News

June 2021: Tutorial at Distributed Event-Based Systems conference

The DaST group will give a tutorial on in-database machine learning at Distributed Event-Based Systems (DEBS) conference in June 2021.

May 2021: Honourable Mention for the 2021 SIGMOD Jim Gray Doctoral Dissertation Award

Former PhD student Maximilian Schleich was awarded an Honourable Mention for the 2021 SIGMOD Jim Gray Doctoral Dissertation Award for his DPhil dissertation entitled "Structure-Aware Learning over Multi-Relational Databases". The award recognizes excellent research by doctoral candidates in the database field.

May 2021: Invited Talk at Spotlight on Logic and Databases

Dr. Ahmet Kara and Prof. Dan Olteanu will give an invited talk on their work on trade-offs in incremental maintenance for query processing at the workshop Spotlight on Logic and Databases associated with the Highlights of Logic, Games, and Automata conference.

October 2020: LMFAO prototype released


LMFAO (Layered Multiple Functional Aggregate Optimisation) has been released in the public domain.

LMFAO 1.0 Repository https://github.com/fdbresearch/LMFAO

September 2020: Article accepted for ACM Transactions on Database Systems


Our article on functional aggregate queries with additive inequalities has been accepted for the ACM Transactions on Database Systems (TODS) special issue of best papers at ACM Principles of Database Systems (PODS) 2019.
A publicly available version of the article is on arxiv.

August 2020: VLDB'20 Keynote and System Demonstration


Dan Olteanu will give a keynote at Very Large Data Bases (VLDB) 2020. VLDB is an internationally premier forum for data management and database research in academia and industry.

  • The Relational Data Borg is Learning (Keynote) [arxiv]
    Dan Olteanu.
    In PVLDB 13(12): 3503 - 3516, 2020.
  • LMFAO: An Engine for Batches of Group-By Aggregates (Demonstration) [arxiv, video]
    Maximilian Schleich, Dan Olteanu.
    In PVLDB 13(12): 2945 - 2948, 2020.

June 2020: PODS'20 Paper and SIGMOD'20 System Demonstration


Check out videos and slides for our PODS and SIGMOD papers on incremental maintenance of queries and machine learning over evolving relational databases:

  • F-IVM: Learning over Fast Evolving Relational Data. (Demonstration)
    Milos Nikolic, Haozhe Zhang, Ahmet Kara, Dan Olteanu.
    In ACM SIGMOD 2020. [pdf, video]
  • Trade-offs in Static and Dynamic Evaluation of Hierarchical Queries.
    Ahmet Kara, Milos Nikolic, Dan Olteanu, Haozhe Zhang.
    In ACM PODS 2020. [arxiv, extended slides, video]

May 2020: Article accepted for ACM Transactions on Database Systems


Our article on worst-case optimal incremental maintenance for triangle queries has been accepted for the ACM Transactions on Database Systems (TODS) special issue of best papers at the International Conference on Database Theory (ICDT) 2019.
A publicly available version of the article is on arxiv.

May 2020: Article accepted for ACM Transactions on Database Systems


Our article on learning with sparse tensors and functional dependencies has been accepted for the ACM Transactions on Database Systems (TODS) special issue of best papers at ACM Principles of Database Systems (PODS) 2018.
A publicly available version of the article is on arxiv.

May 2020: PC Chair of ICDT 2022


Prof. Olteanu has been appointed Programme Committee Chair of the International Conference on Database Theory (ICDT) 2022. Together with PODS, ICDT is the main international forum for research in database theory.

May 2020: The DAST group is born


As of 1 May 2020 the Board of the University has appointed Dan Olteanu as Professor for Big Data Science.
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