Mario Nascimento

Professor, Faculty of Science - Computing Science
Associate Chair (Research), Faculty of Science - Computing Science


Professor, Faculty of Science - Computing Science
(780) 492-5678
4-34 Athabasca Hall
9119 - 116 St NW
Edmonton AB
T6G 2E8

Associate Chair (Research), Faculty of Science - Computing Science


Area of Study / Keywords

Spatiotemporal Data Management


Mario A. Nascimento is a Professor at the University of Alberta's Department of Computing Science and has served as the department's Chair between 2014 and 2021 (with a one-year leave in 2019-2020). 

Before joining the University of Alberta in 1999, he was a researcher with the Brazilian Agency for Agricultural Research and also an adjunct faculty member with the Institute of Computing of the University of Campinas. Mario has also been a visiting professor at the National University of Singapore's School of ComputingAalborg University's Department of Computer ScienceLMU's Institute for Informatics and at the Federal University of Ceara in Brazil.

His main research interests are contained in the area of spatiotemporal data management and according to Google Scholar his publications have been cited 4,500+ times earning him an H-index of 31. 

Besides often serving as a program committee member for the main database conferences, and as (co-)chair of several workshops and symposia, Mario has also served as ACM SIGMOD's Information Director (2002-2005), ACM SIGMOD Record's Editor-In-Chief (2005-2007), VLDB Journal's Editorial Board member (2011-2017).  He is currently a member of  GeoInformatica's Editorial BoardSSTD Endowment's Board of Directors (serving as its Chair) and also serves as a member of AltaML's Board of Directors.  

Finally, he finds it rather amusing writing about himself in the third person ...


Spatio-Temporal Data Management in general and in particular, routing and spatial crowdsourcing applications


CMPUT 191 - Introduction to Data Science

Introduction to data acquisition, basic data manipulation (cleaning, outlier detection), analysis (regression, clustering, classification), basic statistics and machine learning tools, information visualization to communicate information from data. Prerequisite: Math 30-1.

CMPUT 694 - Topics in Databases

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