Mario Nascimento

Professor & Chair


Computing Science

About Me

Mario A. Nascimento is a Full Professor at (and since July/2014 serves as Chair of) the University of Alberta's Department of Computing Science. He earned his PhD in 1996, and 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. In addition, Mario has been a visiting professor at the National University of Singapore's School of Computing (Fall/2005), Aalborg University's Department of Computer Science (Winter/2006), LMU Munich (Fall/2013-Winter/2014) and also had an appointment as Visiting Professor at the Federal University of Ceara in Brazil (2013 and 2014). According to Google Scholar (as of July/2015) his publications have been cited 2,750+ times, earning him an H-index of 27. His main research interests lie in the areas of Spatio-Temporal Data Management and Data Management for Wireless Sensor Networks. 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) and ACM SIGMOD Record's Editor-In-Chief (2005-2007). He is currently a member of the VLDB Journal's Editorial Board, the SSTD Endowment's Board of Directors, and has been a senior member of the ACM since 2007. Finally, he finds it amusing writing about himself in the third person.


Spatio-Temporal Data Management: Spatio-temporal data has always existed, but is becoming more and more commonly available and usable nowadays, therefore generating demand for more effective and efficient data management techniques. At a very high level, the task at hand is managing with who was where and when. A few sample application scenarios are as follows. Rental car companies can track their fleet using GPS devices installed in the vehicles in order to verify whether the rental contract was violated. Cell phones can also be equipped with GPS devices which, for instance, would facilitate the location of the person carrying it when an emergency call is placed and/or provide location-based services. Animals behaviour (or changes thereof) can also be seen as spatio-temporal data. In particular, one could correlate changes of behaviour to changes in the environment. Another application could be to proactively advise drivers of current road accidents based on their usual driving routine.  

Data Management in Sensor Networks: A close and relatively new research topic related to spatio-temporal data is that of data management on (ad-hoc) wireless sensor networks. For instance, using this paradigm, (very small) sensors can be spread over a large area (e.g., a forest) in order to gather and store data which can be used for (a posteriori) query processing. A chief concern in this environment is to minimize the energy consumption during the network's lifetime, in particular during query processing time. Numerous issues, previously researched under the umbrella of distributed databases and stream processing, require new research within this new framework. A typically neglected "interface" area in this domain is that of data communication/networks and all such issues become even more complex when nodes are mobile.