Data Intensive Applications & Systems Laboratory

Despite recent technological advances both in the data management and in computer architecture domains, our ability to analyze data still falls behind the unstoppable data collection rates. Data-intensive applications are increasingly more demanding in sophisticated algorithms to store, manage, and interpret data.

Research in DIAS lab focuses on addressing these challenges by adapting data management technology to computer architecture trends, enabling discoveries in scientific domains through automating physical database design and revolutionizing exploration algorithms in very large data repositories. 

© 2024 Dimitra Tsaoussis (DIAS)

Celebrating DIAS' Achievements: Two more Doctors in the family

— Viktor Sanca and Aunn Raza, have successfully defended their theses this summer and earned their doctorates. Their journeys reflect years of dedication, intellectual curiosity, and relentless pursuit of knowledge, marking a significant milestone in their careers.

© 2024 IC DIAS

DIAS at the 2024 EDIC Open House

— Inspiring the Next Generation of Researchers at the EDIC Open House

© 2023 EPFL

DIAS research: publications accepted at EDBT and CIDR 2024

— The DIAS team will present their work on "Optimizing Goodput via Sharing for Batch Analytics with Deadlines" at EDBT 2024 and on "Oligolithic Cross-task Optimizations across Isolated Workloads" at CIDR 2024.

© 2023 DIAS

Highlights of the DIAS presence at SIGMOD and VLDB 2023

— In the summer of 2023 DIAS' research was presented both at SIGMOD and VLDB, two of the most prestigious conferences for Data Management.

© 2022 EPFL

DIAS wins the 2022 ACM SIGMOD Test-of-Time Award

— The ACM SIGMOD Test of Time Award for 2022 was given to the DIAS lab for the paper NoDB: Efficient Query Execution on Raw Data Files.

Two girls looking to the stars © iStock / EPFL 2022

Girl Power: Can we Break the Bias in Al and Beyond?

— We all know the story. It gets rolled out every March when women and men around the world celebrate International Women’s Day. Human biases are well documented, from the implicit to the explicit and they have always existed but as algorithms and big data increasingly run our lives these biases become embedded in everything.

© 2020 EPFL

My students are my biggest achievement

— EPFL Professor Anastasia Ailamaki wins the prestigious Women in Database Research Award and is appointed as a member of Academia Europaea.

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