I design high-performance, mathematically grounded software systems for scientific data analysis.
- C++ / performance-critical systems
- Python data architectures
- Distributed workloads (Slurm, PBS)
- ETL pipelines and large-scale analysis
- Graph-level optimisation and execution design
- Lena – Functional framework for composable scientific data analysis
- ROOT/RDataFrame optimisation – HPC-oriented analysis pipelines
- Custom C++ modelling libraries – High-throughput computational systems
- yarsync (Debian/Ubuntu) – File synchronisation tool
- Architecture first
- Separation of mathematical logic and execution backend
- Reproducibility and long-term maintainability
- Performance without sacrificing clarity
- PhD Candidate in Physics | RWTH Aachen, Germany
- MS in Applied Physics and Mathematics | Moscow Institute of Physics and Technology (Global Top 100 for Physics and Mathematics, Global Top 10 for Competitive Programming (ICPC)) | Diploma with distinction, Potanin scholarship
- MS in Mathematics | Independent University of Moscow (Founded by world-renowned mathematicians, 3-4 graduates per year)