness of the tool in the context of a university course. The results demonstrated the potential of AccessCademy which offers students a fun and engaging way to learn about accessibility, to understand the importance of accessible design with WCAG and gain accessible design skills as well. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

2023

A Model for Cognitive Personalization of Microtask Design

Authors
Paulino, D; Guimaraes, D; Correia, A; Ribeiro, J; Barroso, J; Paredes, H;

Publication
SENSORS

Abstract
The study of data quality in crowdsourcing campaigns is currently a prominent research topic, given the diverse range of participants involved. A potential solution to enhancing data quality processes in crowdsourcing is cognitive personalization, which involves appropriately adapting or assigning tasks based on a crowd worker's cognitive profile. There are two common methods for assessing a crowd worker's cognitive profile: administering online cognitive tests, and inferring behavior from task fingerprinting based on user interaction log events. This article presents the findings of a study that investigated the complementarity of both approaches in a microtask scenario, focusing on personalizing task design. The study involved 134 unique crowd workers recruited from a crowdsourcing marketplace. The main objective was to examine how the administration of cognitive ability tests can be used to allocate crowd workers to microtasks with varying levels of difficulty, including the development of a deep learning model. Another goal was to investigate if task fingerprinting can be used to allocate crowd workers to different microtasks in a personalized manner. The results indicated that both objectives were accomplished, validating the usage of cognitive tests and task fingerprinting as effective mechanisms for microtask personalization, including the development of a deep learning model with 95% accuracy in predicting the accuracy of the microtasks. While we achieved an accuracy of 95%, it is important to note that the small dataset size may have limited the model's performance.

2023

Detection of Intermittent Claudication from Smartphone Inertial Data in Community Walks Using Machine Learning Classifiers

Authors
Pinto, B; Correia, MV; Paredes, H; Silva, I;

Publication
SENSORS

Abstract
Peripheral arterial disease (PAD) causes blockage of the arteries, altering the blood flow to the lower limbs. This blockage can cause the individual with PAD to feel severe pain in the lower limbs. The main contribution of this research is the discovery of a solution that allows the automatic detection of the onset of claudication based on data analysis from patients' smartphones. For the data-collection procedure, 40 patients were asked to walk with a smartphone on a thirty-meter path, back and forth, for six minutes. Each patient conducted the test twice on two different days. Several machine learning models were compared to detect the onset of claudication on two different datasets. The results suggest that we can identify the onset of claudication using inertial sensors with a best case accuracy of 92.25% for the Extreme Gradient Boosting model.

2023

Bird's eye view of augmented reality and applications for education and training: A survey of surveys and reviews

Authors
Cruz, A; Paredes, H; Martins, P;

Publication
COMPUTER APPLICATIONS IN ENGINEERING EDUCATION

Abstract
Augmented reality (AR) is a field of knowledge being developed since the middle of the last century. Its use has been spreading because of its usefulness, but more recently because of mobile platforms being widespread and accessible. AR has been applied in several fields of activity, and also in the field of Education and Training, because AR has several advantages over other teaching methods. In this paper, we search and analyze surveys and reviews of AR to present a brief history and its definition. We also present a classification of our sample under a scheme we developed in past work, and present also examples of technologies and applications of AR in each field. Finally, we do a deeper analysis over the publications of Education and Training, advantages and issues of AR in this field, and some research trends.

2023

Stigmergy in Crowdsourcing and Task Fingerprinting: Study on Behavioral Traces of Weather Experts in Interaction Logs

Authors
Paulino, D; Correia, A; Guimarães, D; Chaves, R; Melo, G; Schneider, D; Barroso, J; Paredes, H;

Publication
26th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2023, Rio de Janeiro, Brazil, May 24-26, 2023

Abstract

Supervised
thesis

2022

Scrum no Projeto Integrado na Construção de Edifícios - Scrumming the Scrum for Integrated Project Delivery

Author
Yanh André Ribeiro

Institution
UP-FEUP

2022

Parker's Commute - Digital Game to promote the Use of Electric Vehicles

Author
Diogo José de Sousa Machado

Institution
UP-FEUP

2022

On the Acquisition, Storage, and Visualization of Meteorological and Seismic Data from IGUP

Author
Diogo Gonçalves Delgado

Institution
UP-FCUP

2022

Designing a Customer Application for Consulting Services through Service Design

Author
David Tomé Grande

Institution
UP-FEUP

2022

The Art of Storytelling: Its Importance in Video Game Immersion When Paired With Localisation

Author
Mariana Cardoso Ribeiro

Institution
UP-FEUP