I'm a Reader (Associate Professor) in the
School of Informatics,
University of Edinburgh. My research focuses on the fundamentals, design and optimisation of database systems, including, recently, the intersection between databases and machine learning, like
this and
this.
I have specifically been working on the following topics (check my
Publications for more details):
- Vector Databases and Universal Representation:
- discovery of the geometric local consistency across different embedding spaces and its potential for data integration of vector databases across different embedding models: SIGMOD'26 (Best Paper Honorable Mention)
- theoretical justification of the local consistency phenomenon for contrastive encoders, and its application for
vector linking across vector databases embedded by different models: ICML'26a
- generalizable and composable multi-model embedding interoperability with local consistency: ICML'26b (Spotlight)
- Rethinking classic database concepts:
- Graph computing frameworks: graph auto-vectorization (e.g., SIGMOD'25 SIGMOD Research Highlight Award) and auto-parallelization (e.g., SIGMOD Best Paper Award and SIGMOD Research Highlight) frameworks
