Algoritmi | User | Luís Miguel da Rocha de Matos
Luís Miguel da Rocha de Matos
Luís Miguel da Rocha de Matos
At Algoritmi
Academic Degree
PhD
Current Position
Invited Assistant Professor at Escola de Engenharia da Universidade do Minho
Personal Webpage
https://lmm.dsi.uminho.pt/Personal Email
luis.matos@dsi.uminho.ptOrcid
0000-0001-5827-9129Researcher ID
N-8043-2015FCT Public Key
J64911226d44
Ciência ID
4B15-8E29-1D57Google Scholar
o3_qOXkAAAAJh-index
3Publications
11Editorial
0Citations
27Q1 / Q2
1About Me 
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
Publications (23)
A Deep Learning-Based Decision Support System for Mobile Performance Marketing
International Journal of Information Technology and Decision Making
2023 | journal-article
Machine Learning for Predicting Production Disruptions in the Wood-Based Panels Industry: A Demonstration Case
IFIP Advances in Information and Communication Technology
2023 | conference-paper
RTSIMU: Real-Time Simulation tool for IMU sensors[Formula presented]
Software Impacts
2023 | journal-article
A Deep Learning Approach to Prevent Problematic Movements of Industrial Workers Based on Inertial Sensors
Proceedings of the International Joint Conference on Neural Networks
2022 | conference-paper
A Machine Learning Approach for Spare Parts Lifetime Estimation
2022 | conference-paper
A Sequence to Sequence Long Short-Term Memory Network for Footwear Sales Forecasting
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2022 | conference-paper
An Empirical Study on Anomaly Detection Algorithms for Extremely Imbalanced Datasets
IFIP Advances in Information and Communication Technology
2022 | conference-paper
An Intelligent Decision Support System for Road Freight Transport
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2022 | book
Categorical Attribute traNsformation Environment (CANE): A python module for categorical to numeric data preprocessing[Formula presented]
Software Impacts
2022 | journal-article
Deep autoencoders for acoustic anomaly detection: experiments with working machine and in-vehicle audio
Neural Computing and Applications
2022 | journal-article
Isolation Forests and Deep Autoencoders for Industrial Screw Tightening Anomaly Detection
Computers
2022 | journal-article
Predicting Yarn Breaks in Textile Fabrics: A Machine Learning Approach
Procedia Computer Science
2022 | conference-paper
A Comparison of Anomaly Detection Methods for Industrial Screw Tightening
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2021 | conference-paper
A Comparison of Machine Learning Approaches for Predicting In-Car Display Production Quality
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2021 | conference-paper
Deep Dense and Convolutional Autoencoders for Machine Acoustic Anomaly Detection
IFIP Advances in Information and Communication Technology
2021 | conference-paper
Using deep autoencoders for in-vehicle audio anomaly detection
Procedia Computer Science
2021 | conference-paper
Deep Dense and Convolutional Autoencoders for Unsupervised Anomaly Detection In Machine Condition Sounds
arXiv
2020 | other
A Categorical Clustering of Publishers for Mobile Performance Marketing
Advances in Intelligent Systems and Computing
2019 | conference-paper
Using Deep Learning for Mobile Marketing User Conversion Prediction
Proceedings of the International Joint Conference on Neural Networks
2019 | conference-paper
Using deep learning for ordinal classification of mobile marketing user conversion
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2019 | conference-paper
A Comparison of Data-Driven Approaches for Mobile Marketing User Conversion Prediction
9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 - Proceedings
2018 | conference-paper
Forecasting store foot traffic using facial recognition, time series and support vector machines
Advances in Intelligent Systems and Computing
2017 | conference-paper
Forecasting Human Entrances at a Commercial Store using facial recognition data
2015 | dissertation-thesis
History
| Init | End | Change | Value | |
|---|---|---|---|---|
| 1970-01-01 | Luís | |||
| https://scholar.google.pt/citations?user=o3_qOXkAAAAJ&hl=pt-PT | ||||
| Laboratory | IDS | |||
| 1288-01-17 14:43:27 | ||||
| 17/01/2023 20:15 | ||||
| 1376-01-17 14:43:27 | ||||
| Member Type | Assistant Researcher | |||
| 1288-03-02 10:56:54 | ||||
| 02/03/2023 20:21 | ||||
| Aluno do MIEGSI - data de inscrição 18/10/2010.;;;;;;;;;;; | ||||
| 1376-03-02 10:56:54 | ||||
| Internal Member Type |
A Deep Learning-Based Decision Support System for Mobile Performance Marketing
International Journal of Information Technology and Decision Making
2023 | journal-article
Machine Learning for Predicting Production Disruptions in the Wood-Based Panels Industry: A Demonstration Case
IFIP Advances in Information and Communication Technology
2023 | conference-paper
RTSIMU: Real-Time Simulation tool for IMU sensors[Formula presented]
Software Impacts
2023 | journal-article
A Deep Learning Approach to Prevent Problematic Movements of Industrial Workers Based on Inertial Sensors
Proceedings of the International Joint Conference on Neural Networks
2022 | conference-paper
A Machine Learning Approach for Spare Parts Lifetime Estimation
2022 | conference-paper
A Sequence to Sequence Long Short-Term Memory Network for Footwear Sales Forecasting
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2022 | conference-paper
An Empirical Study on Anomaly Detection Algorithms for Extremely Imbalanced Datasets
IFIP Advances in Information and Communication Technology
2022 | conference-paper
An Intelligent Decision Support System for Road Freight Transport
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2022 | book
Categorical Attribute traNsformation Environment (CANE): A python module for categorical to numeric data preprocessing[Formula presented]
Software Impacts
2022 | journal-article
Deep autoencoders for acoustic anomaly detection: experiments with working machine and in-vehicle audio
Neural Computing and Applications
2022 | journal-article
Isolation Forests and Deep Autoencoders for Industrial Screw Tightening Anomaly Detection
Computers
2022 | journal-article
Predicting Yarn Breaks in Textile Fabrics: A Machine Learning Approach
Procedia Computer Science
2022 | conference-paper
A Comparison of Anomaly Detection Methods for Industrial Screw Tightening
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2021 | conference-paper
A Comparison of Machine Learning Approaches for Predicting In-Car Display Production Quality
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2021 | conference-paper
Deep Dense and Convolutional Autoencoders for Machine Acoustic Anomaly Detection
IFIP Advances in Information and Communication Technology
2021 | conference-paper
Using deep autoencoders for in-vehicle audio anomaly detection
Procedia Computer Science
2021 | conference-paper
Deep Dense and Convolutional Autoencoders for Unsupervised Anomaly Detection In Machine Condition Sounds
arXiv
2020 | other
A Categorical Clustering of Publishers for Mobile Performance Marketing
Advances in Intelligent Systems and Computing
2019 | conference-paper
Using Deep Learning for Mobile Marketing User Conversion Prediction
Proceedings of the International Joint Conference on Neural Networks
2019 | conference-paper
Using deep learning for ordinal classification of mobile marketing user conversion
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2019 | conference-paper
A Comparison of Data-Driven Approaches for Mobile Marketing User Conversion Prediction
9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 - Proceedings
2018 | conference-paper
Forecasting store foot traffic using facial recognition, time series and support vector machines
Advances in Intelligent Systems and Computing
2017 | conference-paper
Forecasting Human Entrances at a Commercial Store using facial recognition data
2015 | dissertation-thesis
| Start | End | Term | Value | |
|---|---|---|---|---|
| Luís | ||||
| https://scholar.google.pt/citations?user=o3_qOXkAAAAJ&hl=pt-PT | ||||
| Laboratory | IDS | |||
| 1288-01-17 14:43:27 | ||||
| 17/01/2023 20:15 | ||||
| 1376-01-17 14:43:27 | ||||
| Member Type | Assistant Researcher | |||
| 1288-03-02 10:56:54 | ||||
| 02/03/2023 20:21 | ||||
| Aluno do MIEGSI - data de inscrição 18/10/2010.;;;;;;;;;;; | ||||
| 1376-03-02 10:56:54 | ||||
| Internal Member Type |
