👋 Hey, I'm Ash Nicolus

• 🧠 AI/ML Engineer focused on Deep Learning, Agentic Systems, and AI Infrastructure
• 🤖 Building production-grade systems using LangGraph, RAG, FastAPI, and multi-agent architectures
• 🩺 Developed healthcare AI systems for embedded medical inference
• ⚙️ Strong interest in systems programming, backend engineering, Linux, and AI deployment
• 🚀 Passionate about solving real-world problems using scalable AI systems

CNN-powered healthcare intelligence system deployed on embedded environments using Raspberry Pi for non-invasive jaundice prediction.

Multi-agent research architecture using LangGraph + LangChain for autonomous retrieval, reasoning, and answer synthesis across large-scale knowledge sources.

FastAPI-powered Retrieval-Augmented Generation system supporting semantic retrieval, dynamic context orchestration, and scalable document intelligence.

Custom Unix-style shell integrating LLM-based command generation with process execution and safety validation.

Retail-focused AI system for demand forecasting, inventory monitoring, and intelligent pricing optimization.

Built and deployed a Feed Forward Neural Network on resource-constrained embedded hardware for real-time fault detection with sub-100ms inference latency. :contentReference[oaicite:0]{index=0}

Developed a CNN-based neonatal jaundice detection system achieving 92% classification accuracy across 500+ medical samples. :contentReference[oaicite:1]{index=1}

Built an Arduino-based automation system integrating sensors and APIs for real-world deployment. :contentReference[oaicite:2]{index=2}

• Built scalable AI infrastructure on Azure, AWS, and GCP
• Improved processing efficiency by 60%
• Achieved 99.5% deployment uptime
• Developed systems serving 5000+ users
• Built retrieval pipelines indexing 1000+ documents

• Codeforces Pupil (1200+)
• LeetCode Rating: 1624
• Strong focus on Graphs, DP, Greedy, and systems-level problem solving

> build intelligent systems
> optimize everything
> automate workflows
> deploy at scale
> repeat

Linux Enthusiast • Minimal Builder • Performance-Focused Engineer

I enjoy building systems that combine:

• intelligent reasoning
• scalable backend infrastructure
• efficient deployment
• autonomous workflows
• real-world usability

Focused on shipping practical AI systems instead of isolated prototypes.

• Advanced Deep Learning
• CUDA Optimization
• LLM Fine-Tuning
• Multi-Agent AI Architectures
• High-Performance AI Inference
• Open Source Contributions (GSoC 2026)