INTEC participates in IEEE CAMSAP 2025
The event, organized by the IEEE Signal Processing Society, was held in the country and included lectures, sessions, and technical presentations on adaptive signal processing, machine learning, and multisensor systems.
SANTO DOMINGO. - The Instituto Tecnológico de Santo Domingo (INTEC) participated in the 2025 IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (IEEE CAMSAP 2025), One most prestigious international events in the area of adaptive signal processing, machine learning algorithm y multisensor systems.
The activity, organized by the IEEE Signal Processing Society, in collaboration with the Johns Hopkins Data Science and AI Institute and Region of Madrid, gathered leading researchers, academics and professionals of universities and high-level research centers de America, Europe and Asia.
The workshop included plenary conferences, special sessions y technical presentations subjected to a rigorous peer review process, guaranteeing a scientific program of excellence.
As part of the activity, the professor of INTEC Engineering Area, Miguel Aybar Mejía, represented the institution both in the field academic as organizational, serving as Local Liaison Chair of the eventa key role for the local coordination and the success of the workshop in the country.
The participation of INTEC It materialized in the technical session “Machine Learning for Signal Processing Applications”where the research was presented “A machine learning approach to predicting energy consumption at electric vehicle charging stations”The study evaluates various machine learning models —ARIMA, Linear Regression, Random Forest, XGBoost and LSTM— for the energy demand forecast en electric vehicle charging stationsusing a set of 3,395 actual charging sessions.
The study was developed by Professors and graduates of the Master's Program in Data Science at INTEC, together with international collaborators, as part of the joint work with the Autonomous University of Yucatan and NETWORK RIBIERSE, of which INTEC is an active memberThe authors include Deyslen Mariano, David Aquino, Armando José Taveras, Edwin Sánchez, Miguel Aybar y Ali Bassam, Autonomous University of Yucatán (Mexico).
The results show that Random Forest and XGBoost offer the greater global accuracyWhile Linear regression and LSTM models They perform better in the peak demand prediction, contributing key tools for infrastructure planning, The optimization of energy resources and stability of the electrical grid.
El IEEE CAMSAP 2025 organizing committee It was made up of international researchers from institutions such as King Juan Carlos University (Spain), University of Rochester (USA), KU Leuven (Belgium), TU Delft (Netherlands), Rutgers University (USA), Johns Hopkins University (USA) and Chinese University of Hong Kong, among others.
With this type of contribution, INTEC continues to strengthen its academic leadership and its commitment to high-impact applied research, geared towards the technological and energy challenges of the present and the future.