• Artificial Intelligence in Medicine

Invited SpeakersProfile Details

Maxat Kulmanov
Maxat Kulmanov M. Kulmanov is a Ph.D. candidate at King Abdullah University of Science and Technology.


M. Kulmanov is a Ph.D. candidate at King Abdullah University of Science and Technology.
His interests are bioinformatics, knowledge representation and reasoning, machine learning,
neural networks, semantic web, and algorithms. He develops methods for knowledge
discovery and data integration using artificial intelligence and semantic web technologies
in biology and biomedicine. His research topic is "Predicting Gene Knockout Phenotypes".

All sessions by Maxat Kulmanov

  • Day 3Wednesday, February 20th
Session 6 : Spotlight on Young Talent ( Chair - John Archer)
2:00 pm

Vec2SPARQL: integrating SPARQL queries and knowledge graph embeddings

Recent developments in machine learning have led to a rise of large number of methods for extracting features from structured data. The features are represented as vectors and may encode for some semantic aspects of data. They can be used in a machine learning models for different tasks or to compute similarities between the entities of the data.
SPARQL is a query language for structured data originally developed for querying Resource Description Framework (RDF) data. It has been in use for over a decade as a standardized NoSQL query language. Many different tools have been developed to enable data sharing with SPARQL. For example, SPARQL endpoints make your data interoperable and available to the world. SPARQL queries can be executed across multiple endpoints. We have developed a Vec2SPARQL, which is a general framework for integrating structured data and their vector space representations. Vec2SPARQL allows jointly querying vector functions such as computing similarities (cosine, correlations) or classifications with machine learning models within a single SPARQL query. We demonstrate applications of our approach for biomedical and clinical use cases.

Building 9 - Lecture hall 2 14:00 - 14:15 Details