Olga Papaemmanouil

Associate Professor
Department of Computer Science
Brandeis University

Email: {olga}@cs.brandeis.edu
Phone: +1-781-736-2716
Fax: +1-781-736-2741
Address: Department of Computer Science,  MS 018
415 South St, Waltham, 02454, MA, USA
Office
Volen 214

 

Research interests

My research interests are in the general area of data management and distributed systems with a recent focus on using machine learning techniques for data management problems, such as query optimization, data exploration, query performance prediction and resource provisioning and workload management on cloud-based systems.


Awards and Funding

My research has been funded by the following sources:
  • Amazon Research Award on Query Performance Modeling via Deep Learning (2019)
  • NSF Award on Automatic Learning-based Services for Distributed Data Management Systems (2018-2021)
  • Huawei Innovation Research Award on Redesigning Database Query Optimizers using Deep Learning (2018)
  • Huawei Innovation Research Award on Learning-based Performance Management Under Concurrent Query Executions (2017)
  • NSF Career Award on Extensible Performance Management for Cloud Data Services (2012-2018)
  • NSF Award on Development Environment for Query Optimizer Engineering (20012-2016)
  • NSF Award on Interaction History Management Services and their Applications to Evidence-based Practice of Healthcare (2010-2013)
  • Educational Credits from Amazon AWS and Google Cloud Platform

Students (PhD)
  • Chi Zhang (2018-today)
  • Ryan Marcus (First position: postdoc at MIT, 2019)
  • Zhan Li (First employment: Oracle, 2017)
  • Kyriaki Dimitriadou (First employment: Amazon, 2017)

Selected Publications [DBLP] [Google Scholar]
Curriculum Vitae
  • Flexible Operator Embeddings via Deep Learning, Ryan Marcus, Olga Papaemmanouil. January 2019, arXiv.org [pdf]

  • Plan-Structured Deep Neural Networks for Query Performance Prediction, Ryan Marcus, Olga Papaemmanouil. January 2019, arXiv.org [pdf]

  • Towards a Hands-Free Query Optimizer through Deep Learning, Ryan Marcus, Olga Papaemmanouil, In Proceedings of the 9th Biennial Conference in Innovative Data Systems Research (CIDR 2019) [pdf]

  • Deep Reinforcement Learning for Join Order Enumeration, Ryan Marcus, Olga Papaemmanouil, In Proceedings of the 1st International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, SIGMOD Workshops (aiDM 2018). [pdf]

  • NashDB: An Economic Approach to Fragmentation, Replication and Provisioning for Elastic Databases , Ryan Marcus, Olga Papaemmanouil, Sofiya Semenova, Solomon Garber,  In Proceedings of 37th ACM Special Interest Group in Data Management (SIGMOD 2018). [pdf]

  • A Learning-based Service for Cost and Performance Management of Cloud Databases (Demonstration), Ryan Marcus, Sofiya Semenova, Olga Papaemmanouil, In  Proceedings of 33rd  IEEE International Conference on Data Engineering (ICDE  2017). [pdf]

  • Releasing Cloud Databases from the Chains of Predictions Models. Ryan Marcus, Olga Papaemmanouil. In Proceedings of the 8th Biennial Conference in Innovative Data Systems Research (CIDR 2017). [pdf]

  • Interactive Data Exploration via Machine Learning Models, Olga Papaemmanouil, Yanlei Diao, Kyriaki Dimitriadou, Liping Peng. In Proceedings of IEEE Data Engineering Bulletin (invited paper), Volume 39, Issue 4, pages 21-30, December 2016. [pdf]

  • AIDE: An Active Learning-based Approach for Interactive Data Exploration. Kyriaki Dimitriadou, Olga Papaemmanouil, and Yanlei Diao. IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume 28, Issue 11, pages 2842 - 2856, November 2016. [pdf]

  • OptMark: A Toolkit for Benchmarking Query Optimizers,  Zhan Li, Olga Papaemmanouil, Mitch Cherniack. In Proceedings of 25th ACM International Conference on on Information and Knowledge Management (CIKM  2016).  [pdf] [long version]

  • WiSeDB: A Learning-based  Workload Management Advisor for Cloud Databases, Ryan Marcus, Olga Papaemmanouil. In Proceedings of  the Very Large Databases Endowment (PVLDB 2016). Volume 9, Issue 10, pages 780-791. [pdf]

  • AIDE: An Automatic User Navigation Service for Interactive Data Exploration (Demonstration), Yanlei Diao, Kyriaki Dimitriadou, Zhan Li, Wenzhao Liu, Olga Papaemmanouil, Kemi Peng, Liping Peng. In Proceedings of 41st International Conference on Very Large Databases (VLDB 2015) [pdf]
  • Overview of Data Exploration Techniques (Tutorial), Stratos Idreos, Olga Papaemmanouil, Surajit Chaudhuri. In Proceedings of 34th ACM Special Interest Group in Data Management (SIGMOD 2015). [pdf] [slides] (the slides cover part 1 (User Interaction) and part 2 (Middleware Optimizations))

  • Skew-Aware Join Optimization for Array Databases, Jenny Duggan, Olga Papaemmanouil, Leilani Battle, Michael Stonebraker. In Proceedings of 34th ACM Special Interest Group in Data Management (SIGMOD 2015). [pdf]
  • Explore-by-Example: An Automatic Query Steering Framework for Interactive Data Exploration, Kyriaki Dimitriadou, Olga Papaemmanouil, Yanlei Diao. In Proceedings of 33rd ACM Special Interest Group in Data Management (SIGMOD 2014). [pdf]
  • Contender: A Resource Modeling Approach for Concurrent Query Performance Prediction, Jenny Duggan, Olga Papaemmanouil, Ugur Cetintemel, Eli Upfal. In Proceedings of 17th International Conference on Extending Database Technology (EDBT 2014). [pdf]
  • Devel-Op: An Optimizer Development Environment (Demonstration), Zhibo Peng, Mitch Cherniack, Olga Papaemmanouil. In Proceedings of 30th IEEE International Conference on Data Engineering (ICDE  2014). [pdf]

  • Performance Prediction for Concurrent Database Workloads, Jennie Rogers, Ugur Cetintemel, Olga Papaemmanouil, Eli Upfal. In Proceedings of the 30th ACM Special Interest Group on Management of Data (SIGMOD 2011). [pdf]

Recent Service
  • Publicity Chair SoCC 2019
  • PC co-Chair BigVis 2018, BigVis 2019
  • Area Chair ICDE 2017
  • Associate Editor SIGMOD Record (since 2015)
  • PC Member: SIGMOD 2019 (demo), CIDR 2019, VLDB 2019, VLDB 2018, SIGMOD 2018 (Demo), CIDR 2017, VLDB 2016, ICDE 2016, SIGMOD 2016

Teaching
  • COSI 132b - Networked Information Systems: Spring 2018, Fall 2016, Fall 2013, Fall 2012, 
  • COSI 228a - Topics in Distributed Systems: Fall 2015 (Big Data Exploration), Fall 2011 (Cloud Databases), Fall 2009 (Web Scale Data Management)
  • COSI 129a - Introduction to Big Data Analysis: Fall 2014
  • COSI 12b- Advanced Programming Techniques: Fall 2018, Fall 2017, Spring 2016, Spring 2015, Spring 2012, Spring 2011, Spring 2010 

Short Bio

Olga Papaemmanouil is an  Associate Professor in the Department of Computer Science at Brandeis University. She received her undergraduate degree in Computer Science and Informatics at the University of Patras, Greece in 1999. In 2001, she received her Sc.M. in Information Systems at the University of Economics and Business, Athens, Greece. She then joined the Computer Science Department at Brown University, where she completed her Ph.D in Computer Science at Brown University in 2008. Her research interests are in  databases  and distributed data management with a recent focus on applying machine learning techniques to solve traditional data management problems. She is the recipient of an Amazon Research Award (2019), two Huawei Innovation Research Awards (2018, 2017), an  NSF Career Award (2013), a Best Demonstration Award (SIGMOD 2015), a Paris Kanellakis Fellowship (2002) and multiple NSF grants.