Artificial Intelligence (AI) is revolutionizing the world of forecasting. It provides powerful tools to analyze complex datasets and make predictions with unprecedented accuracy. Time series forecasting, in particular, is a key area where AI has shown remarkable results, helping businesses and organizations make better decisions based on past and future trends.

In this seminar, we explored different AI-based approaches to time series forecasting and discussed their applications and benefits.

Participants joined this seminar to learn how AI can help unlock new insights and optimize their forecasting strategies.

Paulo S. G. de Mattos Neto received the Ph.D. degree in computer science from the Centro de Informática (CIn), Universidade Federal de Pernambuco (UFPE), Recife, Brazil, in 2012.  He joined the CIn/UFPE in 2014, where he is currently a professor, member of the Computational Intelligence Group, and coordinator of the Data Science post-graduation course. He has authored or coauthored articles in scientific journals and conferences on neural networks and time series forecasting in several applications, such as renewable energy, environment, health, and finance. He is a senior member of the IEEE and the Brazilian Computer Science Society. His current research interests include time series modeling, artificial neural networks, ensemble learning, and multiple forecaster system.

The session took place at Executive Room 4 at Colégio Almada Negreiros, located on the Campolide Campus.

Transports
Metro: S. Sebastião (Blue and Red Line); Praça de Espanha (Blue Line)
Carris: 701, 713, 716, 726, 742, 746, 756, 758, 770