
Professor Timos Sellis
PhD in Computer Science, University of California, Berkeley, United States; MSc in Computer Science, Harvard University, United States; Diploma in Electrical Enginerring, National Technical Univ. of Athens, Greece
- Faculty of Science, Engineering & Technology
- School of Software and Electrical Engineering
- Department of Computer Science and Software Engineering
- EN506c Hawthorn campus
- ORCID profile
Biography
Professor Timos Sellis is Director of Swinburne’s Data Science Research Institute. His research interests include big data, data streams, personalisation, data integration, and spatio- temporal database systems.
Professor Sellis is an IEEE Fellow for his contributions to database query optimisation and spatial data management. He is also an ACM Fellow for his contributions to database query optimisation, spatial data management and data warehousing.
Up until 2012 Professor Sellis was Director of the Institute for the Management of Information Systems and a Professor at the National Technical University of Athens. He holds an MSc degree from Harvard University, a PhD from the University of California at Berkeley, and has served as president of the National Council for Research and Technology of Greece.
Research interests
Database Systems; Data Science; Big Data
PhD candidate and honours supervision
Higher degrees by research
Accredited to supervise Masters & Doctoral students as Principal Supervisor.
Fields of Research
- Database Management - 080604
- Global Information Systems - 080606
Teaching areas
Database Systems
Awards
- 2018, International, Impact Award, IEEE TCDE
- 2013, International, ACM Fellow, ACM
- 2009, International, IEEE Fellow, IEEE
Publications
Also published as: Sellis, Timos; Sellis, T.; Sellis, Timoleon
This publication listing is provided by Swinburne Research Bank. If you are the owner of this profile, contact us to update.
Recent research grants awarded
- 2018: Linked semantic platforms for social & physical infrastructure & wellbeing *; ARC Linkage Infrastructure and Equipment Scheme
- 2017: Identifying technological trajectories using machine learning algorithms *; ARC Linkage Projects Scheme
- 2017: Trajectory Data Processing - Spatial Computing meets Information Retrieval *; ARC Discovery Projects Scheme
- 2016: Effective and Efficient Query Processing over Dynamic Social Networks *; ARC Discovery Projects Scheme
- 2016: Sonepar Data and Predictive Analytics *; Sonepar Asia Pacific Ltd
* Chief Investigator
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