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
https://scholar.google.pt/citations?user=o3_qOXkAAAAJ&hl=pt-PTAbout Me 
Hi, my name is Luís Miguel Matos and I started my journey in the area of information systems during my High School education by completing the Management Informatics course. Then I entered the university of minho and took the Integrated Masters course in Technologies and Information Systems. During this period I specialized in several areas of programming with special 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 PhD in Information Systems and Technologies where I started my research career and my academic career. My PhD focused on the development of an intelligent decision support system for the mobile market, where I attributed campaigns to users taking into account the dynamics of the volatile market that this project was part of. I currently lecture, mainly, the course in engineering and management of information systems and respective masters courses. Furthermore, I work as a researcher having contributed to several Scientific projects (e.g., Factory of the Future, TexBoost, STVgoDigital, EasyRide). Currently my research interests are: -Business Analytics -Decision Support Systems -Data Mining -Data Science -Neural Networks -Anomaly Detection Currently I lecture 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
Publications (14)
A Machine Learning Approach for Spare Parts Lifetime Estimation
Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
2022 | conference-paper
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
A Comparison of Anomaly Detection Methods for Industrial Screw Tightening
Computational Science and Its Applications - ICCSA 2021 - 21st International Conference, Cagliari, Italy, September 13-16, 2021, Proceedings, Part II
2021 | conference-paper
A Comparison of Machine Learning Approaches for Predicting In-Car Display Production Quality
Intelligent Data Engineering and Automated Learning – IDEAL 2021
2021 | book-chapter
Deep Dense and Convolutional Autoencoders for Machine Acoustic Anomaly Detection
2021 | book-chapter
Using deep autoencoders for in-vehicle audio anomaly detection
2021 | conference-paper
Deep Dense and Convolutional Autoencoders for Unsupervised Anomaly Detection in Machine Condition Sounds
2020 | preprint
A Categorical Clustering of Publishers for Mobile Performance Marketing
Advances in Intelligent Systems and Computing
2019 | book
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
Intelligent Data Engineering and Automated Learning – IDEAL 2019
2019 | book-chapter
A Comparison of Data-Driven Approaches for Mobile Marketing User Conversion Prediction
2018 International Conference on Intelligent Systems (IS)
2018 | conference-paper
Forecasting store foot traffic using facial recognition, time series and support vector machines
Advances in Intelligent Systems and Computing
2017 | book
Forecasting Human Entrances at a Commercial Store using facial recognition data
2015 | dissertation-thesis
A Machine Learning Approach for Spare Parts Lifetime Estimation
Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
2022 | conference-paper
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
A Comparison of Anomaly Detection Methods for Industrial Screw Tightening
Computational Science and Its Applications - ICCSA 2021 - 21st International Conference, Cagliari, Italy, September 13-16, 2021, Proceedings, Part II
2021 | conference-paper
A Comparison of Machine Learning Approaches for Predicting In-Car Display Production Quality
Intelligent Data Engineering and Automated Learning – IDEAL 2021
2021 | book-chapter
Deep Dense and Convolutional Autoencoders for Machine Acoustic Anomaly Detection
2021 | book-chapter
Using deep autoencoders for in-vehicle audio anomaly detection
2021 | conference-paper
Deep Dense and Convolutional Autoencoders for Unsupervised Anomaly Detection in Machine Condition Sounds
2020 | preprint
A Categorical Clustering of Publishers for Mobile Performance Marketing
Advances in Intelligent Systems and Computing
2019 | book
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
Intelligent Data Engineering and Automated Learning – IDEAL 2019
2019 | book-chapter
A Comparison of Data-Driven Approaches for Mobile Marketing User Conversion Prediction
2018 International Conference on Intelligent Systems (IS)
2018 | conference-paper
Forecasting store foot traffic using facial recognition, time series and support vector machines
Advances in Intelligent Systems and Computing
2017 | book
Forecasting Human Entrances at a Commercial Store using facial recognition data
2015 | dissertation-thesis
