Senior Software Engineer · Industrial Software · CNC/HMI Systems · Applied AI

I design and build software for complex industrial systems, with a strong focus on CNC machinery, HMI platforms, CAD/CAM workflows, legacy modernization and applied artificial intelligence.

My background is mainly in long-lived C++/C#/Python codebases, production software, machine-oriented logic, computational geometry, diagnostics, automation and human-machine interaction.

Most of my professional work happens inside private enterprise repositories and NDA-bound environments.
This profile contains the public-facing subset of my engineering work, research experiments and independent projects.

My work sits at the intersection of industrial software, machine automation and applied AI.

I am especially interested in systems that must remain understandable, maintainable and reliable over time: software that talks to machines, supports operators, assists engineering workflows and has to survive real production constraints.

Main areas:

• CNC and CAD/CAM software
• HMI design for industrial machinery
• Legacy C++/C# codebase modernization
• Multi-axis kinematics and machine-oriented computational geometry
• Internal tooling, QA automation and diagnostics
• Applied AI, ML and agent-based workflows for industrial use cases
• Research-oriented simulation and experimental software

Ground Control is a discrete-time simulation framework for studying policy decisions in LEO satellite network scenarios.

The project focuses on falsification-driven analysis rather than optimistic simulation: routing policies, DTN behavior, gateway placement, inter-satellite links, SLA trade-offs and topology constraints are tested through reproducible experiments.

Current public material includes:

• a simulation engine
• documented experiment batches
• OneWeb TLE-based validation through SGP4
• research notes and whitepaper material
• policy-level analysis for LEO constellation behavior

Repository:
https://github.com/denisbilli/ground-control-public

Spectral Generalization explores frequency-domain methods for detecting synthetic and AI-generated imagery.

The project investigates whether spectral artifacts can generalize across generation models, datasets and image domains.

Repository:
https://github.com/denisbilli/spectral-generalization-paper

StoryHash is an experimental project about temporal fingerprinting of video content.

The goal is to represent video sequences through stable temporal signatures, useful for similarity analysis, authenticity research and content-level comparison.

Repository:
https://github.com/denisbilli/storyhash-paper

A lightweight ORM / entity manager for the Qt framework.

Repository:
https://github.com/denisbilli/qDBManager

A C++ implementation of the classic arcade game, developed as an exploration of game loops, rendering and basic engine structure.

Repository:
https://github.com/denisbilli/Asteroids

A Python utility to detect and move duplicate images using similarity heuristics.

Repository:
https://github.com/denisbilli/PyImgDuplicateFinder

A Python-based interactive quiz maker.

Repository:
https://github.com/denisbilli/PyQuizMakerAdvanced

Git Gamification Platform is an educational project designed to teach Git workflows through interactive challenges and game-like progression.

The goal is to make version-control concepts easier to understand through practice rather than slides alone: branches, commits, merge conflicts, collaboration flows and common Git mistakes become part of an interactive learning experience.

Repository:
https://github.com/denisbilli/GitGamificationPlatform

SnapBiz is a full-stack platform for managing photography businesses, including communication flows, client portals, reminders, contracts, internal collaboration and operational dashboards.

Built mainly with Django, Celery, REST APIs and automation-oriented backend workflows.
It is progressively evolving toward a SaaS model with analytics and AI-assisted business workflows.

Scribit.ai is a lightweight speech-to-text and meeting-notes platform based on Whisper pipelines, backend batching strategies and microservice-oriented deployment.

Private tools and prototypes covering:

• 5-axis kinematics
• angle computation
• ISO code generation
• post-processing
• machine simulation
• validation utilities
• ML-based diagnostics and pattern analysis

I write about AI, software engineering and the impact of emerging technologies on industrial work.

My focus is not hype, but what happens when AI enters real organizations: legacy systems, production constraints, human workflows, costs, safety, maintainability and decision-making.

I publish mainly on LinkedIn and I recently opened a Substack to collect longer-form essays and research-oriented reflections.

I also mentor students and colleagues on Git workflows, computational geometry, machine learning, game development, CNC/HMI architecture and AI explainability.

I tend to work on software where shortcuts become expensive.

My engineering approach is shaped by industrial constraints: hardware limits, safety, latency, cost, backward compatibility, maintainability and long product lifecycles.

I value:

• correctness before cleverness
• explainability over blind optimization
• measurable improvements over theoretical elegance
• simple tools until complexity is justified
• production behavior over demo behavior
• maintainability as a first-class design constraint

I am skeptical of black-box solutions when they are placed inside operational systems without evaluation, observability or failure boundaries.

Core technologies:

C++ · C# · Python · Qt · Django · CMake · Linux · Git · Docker

Domains and practices:

CAD/CAM · CNC · HMI · Industrial Automation · Machine Simulation · Applied AI · ML Prototyping · Agent Workflows · Software Architecture · Legacy Modernization

I am inventor or co-inventor of multiple software patents related to CNC machinery, HMI workflows, CAD/CAM automation and machine-control logic.

Details are available only where disclosure is permitted.

This profile is a public snapshot of a broader technical path: industrial software engineering, applied AI research, independent experimentation, teaching and product-oriented side projects.

The common thread is building software that has to deal with reality: machines, users, constraints, costs, failures and long-term maintenance.

For technical discussions, research collaboration or professional inquiries, feel free to reach out.