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Dimitris Tsitsigkos

@dimitristsitsigkos

I build high-performance in-memory data systems for scalable query processing.

I've built high-performance in-memory indexing and spatial data-processing systems at Athena Research Center, the University of Ioannina, and Archimedes Research. My C++ work has improved query throughput, reduced memory consumption, and processed spatial joins involving tens of millions of rectangles in under one second on multi-core systems.

I've also developed Java and Spring backends, RESTful APIs, distributed Hadoop and HBase components, and parallel Python analytics with Dask. My work spans data structures, performance optimization, parallel computing, spatial queries, and real-time energy data processing.

Experience

Work history, roles, and key accomplishments

Postdoctoral Researcher

Archimedes Research on AI, Data Science and Algorithms

Feb 2025 - Mar 2026 (1 year 1 month)

Designed and implemented high-performance in-memory multi-dimensional indices in C++ using parallelism and hardware-aware optimizations to improve query throughput and latency. Worked on data structures and algorithms with a focus on efficient memory access, CPU utilization, and multi-core scalability.

C++OpenMP SIMD

Education

Degrees, certifications, and relevant coursework

University of Ioannina

Doctor of Philosophy, Data Management

2019 - 2024

Activities and societies: Visiting Researcher, Institute of Computer Science, Data Management Research Group, Johannes Gutenberg University Mainz, Germany (May 2022 – Jul 2022)

PhD in Data Management, completed in collaboration with Athena Research Center. Thesis on in-memory indexing for parallel processing of single and multi-dimensional queries.