9:00 – 9:10Welcome
Chairs
9:10 – 10:30Keynote
How to Do Research for Fun and Profit
Dr. Divesh Srivastava (AT&T)
10:30 – 11:00Coffee Break
11:00 – 12:30Session 1: Data Warehousing, Lakes, Spatio-temporal Data, Streaming Data, and Multi-modal Data
Chair: Wonseok Lee
Towards Efficient Construction of a Traceable, Multimodal, and Heterogeneous Data Warehouse
Antoine Gauquier (DI ENS, ENS, CNRS, PSL University & Inria)
AI-Powered Orchestration of Multi-Model Data
Jáchym Bártík (Charles University)
Enhancing Security for Columnar Storage and Data Lakes
Lotte Felius (CWI)
Table Discovery in Data Lakes
Grace Fan (Northeastern University)
The Cases of Data Cleaning with Spatial and Temporal Awareness
Yuchuan Huang (University of Minnesota - Twin Cities)
Efficient Stream Processing in Decentralized Networks
Wang Yue (Hasso Plattner Institute, University of Potsdam)
12:30 – 14:00Lunch Break
14:00 – 15:30Session 2: ML for DB and DB for ML
Chair: Joohyung Yun
Better Learning from Graph Structures: Research on Representation Learning for Knowledge Graph Reasoning
Ke Liang (National University of Defense Technology)
On Efficient ML Model Training in Data Lakes
Wenbo Sun (Delft University of Technology)
Towards Flexible Self-Tuning Data Stream Management Systems
Wieger R. Punter (TU Eindhoven)
Instrumentation and Analysis of Native ML Pipelines via Logical Query Plans
Stefan Grafberger (BIFOLD & TU Berlin)
Autonomous Hierarchical Storage Management via Reinforcement Learning
Tianru Zhang (Uppsala University)
Automating Data Lineage and Pipeline Extraction
Sebastian Eggers (Technische Universität Berlin)
15:30 – 16:00Coffee Break
16:00 – 17:30Session 3: Scalable, Efficient, and Interpretable Data Processing Techniques
Chair: Stefan Grafberger
Time Series Analytics for Electricity Consumption Data
Adrien Petralia (EDF)
Vector Search on Billion-Scale Data Collections
Ilias Azizi (Mohammed VI Polytechnic University)
Parallel Algorithms Can Be Provably Fast and Scalable
Xiaojun Dong (University of California, Riverside)
Advancements in Parallel Graph Algorithms for Data Science: Scalable, Fast and Space-Efficient Solutions
Letong Wang (University of California, Riverside)
Towards Holistic Query Optimization for Datalog
Nick Rassau (Johannes Gutenberg-Universität Mainz)
Interpretable Feature Engineering for Structured Data
Mohamed BOUADI (Université Paris Cité, SAP Paris)
17:30 – 18:30Panel Discussion: Success in Ph.D. Journey
Moderator: Byungchul Tak (Kyungpook National University)
Mohammad Javad Amiri (Stony Brook University), Anthony Tung (National University of Singapore), Eleni Tzirita Zacharatou (IT University of Copenhagen)
