DARE Lab

Bridging the gap between users and data.

Athena Research Center
Athens, Greece
Data is considered the 21st century's most valuable commodity and is growing at an exponential rate. Despite technological advances both in the data exploration and data management domains, our ability to leverage data still falls behind in bridging the chasm between users and data.

Our research emerges at the intersection of data management, deep learning, natural language processing, and the ethical aspects of AI. We are specifically investigating how AI can help us build tools that enable seamless access to different types of data: This starts from the lowest level of how to understand data and queries and learn how to best process user queries, going up the data stack closer to the user, where the goal is to understand user intention and enable a more natural dialogue with the data, while ensuring that fairness and ethical considerations are integral to this process.


Research Areas

News

Jun 19, 2024 Our paper “Analysis of Text-to-SQL Benchmarks: Limitations, Challenges and Opportunities” has been accepted at EDBT/ICDT 2025!
Mar 25, 2024 We are over the moon to share that our latest work, “Optimizing Neighborhoods for Fair Top-N Recommendation”, has been accepted at UMAP’24 held in Sardinia, Italy! It is time to pack the sunscreen and grab those sunglasses—we are bringing fairness in recommenders to the beach 🏖️
Mar 10, 2024 We are thrilled to announce that our research paper, “Guided SQL-based Data Exploration with User Feedback”, has been accepted at ICDE’24!
Nov 23, 2023 Ismini Bouliari just defended her master thesis, “Mitigating Popularity Bias in Recommender Systems: A Hybrid Approach with KoalaRec”. Time to pop the champagne and celebrate🍾🎉
Nov 20, 2023 ScienceBenchmark has been accepted at VLDB’24! This is a joint work with ZHAW on Text-to-SQL benchmarking and data augmentation for complex scientific DBs.

Selected Publications

  1. EDBT
    QPSeeker: An Efficient Neural Planner Combining Both Data and Queries through Variational Inference
    In Proceedings 27th International Conference on Extending Database Technology, EDBT 2024, Paestum, Italy, March 25 - March 28
  2. VLDBJ
    A Survey on Deep Learning Approaches for Text-to-SQL
    The VLDB Journal
  3. UMAP
    Optimizing Neighborhoods for Fair Top-N Recommendation
    Eleftherakis, Stavroula, Koutrika, Georgia, and Amer-Yahia, Sihem
    In Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization
  4. ICDE
    Guided SQL-Based Data Exploration with User Feedback
    Mandamadiotis, Antonis, Koutrika, Georgia, and Amer-Yahia, Sihem
    In 2024 IEEE 40th International Conference on Data Engineering (ICDE) May

Funding