Martin Kruliš

Martin Kruliš is an associate professor in the Department of Distributed and Dependable Systems at the Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic. His primary roles include research, teaching, advising, and leading projects that bridge high-performance computing, GPU programming, and self-adaptive systems.

Education: While exact details of his own degrees are not provided, Dr. Kruliš’s extensive publication record and faculty position at Charles University indicate advanced training in computer science with specialization in parallel and distributed computing.

Research Interests:

• High-Performance GPU Computing: Deep investigation into CUDA kernel optimization, memory bandwidth utilization, and workload dispatching for massively parallel accelerators.
• Self-Adaptive & Self-Optimizing Systems: Designing ensemble-based abstractions that integrate machine-learning estimators to enable runtime adaptation in component architectures.
• Parallel Algorithms & Data Structures: Development of cache-friendly, SIMD-aware, and GPU-accelerated algorithms for clustering, dimensionality reduction, and similarity search.
• Software Engineering for Parallelism: Creation of C++ libraries, DSLs (e.g., Bobolang), and educational tools (ReCodEx) that simplify parallel programming and automated evaluation.

Publication Trends: Across 2011–2025, Kruliš’s articles reveal a clear trajectory from foundational GPU-accelerated indexing and multimedia retrieval toward sophisticated self-adaptive systems that leverage machine learning. Recent works (2023–2025) increasingly focus on integrating LLMs and neural networks into compiler and runtime optimization loops, reflecting a convergence of AI and systems research.

Scientific Awards & Recognition:

• No specific awards or fellowships are mentioned in the provided text; however, sustained publication in top-tier venues (JPDC, IPDPS, Euro-Par, SEAMS) and active involvement in program committees and tool development indicate strong peer recognition.

Teaching & Student Supervision:

• Teaches Programming in Parallel Environment (NPRG042), Advanced Programming in Parallel Environment (NPRG058), Computer Systems (NSWI170), and Software Projects.
• Supervises numerous bachelor’s and master’s theses; exact student names are not listed in the text.

Labs, Projects & Tools:

• ReCodEx: A widely used platform for semi-automated evaluation of programming assignments at Charles University.
• Simdex: A modular simulator of the ReCodEx backend that enables realistic experimentation with self-adaptive job dispatching and machine-learning controllers.
• Active contributor to open-source repositories on GitHub, focusing on GPU kernels, benchmarking frameworks, and educational tooling.