Luis Miguel Da Rocha De Matos is an Assistant Professor in the Department of Information Systems and Technologies at Universidade Lusófona, Lisbon, Portugal. He is affiliated with the ALGORITMI Research & Development Center (IDS Group), where he contributes to cutting-edge research in artificial intelligence and machine learning applications in industrial and commercial domains. His research focuses on Machine Learning, Artificial Intelligence, Anomaly Detection, Predictive Maintenance, and Data Preprocessing . He develops intelligent systems for industrial monitoring, worker safety, and marketing optimization, leveraging deep learning, time series analysis, and AutoML techniques. His work bridges theoretical innovation with practical deployment in real-world settings. The analysis of his recent publications reveals a consistent trend toward applying advanced machine learning methods—particularly deep learning and unsupervised models—to solve industrial challenges such as production defect prediction, acoustic anomaly detection, and ergonomic risk prevention. His research spans multiple sectors including manufacturing, automotive, textiles, and digital marketing. His scientific contributions have been recognized with honors including: Best Paper Award at ICCSA 2021 Conference He actively contributes to the academic community as a peer reviewer for Q1 and Q2 journals and participates in scientific committees, session chairing, and workshops. His software contributions include the open-source Python module Cane , widely adopted for categorical data transformation. He also engages in public outreach through keynotes and media appearances. He is involved in major research initiatives such as Factory of the Future, TexBoost, and EasyRide , which focus on digitizing and optimizing industrial processes using AI-driven decision support systems.






