Dr Renata Borovica-Gajic

  • Room: Level: 07 Room: 03
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • Data Structures (Indexing Structures, Cache Replacement Algorithms)
  • Database Management (Big Data Exploration, Scientific Data Management)
  • Database Management in the Cloud

Personal webpage



Renata Borovica-Gajic holds a position of Lecturer in Data Analytics in the School of Computing and Information Systems at The University of Melbourne. Dr Borovica-Gajic received her PhD degree in Computer Science from École Polytechnique Fédérale de Lausanne (EPFL), Switzerland in 2016. During her studies she worked in the Data-Intensive Applications and Systems Laboratory (DIAS), supervised by Prof. Anastasia Ailamaki. Prior to joining EPFL, she worked in industry for 5 years as a senior member of the database team of a power engineering company. She simultaneously completed her Master’s studies in Electrical and Computer Engineering, receiving a Serbian national award for the best Master’s thesis in the field of mathematics and computer science.

Renata’s research focuses on solving data management problems, when storing, accessing and processing massive data sets, enabling faster, more predictable, and cheaper data analysis as a result. She builds intelligent database systems that are able to automatically adjust query processing strategies to comply with the characteristics of data, hardware and usage patterns. She is also interested in the topics of scientific data management, big data exploration, query optimisation, physical database design, and hardware-software co-design.

Recent publications

  1. Xu Y, Qi J, Borovica-Gajic R, Kulik L. Finding all nearest neighbors with a single graph traversal. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2018, Vol. 10827 LNCS. DOI: 10.1007/978-3-319-91452-7_15
  2. Borovica-Gajic R, Idreos S, Ailamaki A, Zukowski M, Fraser C. Smooth Scan: robust access path selection without cardinality estimation. VLDB Journal. Springer. 2018. DOI: 10.1007/s00778-018-0507-8
  3. Borovica-Gajic R, Graefe G, Lee A. Robust Performance in Database Query Processing (Dagstuhl Seminar 17222). Dagstuhl Reports. 2017, Vol. 7, Issue 5. DOI: 10.4230/DagRep.7.5.169
  4. Appuswamy A, Borovica-Gajic R, Graefe G, Ailamaki A. The Five-minute Rule Thirty Years Later and its Impact on the Storage Hierarchy. 8th International Workshop on Accelerating Analytics and Data Management Systems Using Modern Processor and Storage Architectures (ADMS). Schloss Dagstuhl. 2017.
  5. Borovica-Gajic R, Appuswamy R, Ailamaki A. Cheap Data Analytics using Cold Storage Devices. PROCEEDINGS OF THE VLDB ENDOWMENT. VLDB Endowment. 2016, Vol. 9, Issue 12.
  6. Ailamaki A, Idreos S, Alagiannis I, Borovica-Gajic R, De Oliveira Branco MS. Query management system and engine allowing for efficient query execution on raw details. (Patent no. )
  7. Alagiannis I, Borovica-Gajic R, Branco M, Idreos S, Ailamaki A. NoDB: Efficient Query Execution on Raw Data Files. COMMUNICATIONS OF THE ACM. Association for Computing Machinery Inc.. 2015, Vol. 58, Issue 12. DOI: 10.1145/2830508
  8. Borovica-Gajic R, Idreos S, Ailamaki A, Zukowski M, Fraser C. Smooth Scan: Statistics-oblivious access paths. Proceedings - International Conference on Data Engineering. IEEE Computer Society. 2015, Vol. 2015-May. DOI: 10.1109/ICDE.2015.7113294
  9. Borovica-Gajic R, Alagiannis I, Ailamaki A. Automated physical designers: What you see is (Not) what you get. Proceedings of the 5th International Workshop on Testing Database Systems, DBTest'12. 2012. DOI: 10.1145/2304510.2304522
  10. Alagiannis I, Borovica-Gajic R, Branco M, Idreos S, Ailamaki A. NoDB in action: Adaptive query processing on raw data. Proceedings of the VLDB Endowment. VLDB Endowment. 2012, Vol. 5, Issue 12. DOI: 10.14778/2367502.2367543
  11. Alagiannis I, Borovica-Gajic R, Branco M, Idreos S, Ailamaki A. NoDB: Efficient query execution on raw data files. Proceedings of the ACM SIGMOD International Conference on Management of Data. 2012. DOI: 10.1145/2213836.2213864