I am a Professor of Computer Science at the Faculty of Computer Science of the Dalhousie University, Canada, an Associate Professor of the Department of Computer Science of the Faculty of Sciences of the University of Porto, Portugal, and an invited professor of the Stern Business School of the New York University where I have been teaching in recent years at the Master of Science in Business Analytics.
At Dalhousie University I carry out my research in the context of the Institute for Big Data Analytics. I am also a senior researcher of LIAAD / INESC Tec, and a current member of the board of this research lab.
My research revolves around the general area of Data Science, with a strong focus on Predictive Analytics. Recently, I’ve been focusing my work on modelling rare events, with applications to fraud detection, prediction of extreme values and monitoring activities for anticipating anomalous behavior. I love to see my research being applied and thus I try to maintain a network of collaborations with researchers from other areas.
My favourite tool is the R programming language and environment. I am the author of the widely acclaimed Data Mining with R book published by CRC Press in 2010 with a strongly revised second edition that appeared in 2017.
I am also the CEO and one of the founding partners of KNOYDA a company devoted to training and consulting within data science.
PhD in Computer Science, 2000
University of Porto, Portugal
Systems and Informatics Engineering, 1989
University of Minho, Portugal
Life at the Edge: Define the Boundaries of the Nitrogen Cycle in the Extreme Antarctic Environments
Models for Predicting Algae Blooms in River Douro
Monitoring and Predicting Water Quality Parameters
Resource-bounded Outlier Detection
Sustainable Ocean Exploitation: Tools and Sensors
Relevance Mining Detection System
In 2017⁄18 I was teaching the following courses at University of Porto:
In the summer of 2018 I taught at the Master of Science in Business Anlytics of NYU the course:
Analyzing and Developing Indicators for Building an Automatic Detector of Fake News in Social Media