Stavros received his Ph.D. in Computer Science from Carnegie Mellon,
in 2005. Through 2007, he worked as a Post-Doctoral researcher
at the DB group of MIT where he was an early contributor to the
projects (commercialized by
Until recently he was a Senior Research Scientist in the
Information Analytics Lab of Hewlett-Packard.
Stavros's interests and expertise are in column-store databases,
main-memory databases, query processing on new processor
and storage technologies,
and energy-efficient data management systems.
Energy-efficiency in large data centers, when running data management
and analysis tasks, will ultimately be controlled and improved
at the software layer. Our SIGMOD'10 and VLDB'12 papers present the first
comprehensive studies on the energy efficiency of single-node and multi-node
database servers. CloudAlloc and Micro-Cellstores explore
practical applications of energy-saving data system designs.
The hardware landscape is rapidly changing. Flash SSDs, multi-core CPUs,
GPU co-processing, deep memory hierarchies, are all here; PC RAM and memristors
are around the corner. Our work in this area studies how data management
platforms can best benefit by new and upcoming technologies.
Main-memory scale-out SQL/noSQL engines are taking off. Our papers
aim at paving the way through a design starting point,
a very fast reference implementation, and a detailed performance analysis
of OLTP engine components.
Columnar storage is emerging as the prevalent format for building
high-performance data-analytics engines. Our VLDB’06 paper analyzed the
performance tradeoffs of columns vs. rows, and our
explored columnar storage on SSDs along with columnar out-of-core joins.