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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 — High‐fidelity digital‐twin platform for HV/MV substation telemetry, DER aggregation, and real‐time grid edge simulation
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.
| Layer | Project | Description |
|---|---|---|
| Embedded Control Layer | RTOS + Signal Integrity | Hard real-time kernels, deterministic scheduling, and bounded latency for safety-critical environments |
| Grid Operating Layer | GridOS | Digital command surface for observability, DER coordination, and closed-loop control of smart grids |
| AI Orchestration Layer | NeuralBridge | Middleware that connects human intent, large language models, and physical actuators while preserving deterministic guarantees |
| Autonomous & Sensing Layer | Robot LiDAR Fusion | Real-time perception and sensor fusion pipelines that translate sensor data into verifiable physical actions |
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:
Technologies for digitising high‐voltage infrastructure
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
| Project | Focus | Maturity | Link |
|---|---|---|---|
| physics-informed | Production-grade interactive simulator for cross-domain CIM + ThreMA ontology, physics-informed neural networks, RL security agents, and IEEE 9-Bus cyber-physical validation (Grimaldi 2025 thesis) | Live Demo | View Live |
| NeuralBridge | AI-native middleware for deterministic human-to-model orchestration in safety-critical cyber-physical systems | Active Development | View Repo |
| GridOS | Control-oriented smart-grid operating surface with real-time observability and digital twin capabilities | Under Construction | View Repo |
| DERIM | Distributed energy resource intelligence middleware with native IEC 61850/DNP3 modelling and verifiable coordination | Active Development | View Repo |
| robot-lidar-fusion | Real-time perception and sensor fusion stack for autonomous inspection robots | Active Development | View Repo |
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
| Role | Organisation | Period | Focus |
|---|---|---|---|
| ITk Fachspezialist – Digitisation of High‐Voltage Assets | DB InfraGO AG | Aug 2024 – Present | Leading digitalisation strategy for railway traction HV grids; IT/OT convergence, cybersecurity governance, resilience engineering |
| Industrial Engineering Intern – High‐Voltage Maintenance | DB Fahrzeuginstandhaltung GmbH & DB Netz AG | Jun 2022 – Sep 2024 | Lifecycle management of traction power substations, asset condition monitoring, critical systems maintenance |
IEC 61850 • CIM • OCPP • SunSpec • ROS 2 • HELICS • TLA+ • IEC 62351 • NERC CIP • NIS2 • EU CRA
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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