Skip to content
View SNPL-glicth's full-sized avatar
🎯
Focusing
🎯
Focusing
  • Bogota D.C , Colombia

Block or report SNPL-glicth

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Content in all repositories owned by your account will be closed.
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
SNPL-glicth/README.md

Nicolás

Full-Stack Quant Developer

Construyendo sistemas resilientes en la intersección de la inferencia activa, matemática estocástica e infraestructura de misión crítica (HFT/IoT).


Proyecto Principal: ZENIN

Motor de Inferencia Activa y Riesgo Estocástico

ZENIN es una arquitectura metacognitiva diseñada para operar bajo incertidumbre extrema. Originalmente concebido para telemetría IoT industrial, hoy opera como un orquestador agnóstico de toma de decisiones.

Arquitectura Implementación
Metacognición Ecuación Maestra v2.2 que evalúa el CVaR y la sincronía temporal antes de ejecutar órdenes.
Zero-Latencia Infraestructura asíncrona desacoplada (asyncio, adaptadores de memoria compartida).
Memoria Vectorial Integración nativa con Weaviate para recuperación de estados y regímenes históricos.
Full-Stack Telemetría en vivo vía WebSockets y panel de control interactivo en React JS.

Stack Técnico

Backend & Core Python (AsyncIO) NumPy Fast-Execution Pipelines Design Patterns

Infraestructura & Datos Weaviate (Vector DB) Event-Driven Architectures REST/WebSockets API

Frontend & UI React JS State Management High-Frequency Rendering

Dominios de Especialidad Active Inference Mixture of Experts (MoE) High-Frequency Trading (HFT)

Pinned Loading

  1. iot_machine_learning iot_machine_learning Public

    ZENIN: Autonomous quantitative trading engine with real-time metacognition, adaptive MoE gating, and mission-critical stochastic risk control.

    Python 4 3