\ifdef{\scivariant}{
\subtitle{Areas of expertise}{\faTasks}
\begin{categories}
	\category{}{Project Management and Technical Leadership}
	\category{}{Parallel and High Performance Computing}
	\category{}{Distributed Data Acquisition and Control Systems}
	\category{}{Performance Analysis and Software Optimization Techniques}
	\category{}{Parallel Algorithms and Parallel Hardware Architectures}
	\category{}{Low-latency Communication in Heterogeneous Systems}
	\category{}{Cloud-based Data Management and Visualization}
\end{categories}
}{
\subtitle{Key Competences}{\faTasks}
\begin{competences}
	\competence{Technical Leadership}{Project management, team leadership, presentations, proposals \& reports}%, Technical \& Financial Planning}
	\competence{System Architecture}{Distributed systems, microservice architectures, scalable data-intensive applications, high-bandwidth data acquisition and data-driven control}
	\competence{HPC}{High performance computing, parallel and distributed algorithms, approximate computing, performance modeling, code optimization}
	\competence{Infrastructure}{Orchestration with Kubernetes, time-series and array databases, CI/CD}
	\competence{Key Technologies}{C/C++, POSIX/IPC/Kernel, CUDA/OpenCL, NUMA, Remote-DMA}
\end{competences}
}






%Parallel programming with MPI, OpenMP, and CUDA · Multi-threaded and task-based concurrency (pthreads, std::thread) · Heterogeneous compute across CPUs and GPUs · Vectorization and memory hierarchy optimization (SIMD, AVX-512, NUMA)
%Design of scalable data acquisition and control systems · Real-time, low-latency networking using AF_XDP, DPDK, RDMA · Distributed messaging with gRPC and ZeroMQ · NUMA-aware system deployment
%Software profiling and tuning with VTune, perf, Nsight · Performance modeling and bottleneck analysis · Optimization of compute pipelines and memory access patterns
%Cloud-integrated data pipelines · Time-series and array databases (PostgreSQL, InfluxDB, TimescaleDB) · Monitoring and visualization with Grafana and custom dashboards
%Experience with Slurm, Ceph, and Lustre · HPC cluster design and job scheduling · Integration of HPC with cloud environments · Infiniband and RDMA-based networking
%CI/CD workflows and 

%Proficient in C/C++, Python, Bash · Git, Make/CMake, YAML/JSON · Familiarity with modern DevOps tools and practices
%Parallelism: MPI, OpenMP, CUDA, pthreads
%Optimization: VTune, perf, AVX-512, NUMA
%Infrastructure: Slurm, Kubernetes, Ceph, RDMA