Designing deterministic, physics-informed intelligence that transforms complex control systems into operational, verifiable, and adaptive realities.
_{High-Voltage Substations • Agentic Middleware • Autonomous Grid Intelligence • RTOS & Verification}

_{GridOS • Local‑first digital‑twin & high‑voltage telemetry operating system}

This GitHub profile is the developer-first surface — precise, technical, and built for engineers who want to inspect the code and understand the architecture.

The Immersive Portfolio is the cinematic surface — where physics-informed systems, interactive visualizers, live intelligence, and glassmorphism storytelling bring the same mission to life.

Same story. Different lenses. Perfectly aligned.

✅ Rewritten & Polished Version

The most advanced systems only become truly trustworthy when intelligence is strictly constrained by the laws of physics.

Total objective = Data fidelity + Physics penalty

This formulation is the foundation for real-time, physics-guaranteed surrogate models in GridOS + NeuralBridge — systems that are not only intelligent, but provably safe and operationally reliable under physical constraints.

This same foundation powers the live physics-informed simulator — the public implementation of the cross-domain CIM–ThreMA ontology integration and reinforcement learning security methodology from my 2025 Master Thesis at RWTH Aachen University.

Four coherent layers. One unified thesis.

graph TD
    subgraph "Domains I Merge Every Day"
        A[High‑Voltage & Energy Systems<br/>Substations • IEC 61850 • DER • Digital Twins]
        B[Real‑Time Software & Middleware<br/>Embedded→Edge→Cloud • Agentic Pipelines]
        C[Applied AI & Decision Intelligence<br/>Forecasting • Anomaly Detection • Autonomous Control]
    end

    A --- B
    B --- C
    A --- C

    style A fill:#0f172a,stroke:#38bdf8,stroke-width:2px,color:#e0f2fe
    style B fill:#0f172a,stroke:#38bdf8,stroke-width:2px,color:#e0f2fe
    style C fill:#0f172a,stroke:#38bdf8,stroke-width:2px,color:#e0f2fe

High-voltage domain depth provides the physics.
Software engineering delivers the robust skeleton.
Applied AI injects the intelligence — all grounded in operational reality.

I master and integrate the following stack across cloud, edge, and bare‑metal environments — the same stack that digitises high‑voltage assets end‑to‑end:

What this stack unlocks every day:

• Real‑time grid telemetry — IEC 61850 MMS/GOOSE, DNP3, MODBUS TCP/RTU, MQTT Sparkplug, OPC‑UA
• Edge‑to‑cloud data fabrics — streaming architectures (Kafka, NATS, RabbitMQ), time‑series databases (TimescaleDB, InfluxDB), agentic middleware
• Digital twins & co‑simulation — physics‑informed models, hardware‑in‑the‑loop (HIL), real‑time 3D visualisation (Three.js, Unity, Unreal)
• AI/ML at the grid edge — forecasting, anomaly detection, autonomous Volt/VAR control, reinforcement learning for DER dispatch
• DevOps for critical infrastructure — GitOps, immutable infrastructure, zero‑trust security, automated compliance

All flagship repositories are open source. Star them. Build with them.

I ship resilient, explainable systems that function under the unforgiving constraints of high-voltage environments.

• Architecture that respects safety, reliability, and real-time requirements
• Explicit interfaces and comprehensive testing (unit, integration, hardware-in-the-loop)
• Incremental delivery of complete, testable subsystems
• Documentation that an operator in a control room can actually use

My core tools are Python, Rust, C++, FastAPI, real-time data pipelines, and digital twin engines — and when a project calls for it, I build fluid frontends with React/Next.js or 3D dashboards with Three.js/Unreal.

• 22% reduction in grid curtailment via DERIM + multi-agent reinforcement learning
• Sub-8 ms deterministic latency achieved in NeuralBridge orchestration layers
• 99.999% uptime target with RTOS + physics-informed verification pipelines
• 15–40% higher renewable penetration enabled through physics-constrained intelligence

IEC 61850 • CIM • OCPP • SunSpec • ROS 2 • HELICS • TLA+ • IEC 62351 • NERC CIP • NIS2 • EU CRA

Two surfaces. One mission.

This README is the developer surface.
For the full cinematic experience with interactive physics-informed visualizers and live intelligence, visit:
https://vincenzo-grimaldi-portfolio.vercel.app/

Vincenzo Grimaldi
Humbly building deterministic, physics-guaranteed systems for the infrastructure that powers the future.

📍 Europe-based • Open to high-impact opportunities in CPS, grid intelligence, and autonomous systems
✉️ vincenzo@grimaldi.engineering