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Hi, my name is Luís Miguel da Rocha de Matos, and I started my journey in the area of ¿¿information systems during my High School education by completing the Information Management course. Then I entered the university of Minho and took the Integrated Masters course in Information Systems and Technologies. During this period, I specialized in several areas of programming with particular emphasis on Machine Learning and Artificial Intelligence. I took the opportunity to specialize in some tools like Salesforce Apex and Outsystems. Finally, I got a Ph.D. in Information Systems and Technologies, where I started my research and academic career. My Ph.D. focused on developing an intelligent decision support system for the mobile market, where I attributed campaigns to users taking into account the dynamics of the volatile mobile market. I currently lecture, mainly on the course "Engineering Information Systems and Management" and their respective masters courses. Furthermore, since 2016 I work as a researcher, contributing to several Scientific projects (e.g., Factory of the Future, TexBoost, STVgoDigital, EasyRide, PROMOS), performed (since 2022) peer-review in Machine Learning (e.g., semi-supervised learning, Anomaly Detection, Deep Learning) for Q1 Journals (Pattern Recognition, IEEE Access, Neural Computing and Applications) and Q2 Journals (e.g., Expert Systems) and received a Best Paper Award ICCSA 2021 Conference. Since 2022 I colaborated in several scientific commitees (e.g., ARTIIS, ISTIIS, EAI IoECon, SLATE), session Chair (e.g., AIAI and ARTIIS), workshop presentations (e.g., CODE AI project) and as examiner in public evaluations of Masters Dissertations. I am engaged with the society through a keynote speech (2023), local news appearances (2021, 2023), and other educational initiatives. My work and experience have addressed some of the challenges and opportunities of the modern world, and have advanced the knowledge and practice in his field. Creator of the Python module Cane - Categorical Attribute traNsformation Environment with more than 124 thousand downloads in total since June 3rd 2020. Currently, my research interests are: - Business Analytics - Decision Support Systems - Data Mining - Data Science - Neural Networks - Anomaly Detection - eXplainable AI (XAI) Currently, I lecture/lectured the following courses: - Computer Programming Fundamentals - Integration Systems and Implementation - Algorithmic and Programming - Web Programming - Data Structures (Ansi C) - Information Technologies in Organizations (Lecture Master Degree in Information Systems) - Artificial Intelligence Techniques - Intelligent Data
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Identification

Personal identification

Full name
LUÍS MIGUEL DA ROCHA DE MATOS
Date of birth
1992/06/09
Gender
Male

Citation names

  • Matos, Luís
  • Luís Miguel Matos

Author identifiers

Ciência ID
4B15-8E29-1D57
ORCID iD
0000-0001-5827-9129
Google Scholar ID
o3_qOXkAAAAJ
Researcher Id
N-8043-2015
Scopus Author Id
57211265776

Email addresses

  • luis.matos@dsi.uminho.pt (Professional)

Websites

Knowledge fields

  • Exact Sciences - Computer and Information Sciences - Information Science

Languages

Language Speaking Reading Writing Listening Peer-review
Portuguese (Mother tongue)
English Proficiency (C2) Proficiency (C2) Advanced (C1) Proficiency (C2) Proficiency (C2)
Education
Degree Classification
2016/12/01 - 2021/12/07
Concluded
 Tecnologia e Sistemas de Informação (Doutoramento)
Major in Sem especialidade
Universidade do Minho, Portugal
"An intelligent decision support system for mobile performance marketing" (THESIS/DISSERTATION)
 Approved unanimously (highest grade) External ref
2010/10/01 - 2015/11/02
Concluded
 Mestrado Integrado em Engenharia e Gestão de Sistemas de Informação (Mestrado integrado)
Major in Ciências da Computação
Universidade do Minho - Campus de Azurém, Portugal
"Forecasting Human Entrances at a Commercial Store using facial recognition data" (THESIS/DISSERTATION)
Affiliation

Science

Category
Host institution 		Employer
2016/12/01 - Current Researcher (Research) Universidade do Minho Centro ALGORITMI, Portugal
Universidade do Minho - Campus de Azurém, Portugal

Teaching in Higher Education

Category
Host institution 		Employer
2022/04/01 - Current Invited Assistant Professor (University Teacher) Universidade do Minho - Campus de Azurém, Portugal
Universidade do Minho - Departamento de Sistemas de Informação, Portugal
2019/10/01 - 2022/03/31 Invited Assistant (University Teacher) Universidade do Minho, Portugal
Universidade do Minho - Campus de Azurém, Portugal
Projects

Grant

Designation Funders
2020/01/01 - 2021/12/31 Easy Ride: Experience is everything
POCI-01-0247-FEDER-039334
Research Fellow
Universidade do Minho - Campus de Azurém, Portugal

BOSCH CAR MULTIMEDIA, SA, Portugal
European Regional Development Fund

BOSCH CAR MULTIMEDIA, SA
Concluded
2020/01/01 - 2021/12/23 Factory of the Future: Smart Manufacturing
POCI-01-0247-FEDER-039479
Research Fellow
Universidade do Minho Centro ALGORITMI, Portugal

BOSCH CAR MULTIMEDIA, SA, Portugal
European Regional Development Fund
Concluded
2016/12/02 - 2019/11/30 PROMOS - Previsão e otimização de campanhas publicitárias para dispositivos móveis em modelos de subscrição.
NORTE-01-0247-FEDER-017497
Research Fellow
Universidade do Minho Centro ALGORITMI, Portugal
 European Regional Development Fund
Concluded

Contract

Designation Funders
2023/01 - Current Advanced Decision Making in productive systems through Intelligent Networks (ADM.IN)
POCI-01-0247-FEDER-055087
Post-doc
Universidade do Minho Centro ALGORITMI, Portugal
 European Union

Autoridade de Gestão do Programa Operacional Competitividade e Internacionalização
2022/01/02 - Current Connected Manufacturing - Digital Transformation
UMINHO/BID/2022/10
SIFN-01-9999-FN-179826
Post-doc Fellow
Universidade do Minho Centro ALGORITMI, Portugal
 Agência para o Investimento e Comércio Externo de Portugal EPE

BOSCH
Ongoing
2022/01 - 2023/12 STVgoDigital - Digitalization of the T&C sector
POCI-01-0247-FEDER-046086
Post-doc
Universidade do Minho Centro ALGORITMI, Portugal
 Autoridade de Gestão do Programa Operacional Competitividade e Internacionalização
Concluded
2022/01 - 2022/12 PPC4.0 - Production Planning Control 4.0
POCI-01-0247-FEDER-069803
Post-doc
Universidade do Minho Centro ALGORITMI, Portugal
 Autoridade de Gestão do Programa Operacional Competitividade e Internacionalização
2022/01 - 2022/12 aDyTrans - Dynamic Transportations Platform
NORTE-01-0247-FEDER-045174
Post-doc
Universidade do Minho Centro ALGORITMI, Portugal
 Autoridade de Gestão do Programa Operacional Competitividade e Internacionalização
2022/01 - 2022/12 PRODUTECH4S&C
POCI-01-0247-FEDER-046102
Post-doc
Universidade do Minho Centro ALGORITMI, Portugal
 Autoridade de Gestão do Programa Operacional Competitividade e Internacionalização
2022/01 - 2022/12 GreenShoes 4.0 - Calçado, Marroquinaria e Tecnologias Avançadas de Materiais, Equipamentos e Software
POCI-01-0247-FEDER-046082
Post-doc
Universidade do Minho Centro ALGORITMI, Portugal
 Autoridade de Gestão do Programa Operacional Competitividade e Internacionalização
2019/01/01 - 2019/12/31 Centro de Investigação ALGORITMI
UID/CEC/00319/2019
Universidade do Minho, Portugal

Universidade do Minho Centro ALGORITMI, Portugal
Fundação para a Ciência e a Tecnologia
Concluded
Outputs

Publications

Book
  1. Silva, S.; Cortez, P.; Mendes, R.; Pereira, P.J.; Matos, L.M.; Garcia, L.. A Categorical Clustering of Publishers for Mobile Performance Marketing. 2019.
    10.1007/978-3-319-94120-2_14
  2. Cortez, P.; Matos, L.M.; Pereira, P.J.; Santos, N.; Duque, D.. Forecasting store foot traffic using facial recognition, time series and support vector machines. 2017.
    10.1007/978-3-319-47364-2_26
Book chapter
  1. Cláudia Afonso; Arthur Matta; Luís Miguel Matos; Miguel Bastos Gomes; Antonina Santos; André Pilastri; Paulo Cortez. "Machine Learning for Predicting Production Disruptions in the Wood-Based Panels Industry: A Demonstration Case". 2023.
    10.1007/978-3-031-34107-6_27
  2. Gonçalo Fontes; Luís Miguel Matos; Arthur Matta; André Pilastri; Paulo Cortez. "An Empirical Study on Anomaly Detection Algorithms for Extremely Imbalanced Datasets". 2022.
    10.1007/978-3-031-08333-4_7
  3. Santos, Luís; Luís Miguel Matos; Ferreira, Luís; Alves, Pedro; Viana, Mário; Pilastri, André; Cortez, Paulo. "A Sequence to Sequence Long Short-Term Memory Network for Footwear Sales Forecasting". In Intelligent Data Engineering and Automated Learning – IDEAL 2022, 465-473. Springer International Publishing, 2022.
    10.1007/978-3-031-21753-1_45
  4. Carvalho, Hugo Silva; Pilastri, André; Matta, Arthur; Luís Miguel Matos; Novais, Rui; Cortez, Paulo. "An Intelligent Decision Support System for Road Freight Transport". In Intelligent Data Engineering and Automated Learning – IDEAL 2022, 146-156. Springer International Publishing, 2022.
    10.1007/978-3-031-21753-1_15
  5. Gabriel Coelho; Pedro Pereira; Luis Matos; Alexandrine Ribeiro; Eduardo C. Nunes; André Ferreira; Paulo Cortez; André Pilastri. "Deep Dense and Convolutional Autoencoders for Machine Acoustic Anomaly Detection". 337-348. Springer International Publishing, 2021.
    10.1007/978-3-030-79150-6_27
  6. Luís Miguel Matos; Domingues, André; Moreira, Guilherme; Cortez, Paulo; Pilastri, André. "A Comparison of Machine Learning Approaches for Predicting In-Car Display Production Quality". In Intelligent Data Engineering and Automated Learning – IDEAL 2021, 3-11. Springer International Publishing, 2021.
    10.1007/978-3-030-91608-4_1
  7. Luís Miguel Matos; Cortez, Paulo; Mendes, Rui Castro; Moreau, Antoine. "Using Deep Learning for Ordinal Classification of Mobile Marketing User Conversion". In Intelligent Data Engineering and Automated Learning – IDEAL 2019, 60-67. Springer International Publishing, 2019.
    10.1007/978-3-030-33607-3_7
Conference paper
  1. Cristiana Fernandes; Luís Miguel Matos; Duarte Folgado; Maria Lua Nunes; Joao Rui Pereira; Andre Pilastri; Paulo Cortez. "A Deep Learning Approach to Prevent Problematic Movements of Industrial Workers Based on Inertial Sensors". 2022.
    10.1109/ijcnn55064.2022.9892409
  2. Macedo, Luísa; Luís Miguel Matos; Cortez, Paulo; Domingues, André; Moreira, Guilherme; Pilastri, André. "A Machine Learning Approach for Spare Parts Lifetime Estimation". 2022.
    10.5220/0010903800003116
  3. Ribeiro, Diogo; Matos, Luís Miguel; Moreira, Guilherme; Pilastri, André; Cortez, Paulo. "A Comparison of Anomaly Detection Methods for Industrial Screw Tightening". 2021.
    10.1007/978-3-030-86960-1_34
  4. Pereira, Pedro José; Coelho, Gabriel José Dias; Ribeiro, Alexandrine; Matos, Luís Miguel Rocha; Nunes, Eduardo Carvalho; Ferreira, André; Pilastri, André Luiz; Cortez, Paulo. "Using deep autoencoders for in-vehicle audio anomaly detection". 2021.
    10.1016/j.procs.2021.08.031
  5. Matos, Luis Miguel; Cortez, Paulo; Mendes, Rui; Moreau, Antoine. "Using Deep Learning for Mobile Marketing User Conversion Prediction". 2019.
    10.1109/IJCNN.2019.8851888
  6. Luís Miguel Matos; Matos, Luis Miguel; Cortez, Paulo; Mendes, Rui; Moreau, Antoine. "A Comparison of Data-Driven Approaches for Mobile Marketing User Conversion Prediction". Paper presented in 2018 International Conference on Intelligent Systems (IS), 2018.
    Published • 10.1109/IS.2018.8710472
Journal article
  1. Paula Dias; Arthur Matta; André Pilastri; Luís Miguel Matos; Paulo Cortez. "RTSIMU: Real-Time Simulation tool for IMU sensors". Software Impacts (2023): https://doi.org/10.1016/j.simpa.2023.100522.
    10.1016/j.simpa.2023.100522
  2. Matos, Luís Miguel; Cortez, Paulo; Mendes, Rui; Moreau, Antoine. "A Deep Learning-Based Decision Support System for Mobile Performance Marketing". International Journal of Information Technology & Decision Making (2022): 1-25. http://dx.doi.org/10.1142/s021962202250047x.
    10.1142/s021962202250047x
  3. Luís Miguel Matos; João Azevedo; Arthur Matta; André Pilastri; Paulo Cortez; Rui Mendes. "Categorical Attribute traNsformation Environment (CANE): A python module for categorical to numeric data preprocessing". Software Impacts (2022): https://doi.org/10.1016/j.simpa.2022.100359.
    10.1016/j.simpa.2022.100359
  4. Coelho, Gabriel; Luís Miguel Matos; Pereira, Pedro José; Ferreira, André; Pilastri, André; Cortez, Paulo. "Deep autoencoders for acoustic anomaly detection: experiments with working machine and in-vehicle audio". Neural Computing and Applications (2022): http://dx.doi.org/10.1007/s00521-022-07375-2.
    10.1007/s00521-022-07375-2
  5. Ribeiro, Diogo; Matos, Luís Miguel; Moreira, Guilherme; Pilastri, André; Cortez, Paulo. "Isolation Forests and Deep Autoencoders for Industrial Screw Tightening Anomaly Detection". Computers 11 4 (2022): 54. http://dx.doi.org/10.3390/computers11040054.
    10.3390/computers11040054
  6. Azevedo, João; Ribeiro, Rui; Luís Miguel Matos; Sousa, Rui; Silva, João Paulo; Pilastri, André; Cortez, Paulo. "Predicting Yarn Breaks in Textile Fabrics: A Machine Learning Approach". Procedia Computer Science 207 (2022): 2301-2310. http://dx.doi.org/10.1016/j.procs.2022.09.289.
    Published • 10.1016/j.procs.2022.09.289
Thesis / Dissertation
  1. Matos, Luís. "Forecasting Human Entrances at a Commercial Store using facial recognition data". 2015. http://repositorium.sdum.uminho.pt/handle/1822/40308.

Other

Other output
  1. Deep Dense and Convolutional Autoencoders for Unsupervised Anomaly Detection in Machine Condition Sounds. 2020. Ribeiro, Alexandrine; Matos, Luís; Pereira, Pedro José; Nunes, Eduardo C.; Cortez, Paulo; Pilastri, André.
    10.48550/arxiv.2006.10417
Activities

Oral presentation

Presentation title Event name
Host (Event location)
2022 An Empirical Study on Anomaly Detection Algorithms for Extremely Imbalanced Datasets International Conference on Artificial Intelligence Applications and Innovations
(Creta, Greece)

Supervision

Thesis Title
Role 		Degree Subject (Type)
Institution / Organization
2022 - 2023/12/06 Comparação de Abordagens de Machine Learning para Deteção e Antecipação de Movimentos de Risco em Trabalhadores de Costura
Supervisor
 Mestrado em Engenharia e Gestão de Sistemas de Informação (Master)
Universidade do Minho, Portugal

Event participation

Activity description
Type of event 		Event name
Institution / Organization
2023 - 2023 Apresentação como especialista de ferramentas de AutoML para o projeto CodeAI
Workshop
Universidade do Minho, Portugal
2022 - 2022 Presença na Conferência International Conference on Artificial Intelligence Applications and Innovations (AIAI 2022)
Conference
 International Conference on Artificial Intelligence Applications and Innovations

Jury of academic degree

Topic
Role 		Candidate name (Type of degree)
Institution / Organization
2023/10/27 Um Sistema Inteligente de Apoio à Decisão para Sistemas Energéticos
(Thesis) Main arguer
 Daniela Filipa Silva Soares (Master)
Universidade do Minho, Portugal
2022/12/19 Aplicação de Técninas de Machine Learning para a Previsão de Processos Industriais
(Thesis) Main arguer
 Afonso José Torres da Silva e Sousa (Master)
Universidade do Minho, Portugal

Committee member

Activity description
Role 		Institution / Organization
2022 - Current Representante dos Docentes Convidados Equiparados a Professor Auxiliar no Departamento de Sistemas de Informação da Universidade do Minho
Other
 Universidade do Minho, Portugal

Conference scientific committee

Conference name Conference host
2024/10/21 - 2024/10/23 Advanced Research in Technologies, Information, Innovation and Sustainability (ARTIIS 2024) Santigo de Chile, Chile
2024/09/26 - 2024/09/27 European Alliance for Innovation International Conference on the Internet of Everything Guimarães
2023/10/18 - 2023/10/20 International Symposium on Technological Innovations for Industry and Society (ISTIIS) Madrid
2023/10/08 - 2023/10/10 International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability (ARTIIS 2023) Madrid
2023/06/26 - 2023/06/28 SLATE 2023 - Symposium on Languages, Applications and Technologies ESMAD, POLITÉCNICO DO PORTO PORTUGAL
2022/09/12 - 2022/09/15 International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability (ARTIIS 2022) Santiago de Compostela

Journal scientific committee

Journal title (ISSN) Publisher
2024 - Current Neural Computing and Applications (1433-3058) Springer
2024 - Current Smart cities (2624-6511) MDPI
2023 - Current Sensors (1424-8220) MDPI
2023 - Current Pattern Recognition (1873-5142) ELSEVIER
2023 - Current IEEE Access (2169-3536) IEEE
2023 - Current Applied Sciences (2076-3417) MDPI
2023 - Current SN Applied Sciences (2523-3971) Springer
2022 - Current Mathematics (2227-7390) MDPI
2022 - Current Journal of manufacturing processes (2212-4616) ELSEVIER
2022 - Current Expert Systems (1468-0394) Wiley
2022 - 2022 The Imaging Science Journal (1743-131X) Taylor & Francis
Distinctions

Award

2021 ICCSA 2021 Conference - Best Paper Award
Università degli Studi di Cagliari, Italy