Papaemmanouil Receives Funding from Huawei Technologies

Olga PapaemmanouilShenzhen-based Huawei Technologies, the largest manufacturer of telecom equipment in the world, is supporting Associate Professor of Computer Science Olga Papaemmanouil‘s efforts to develop machine learning approaches for managing the performance of data management systems. The grant will support research on workload management, that is the task of query placement, query scheduling and resource allocation for database applications. Workload management is an extremely critical task for database systems as it can impact the execution time of incoming processing tasks as well as the overall perceived performance of the database  and the quality of the service (QoS) offered to end-clients. The complexity of the problem increases for applications that involve dynamically changing workloads and concurrently executing queries sharing the same underlying resources, as well as applications that are deployed on data clusters with fluctuating resource availability.

Dr. Papaemmanouil’s research aims to design frameworks that can be trained on application-specific properties and performance metrics  to automatically learn how to effectively dispatch incoming queries across a cluster of servers, implicitly solving the resource allocation challenge. These techniques will rely on machine learning algorithms (reinforcement learning and deep learning)  that model the interaction of concurrently running queries  as well as the relationship between database performance and the underlying resource availability in the cluster. The project will lead the way towards the development of workload management solutions that eliminate ad-hoc heuristics often used by database administrators to address these challenges and replace them with software modules capable of providing custom workload management strategies to end-clients.

Papaemmanouil gets NSF CAREER grant

Assistant Professor of Computer Science Olga Papaemmanouil has received a Faculty Early Career Development (CAREER) award from the National Science Foundation (NSF), a highly selective grant that the National Science Foundation awards to junior faculty members who are likely to become academic leaders of the future.

The research project funded by Olga’s CAREER grant (“Towards Extensible Performance Management for Cloud Data Services“) aims to a) develop declarative mechanisms that allow application developers to express custom performance criteria for data processing tasks and b) exploit the properties of these mechanisms to design extensible resource, workload and Service-Level-Agreement (SLA) management services for cloud databases.

The project also includes the design and development of XCloud, an extensible cloud-based platform that will unify these services into a usable cloud utility. The XCloud platform is expected to have a significant research and educational impact as it will act as a test-bed for new performance models and diverse performance management techniques for cloud databases facilitating research and innovation in the emerging domain.

The Faculty Early Career Development (CAREER) Program is a Foundation-wide activity that offers the National Science Foundation’s most prestigious awards in support of junior faculty who exemplify the role of teacher-scholars through outstanding research, excellent education and the integration of education and research within the context of the mission of their organizations. Such activities should build a firm foundation for a lifetime of leadership in integrating education and research.

Olga received her B.S. in Computer Engineering from the University of Patras, Greece, and completed her Ph.D. in Computer Science at Brown University in 2008. She joined the Computer Science Department at Brandeis in January 2009.

Other Brandeis science faculty receiving CAREER grants since 2010 include Christine Thomas (Chemistry), Aparna Baskaran, Matthew Headrick, and Zvonimir Dogic (all Physics).

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