Todd Eavis, PhD
Associate Professor, Computer Science and Software Engineering
Todd Eavis received his PhD in 2003 from Dalhousie University in Halifax and was an NSERC postdoctoral fellow at Carleton University in Ottawa. He joined the faculty of Concordia University in 2004, where he is currently an Associate Professor in the Department of Computer Science and Software Engineering. His general research focus is the design of scalable data management applications.
Dr Eavis's teaching includes courses with a focus on programming languages and system architectures. Classes that he has taught include:
- COMP 228: System Hardware
- COMP 248: Object Oriented Programming I
- COMP 249: Object Oriented Programming II
- COMP 346: Operating Systems
- COMP 352: Data Structures and Algorithms
- COMP 353: Databases
- COMP 428: Parallel Programming
- COMP 444: Systems Programming
- COMP 451: Database Design
- COMP 6411: Comparative Programming Languages (Graduate level)
- COMP 6521: Advanced Database Applications (Graduate level)
- Public Cloud architectures for analytics
- In-memory databases
- Distributed caches for relational query support
- Parallel algorithms and data structures
- Construction and indexing of data cubes
- Performance optimization for multi-dimensional DBMSs
For a full list of publications, please see Dr. Eavis's personal website. A small, random sample is included below:
- Omer Baluch and Todd Eavis, "Soft Real-time OLAP: Exploiting modern hardware without breaking the bank", 1st International Workshop on High Performance Computing for Big Data (in conjunction with the 43rd International Conference on Parallel Processing), Minneapolis, USA, 2014.
- A. Taleb, T. Eavis, and H. Tabbara, "Query optimization for the NOX OLAP algebra", LNCS Transactions on Large-Scale Data and Knowledge-Centered Systems, 2013.
- Todd Eavis and Ahmad Taleb, "Query optimization and execution in a parallel analytics DBMS", International Parallel and Distributed Processing Symposium (IPDPS), Shanghai, China, 2012.
- T. Eavis, X. Zheng, "Multi-level Frequent Pattern Mining", Database Systems for Advanced Applications (DASFAA), Brisbane, Australia, 2009.
- Y. Chen, F. Dehne, T. Eavis, and A. Rau-Chaplin, "PnP: Sequential, External Memory, and Parallel Iceberg Cube Computation", Journal of Distributed and Parallel Databases, 2008.
- Y. Chen, F. Dehne, T. Eavis, A. Rau-Chaplin, D. Green, E. Sithirasenan, cgmCube: Efficient Parallel Generation and Querying of Terabyte Size ROLAP Data Cubes", International Conference on Data Engineering (ICDE), Atlanta, USA, 2006.