Anastassia Ailamaki

The Project

Efficient data management for Scientific applications 


Dr. Anastasia Ailamaki
Ecole Polytechnique Fédérale de Lausanne
Station 14, building BC
1015 Lausanne

Thirty-eight year old Greek citizen, Anastasia Ailamaki, is an associate professor at Carnegie Mellon University. In addition to receiving a Sloan Research Fellowship in 2005, she has won five best paper awards and the NSF Faculty early CAREER award in 2002.  Ailamaki is also an associate editor of the IEEE Data Engineering Bulletin and has organised numerous international conferences.  She gained her PhD in computer science at the University of Wisconsin.

Project Description

Several scientific applications are constrained by the complexity of manipulating massive datasets.  Observation-based sciences, such as astronomy, face immense data placement problems, whereas simulation-based sciences, such as earthquake modeling, must deal with complexity.  Efficient data management by means of automated data placement and computational support can push the frontiers of scientists' ability to explore and understand massive scientific datasets.

With this project Ailamaki and her team will design, analyse, implement, and evaluate algorithms to:
(1) Understand and evaluate the nature of datasets and queries used in astronomy and in earthquake modeling;
(2) Automate all schema specification and data placement procedures as well as index creation for scientific datasets;
(3) Simultaneously simplify domain-specific programming and greatly increase the scale of problems that can be studied efficiently.