I am a Canada Research Chair (Tier 1) on Spatiotemporal Ocean Data Analytics and a Professor at the Faculty of Computer Science of the Dalhousie University, Canada. I also hold appointments as an Associate Professor of the Department of Computer Science of the Faculty of Sciences of the University of Porto, Portugal, and as 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, where I act as Deputy Director of the institute and lead the Ocean Data Analytics research lab. At the Faculty of Computer Science of the same university I am the Head of the Research Cluster on Big Data Analytics, AI and Machine Learning. I am also a senior researcher of LIAAD / INESC Tec and an associate member of the Artificial Intelligence Institute of the University of Waikato.

My research revolves around the general area of Data Science, with a strong focus on Predictive Analytics for data with spatial, temporal or spatiotemporal dependencies. 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.

In case you want to know more about me you may have a look at my full CV.

Interests

  • Machine Learning and Data Science
  • Utility-based Predictive Analytics
  • Spatiotemporal Analytics
  • Ocean Data Analytics
  • Rare events
  • Forecasting

Education

  • PhD in Computer Science, 2000

    University of Porto, Portugal

  • Systems and Informatics Engineering, 1989

    University of Minho, Portugal

Main Research Lines

Ocean Data Analytics

Applying Data Science Methods to Ocean Data

Modeling Dependent Data

Forecasting models for dealing with data with dependencies (e.g. temporal, spatial, spatiotempora, etc.)

Imbalanced Distributions

Methods for handling predictive tasks with imbalanced distributions of the target variable

Explainable Machine Learning

Methods for helping end users to better understand complext machine learning models

Recent & Upcoming Talks

Time Series Forecasting, some challenges and possible solutions

Adressing the Data Revolution

Predictive Analytics and the Ocean

Utility-based Regression

Featured Projects

Nitrolimit

Life at the Edge - Define the Boundaries of the Nitrogen Cycle in the Extreme Antarctic Environments

DeepSense

A solution for data analytics in the ocean economy

MarinEye

A Prototype for a Multitrophic Ocean Monitoring

Online Observatory

Tools for detecting frauds on online digital advertisment

OpenML

An open, collaborative, frictionless, automated machine learning environment

Parfois

Sales Forecasting

Projects

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Nitrolimit

Life at the Edge - Define the Boundaries of the Nitrogen Cycle in the Extreme Antarctic Environments

DeepSense

A solution for data analytics in the ocean economy

MarinEye

A Prototype for a Multitrophic Ocean Monitoring

Online Observatory

Tools for detecting frauds on online digital advertisment

Parfois

Sales Forecasting

CORAL

Sustainable Ocean Exploitation, Tools and Sensors

REMINDS

Relevance Mining Detection System

News Summarization

Automatic extraction of (short) news summaries

OpenML

An open, collaborative, frictionless, automated machine learning environment

ePolicy

Engineering the POlicy-making LIfe CYcle

MORWAQ

Monitoring and Predicting Water Quality Parameters

oRanki

Resource-bounded Outlier Detection

MODAL

Models for Predicting Algae Blooms in River Douro

Recent and Forecoming Courses

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Foundations of Data Science using R

CSCI 3141, Faculty of Computer Science

Data Mining using R

Master of Science in Business Analytics, New York University

Spatio-Temporal Data Mining

1 day short course ACM SIGIR/SIGKDD Africa Summer School on Machine Learning for Data Mining and Search

Predictive Analytics

short course at the Porto Business School

Predictive Analytics using R

2 days short course at the Universitat Politecnica de Valencia

Past Courses

Advanced Predictive Analytics using R

1 day short course at the company LTPlabs

Data Mining I

MSc in Computer Science, Faculty of Sciences, University of Porto

Data Science in Practice

5 hours short course, IIMT Executive Programs

Fraud Detection

Master’s on Information Security, Faculty of Sciences, University of Porto

Temporal and Spatio-Temporal Data Mining using R

4 days course at Jozef Stefan Institute

Mentoring

PostDoc

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Vitor Cerqueira

Post Doctoral Fellow

PhD

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Marvin da Silva

PhD Student

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Luis Roque

PhD Student

MSc

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Vishnu Kandimalla

MSc Student

Former Mentoring Activities

Past PostDoc’s

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Paula Branco

Assistant Professor, U. Ottawa

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Collin Bellinger

NRC Research Officer

Past PhD’s

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Vitor Cerqueira

Post Doctoral Fellow

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Paula Branco

Assistant Professor, U. Ottawa

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Nuno Moniz

Post Doctoral Fellow and Invited Professor

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Brett Drury

Data Scientist

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Rita Ribeiro

Assistant Professor

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Pedro Almeida

Assistant Professor

Past MSc’s

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Deepan Shankar

MSc Student

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Carlos Leite

Data Scientist

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Paula Branco

Assistant Professor, U. Ottawa

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Luis Baia

Senior Data Scientist

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