Hi, I'm Anton Andreenko — a an Engineer with over 17 years of experience in industrial automation.
I hold a Master’s degree in Computer Science, where I was first introduced to artificial intelligence and neural networks.
I see plenty of opportunities for AI implementation in industrial process control — including areas like:
✅ Quality control
🔐 OT security
🚨 Alarm management
🛠️ Troubleshooting
...and many others.
The rise of foundation AI models has given a huge boost to this direction, making experimentation easier and more accessible than ever before.
My current work explores:
🌐 Industrial AI for predictive maintenance, anomaly detection, and process optimization
🤖 Integrating AI into DCS, PLC, and SCADA environments
🔧 Developing intelligent solutions to enhance safety, efficiency, and decision-making in manufacturing and process industries
A proof-of-concept application demonstrating the use of a Large Language Model (in this case, Google's Gemini 2.5 Pro) to perform question-answering on Piping and Instrumentation Diagrams (P&IDs).
Github: https://github.com/andreenko-repo/pid_diagrams_llm/
A demo can be found here: https://huggingface.co/spaces/AntonAndreenko/pid_diagram_qa
A sample application that demonstrates how to use the Google Gemini API's native Google Search tool for two distinct purposes: data collection and response grounding. These techniques allow you to minimize hallucinations in many real-world applications.
Github: https://github.com/andreenko-repo/gemini_market_analysis
I converted the alarms dataset into a text format to test alarm management methods using NLP AI models.
The alarm viewer can be found here: https://huggingface.co/spaces/AntonAndreenko/tep_alarms_viewer
Github: https://github.com/andreenko-repo/tep_alarms_text
This is a small experiment in PID performance evaluation and tuning using historical data.
A demo can be found here: https://huggingface.co/spaces/AntonAndreenko/pid_tuning