Nott
Modern C++/CUDA deep-learning framework, focused on fast prototyping, explicit control over kernels, memory layout, and runtime execution.
// introduction
Focus
tooling, observability, performance engineering
Stack
Lang — C++20, Python, TypeScript, Bash
Perf — ASM, SIMD (SSE/AVX), CUDA
Tools — CMake, GDB, Perf
Infra — Docker, Linux, SQL
Currently
Open to C++ SWE opportunities
// projects
Modern C++/CUDA deep-learning framework, focused on fast prototyping, explicit control over kernels, memory layout, and runtime execution.
Single-header C++20 failure-handling framework for low-latency, deterministic, and reliable systems.
Header-only C++ telemetry framework for nanosecond-scale profiling in real-time systems.
Zero-dependency C++17 2D plotting library
ArXiv paper discovery and recommendation app
Real-time analytics Web-Dashboard for trading.
Homelab for Database/Experiments
Voxel-based Multi-Physics Topology Optimizer
Multi-language ASCII call-graph generator for source trees
// research notes
ML model for classification of regime-switches. To achieve better Discretionary-tool calibration.
Binary Decision Tree model for multi-segmentation classification of satellite images.
Multi-level knowledge graph for token-efficient LLM code generation
// contact
Available for C++ SWE