Nott
Modern C++/CUDA deep-learning framework, focused on fast prototyping, explicit control over kernels, memory layout, and runtime execution.
// introduction
Focus
automation, observability, low-latency
Stack
Lang — C++20, Python, Julia, Bash
Perf — ASM, CUDA, Perf, GDB
ML — Torch
Infra — Docker, Linux, SQL
Currently
Open to opportunities as C++ SWE, Automation Developer or low-level C++
// 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
// research notes
Markowitz-based portfolio, quantitative asset selection with sentiment analysis.
Algorithm utilizing Square-root law and LOB-L2.
Guilbaum-Pham and Gueant-Lehalle-al. model.
Multi-scale, price-only trend-following system built around dynamical-frequency rates and trend lifecycle control.
ML model for classification of regime-switches. To achieve better Discretionary-tool calibration.
Binary Decision Tree model for multi-segmentation classification of satellite images.
// contact
Available for SWE/Automation Dev