I work on scalable vector search, graph-based approximate nearest neighbor search, and efficient retrieval systems for modern AI applications. My research spans algorithm design, large-scale experimentation, and high-performance vector indexing.
My research focuses on building scalable and efficient systems for searching high-dimensional vector collections, with particular emphasis on graph-based indexing and billion-scale retrieval.
Research on scalable graph-based vector search, efficient ANN indexing, and large-scale similarity search systems.
Research on scalable and energy-efficient vector retrieval systems and graph-based ANN algorithms.
Worked on large-scale graph-based vector search, indexing algorithms, and billion-scale retrieval optimization.
PhD on scalable high-dimensional vector similarity search, including graph-based ANN indexing and billion-scale retrieval.
Developed machine-learning models for predictive maintenance in industrial solar-energy systems.
I am interested in collaborations around vector databases, graph-based ANN, scalable retrieval, and efficient AI systems.
azizii.ilias@gmail.com →