Cookies Policy
The website need some cookies and similar means to function. If you permit us, we will use those means to collect data on your visits for aggregated statistics to improve our service. Find out More
Accept Reject
  • Menu
About
Download Photo HD

About

Benjamim Fonseca is Assistant Professor at the University of Trás-os-Montes e Alto Douro (UTAD) and a Researcher in the INESC TEC Laboratory, in Portugal. His main research interests are collaborative systems and mobile accessibility. He has dozens of publications in these areas, in conferences, journals and books, and has participated in the reviewing and organization of several scientific publications and events.

Interest
Topics
Details

Details

  • Name

    Benjamim Fonseca
  • Cluster

    Computer Science
  • Role

    Senior Researcher
  • Since

    05th March 1997
002
Publications

2021

Scientometric Research Assessment of IEEE CSCWD Conference Proceedings: An Exploratory Analysis from 2001 to 2019

Authors
Correia, A; Paulino, D; Paredes, H; Fonseca, B; Jameel, S; Schneider, D; de Souza, JM;

Publication
24th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2021, Dalian, China, May 5-7, 2021

Abstract

2021

AuthCrowd: Author Name Disambiguation and Entity Matching using Crowdsourcing

Authors
Correia, A; Guimaraes, D; Paulino, D; Jameel, S; Schneider, D; Fonseca, B; Paredes, H;

Publication
24th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2021, Dalian, China, May 5-7, 2021

Abstract

2021

Intelligent Scheduling with Reinforcement Learning

Authors
Cunha, B; Madureira, A; Fonseca, B; Matos, J;

Publication
APPLIED SCIENCES-BASEL

Abstract
In this paper, we present and discuss an innovative approach to solve Job Shop scheduling problems based on machine learning techniques. Traditionally, when choosing how to solve Job Shop scheduling problems, there are two main options: either use an efficient heuristic that provides a solution quickly, or use classic optimization approaches (e.g., metaheuristics) that take more time but will output better solutions, closer to their optimal value. In this work, we aim to create a novel architecture that incorporates reinforcement learning into scheduling systems in order to improve their overall performance and overcome the limitations that current approaches present. It is also intended to investigate the development of a learning environment for reinforcement learning agents to be able to solve the Job Shop scheduling problem. The reported experimental results and the conducted statistical analysis conclude about the benefits of using an intelligent agent created with reinforcement learning techniques. The main contribution of this work is proving that reinforcement learning has the potential to become the standard method whenever a solution is necessary quickly, since it solves any problem in very few seconds with high quality, approximate to the optimal methods.

2021

Fostering Computational Thinking Skills: A Didactic Proposal for Elementary School Grades

Authors
Silva, R; Fonseca, B; Costa, C; Martins, F;

Publication
EDUCATION SCIENCES

Abstract
There is a growing presence of technology in the daily lives of elementary school students, with a recent exponential rise due to the constraints of remote teaching during the COVID-19 pandemic. It is important to understand how the education system can contribute to helping students develop the required skills for technological careers, without neglecting its obligation to create conditions that allow them to acquire transversal skills and to enable them to exercise full citizenship. The integration of Educational Robotics and block programming activities in collaborative learning environments promotes the development of computational thinking and other ICT skills, as well as critical thinking, social skills, and problem solving. This paper presents a theoretical proposal of a didactic sequence for the introduction to educational robotics and programming with Scratch Jr. It is composed of three learning scenarios, designed for elementary school teaching. Its main goal is to create conditions that favour the development of computational thinking in a collaborative learning environment. With increasing complexity and degree of difficulty, all the tasks root from a common problem: How can we create an algorithm that programs the robot/sprite to reach a predetermined position?

2021

Determinants and Predictors of Intentionality and Perceived Reliability in Human-AI Interaction as a Means for Innovative Scientific Discovery

Authors
Correia, A; Fonseca, B; Paredes, H; Chaves, R; Schneider, D; Jameel, S;

Publication
2021 IEEE International Conference on Big Data (Big Data), Orlando, FL, USA, December 15-18, 2021

Abstract

Supervised
thesis

2021

Universe-m evolution: jogo móvel adaptativo em realidade aumentada na experiência de aprendizagem matemática da função do 1.º grau no ensino médio

Author
Raimundo José Ribeiro Filho

Institution
UTAD

2021

A mediação do Laboratório Físico nos processos de Ensino e de Aprendizagem do curso de Redes de Computadores

Author
Jaildo Tavares Pequeno

Institution
UTAD

2021

Crowd-computing hybrids in scientific discovery

Author
António José Guilherme Correia

Institution
UTAD

2021

Intelligent Scheduling through Reinforcement Learning

Author
Bruno Miguel Almeida Cunha

Institution
UTAD

2020

Crowd-computing hybrids in scientific discovery

Author
António José Guilherme Correia

Institution
UTAD