Engineering robust, physics-informed intelligent systems for aircraft structural health monitoring (SHM), real-time diagnostics, and critical avionics cybersecurity infrastructure. Bridging regulatory airworthiness requirements with real-world hangar execution.
End-to-end construction of physics-grounded virtual replicas of aviation systems (gas turbines, landing gear) enabling real-time monitoring and fault prediction via ODE-based dynamics simulation.
Data-driven and physics-informed approaches to predicting equipment degradation, RUL estimation, and classifying multi-class aviation failure modes before failure occurs.
Applying AI and digital twins to reduce downtime, predict wear, and streamline maintenance workflows. Cost-of-downtime modeling and DOC analysis mapped directly to maintenance action pipelines.
Computational investigation of RDE flow physics, stoichiometric and off-stoichiometric CJ velocity analysis, and spatiotemporal CFD field augmentation using deep generative models.
Numerical simulation of compressible reacting flows for advanced propulsion. OpenFOAM case setup, meshing, solver configuration, and validation against analytical correlations.
Designing aircraft systems against EASA CS-23 requirements. CS-23.473 landing load case compliance analysis, fault tolerance mapping, and structural load validation.
Embedding physical laws and ODE constraints into ML models to ensure predictions are plausible. Designing Physics-Informed Digital Twin Validators (PIDT) for fault physics modeling.
Hybrid deep architectures for sequential, multi-channel time-series data. Dual-input LSTMs, CNN-BiLSTM with Attention mechanisms optimized for 47ms real-time inference latency.
Designing Conditional Variational Autoencoders for structured, physics-constrained synthetic data generation. KL divergence regularization and spatiotemporal field reconstruction.
Creating large-scale, valid synthetic datasets for ML training in data-scarce domains via MATLAB physics simulators and generative models. Published 27k-sample & 72-field open datasets.
Applying gradient boosting ensemble methods for tabular aerospace fault classification. Feature importance analysis, serialization, and FastAPI deployment for interpretability.
Exporting, optimizing, and deploying ML models in ONNX format for cross-platform, low-latency offline inference environments (e.g., Aho-Corasick + ONNX semantic detection).
Securing aviation datalinks (ADS-B, ACARS, CPDLC) via cryptographic protocols and blockchain architectures against spoofing and replay attacks. Resolving the TCAS Paradox.
Deploying enterprise-grade permissioned blockchain networks for distributed trust. Certificate Authority management, chaincode development, and multi-org topology design.
Ed25519 digital signature implementation and Shamir Secret Sharing (GF(2⁸), 2-of-3 threshold) for secure key distribution in safety-critical aviation nodes.
Building high-performance, memory-safe cross-platform apps using Rust and Tauri v2. Offline whisper-rs STT integration, SQLite orchestration, and local system bindings.
Cross-platform mobile apps targeting Android with real-time WebRTC features, offline asset management, state management, and Firebase/PocketBase cloud integration.
Production-grade web apps via Next.js App Router and PocketBase. Real-time multi-channel chat, RBAC, chunked audio pipelines, and seamless cloud deployments.
Lightweight Python REST API microservices for wrapping ML inference engines, managing Pydantic schemas, and exposing digital twin models as queryable async endpoints.
Integrating real-time audio/video communication via LiveKit Cloud. Broadcast/interactive meeting architectures, token generation, and native SDK integration.
Automating build, test, and deployment pipelines. Workflow YAML authoring, Android APK automated builds, keystore signing, and Vercel/Fly.io continuous deployments.
Authoring peer-reviewed manuscripts for top aerospace journals (AIAA, IEEE, Elsevier). Full lifecycle from literature review to response-to-reviewer rebuttal strategies.
Preparing, documenting, and publishing open-access datasets with persistent DOIs. Structuring metadata, ensuring versioning, and linking open science to published papers.
Critical evaluation of submitted manuscripts for technical accuracy, methodological rigor, and originality on behalf of journal editors (AIAA JAIS).
Professional scientific typesetting using domain-specific class files (AIAA, IEEE, elsarticle). Mathematical arrays, TikZ graphics, and BibTeX bibliography management.
Penelope Inc. is the advanced aerospace software and digital twin incubator powering next-generation aviation telemetry frameworks. Operating at the intersection of physics-informed machine learning, resilient edge computing, and zero-leakage security, we build the systems that safeguard tomorrow's aerospace infrastructure.
Founder, CEO & Chief Technologist
Real-time edge diagnostics bridging multi-channel sensor buses with local physics solvers.
Permissioned blockchain frameworks resolving the TCAS Paradox and securing aircraft datalinks.
Ultra-low-latency ONNX/Rust pipelines ensuring flight-critical safety without cloud dependency.