• API

  • Smile Rabbit Bear - AI Translation API

• CLI

  • Aegis-NetValid-Core [The Orchestrator] [Latest]

• Core Function: A from-scratch reference implementation of a payment gateway that sits between merchants and card networks. It handles smart multi-PSP routing (Stripe + Adyen, BIN-aware) and absorbs complex money-movement edge cases like refunds, disputes, retries, and payouts.
• Key Insight: Demonstrates how enterprise payment patterns fit together end-to-end. It features a real double-entry ledger, subscriptions with decline-aware dunning, marketplace splits with connected-account payouts, risk-based reserves, and delegated "agentic payment" credentials.
• Tech Stack: NestJS, TypeScript, Hexagonal Architecture, Domain-Driven Design (DDD), PostgreSQL (Master/Replica CQRS), Redis, HashiCorp Vault.
• Note: This is a portfolio/reference project built to showcase real, verified infrastructure integration (not just mocked-out unit tests). Please review the Known Limitations and LICENSE before assuming any part of it is production-ready.

• Core Function: A local-first desktop application enabling fab quality engineers to perform interactive 3D wafer visualization, offline AI defect classification, and statistical process control (SPC) monitoring directly on-device.
• Key Insight: Designed for air-gapped or high-security fab environments, the architecture completely eliminates external API dependencies. By leveraging onnxruntime-web for 100% local inference and implementing a background human-in-the-loop calibration layer, the system continuously adapts to engineer feedback without modifying the base CNN weights—solving model drift while maintaining deterministic reliability.
• Tech Stack: Electron, React 19, TypeScript, Node.js, SQLite (Encrypted at rest), ONNX Runtime, Three.js
• Note: The underlying CNN classifier was trained offline via PyTorch on the WM-811K dataset (achieving 95.6% accuracy). The application enforces strict IPC boundaries between the renderer and main processes to ensure robust local security.

I develop specialized Digital Tools designed to validate, stress-test, and monitor wireless networking infrastructure. These tools bridge the gap between raw data collection and actionable QA insights.

• Core Function: A unified, multi-engine validation framework that orchestrates the entire suite (Simulator, Stresser, IDS, Monitor) into a single testing workflow.
• Key Insight: Solves the "Fragmentation" problem in network QA by providing time-synced data aggregation and engine lifecycle management. It allows for complex scenarios, such as: “Trigger 100 devices (Simulator) -> Inject 95% load (Stresser) -> Validate if IDS detects the resulting anomalies in real-time.”
• Tech Stack: Python (Multiprocessing), YAML-driven Scenarios, Rich (TUI Dashboard), Cloud-native validation (AWS/GCP IoT SDKs).

• Core Function: A high-fidelity framework that emulates 50+ diverse IoT devices (IP Cameras, Smart Bulbs) with dynamic behaviors and security vulnerabilities.
• Key Insight: Validates Router Stability and Security Observability by simulating real-world chaos like "Thundering Herd" reconnection and anomaly injection.
• Tech Stack: Python, Threading, Rich (Dashboard), Zeroconf (mDNS), Scapy.

• Core Function: Tracks RSSI (Signal Strength), Noise Floor, and Latency over time.
• Key Insight: Helps identify signal degradation patterns and interference in Mesh environments.
• Tech Stack: Python, CoreWLAN (macOS), Pandas.

• Core Function: Simulates high-density household traffic using multi-threaded iperf3 streams.
• Key Insight: Evaluates Bufferbloat, Congestion Control, and hardware stability under 95%+ load.
• Tech Stack: Python, Subprocess, Matplotlib, JSON-parsing.

• Core Function: A modular Intrusion Detection System (IDS) that monitors real-time IoT traffic to identify and mitigate cyber threats (DDoS, Scanning, Lateral Movement).
• Key Insight: Implements Stateful Traffic Profiling and Sliding-Window Frequency Analysis to distinguish between normal device heartbeats and malicious spikes.
• Tech Stack: Python, Scapy (Packet Inspection), PyYAML (Config-driven), psutil (System Guard), Logging.

My toolkit addresses the full spectrum of network validation:

1. Signal Layer: WiFi-Performance-Monitor (RF Health)
2. Throughput Layer: Network-Stresser (Capacity & Stress)
3. Application/IoT Layer: Smart-Home-Simulator (Ecosystem Behavior & Security)

A collection of production-ready NestJS templates following modern software architecture principles.

• Onion architecture with DDD
• Microkernel (Plug-in) architecture
• Clean Architecture
• Hexagonal Architecture
• Modular Monlith Architecture

• Modular Monolith Architecture with integrated CQRS and Event Sourcing patterns
• Modular Monolith Architecture incorporating Event-Driven communication patterns

• Clean Architecture
• Modular Monolith Architecture
• Hexagonal Architecture

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• Onion architecture with DDD
• Modular Monolith Architecture [Latest]

• Design for Failure: Systems must degrade gracefully. Centralized orchestration often creates bottlenecks; I favor resilient, decoupled boundaries.
• Documentation is Architecture: Clear technical documentation and standardized protocols (like PCI DSS or ISO 8583) are non-negotiable for system integrity.

LinkedIn: Da-Wei Lin