CV

AUTOMATION · DATA · INTELLIGENCE

Mayank
Dinesh Mehta

M.Eng. Automation & IT

Industrial Automation · PLC/SCADA · Machine Learning · Signal Processing · Energy Systems

📍 Gummersbach, Germany

Explore My Projects → View CV ↓
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Mayank Dinesh Mehta

ABOUT ME

Engineering systems from measurement to intelligence.

Automation, data and intelligent engineering systems are at the core of my work.

I'm a Master's student in Automation & IT at Technische Hochschule Köln, Germany, with a Bachelor's degree in Instrumentation & Control Engineering.

My engineering interests lie at the intersection of industrial automation, control systems, data acquisition, machine learning, signal processing and energy systems. I enjoy transforming physical measurements and engineering problems into reliable software-based solutions.

My projects combine industrial technologies such as Siemens automation, PLC/SCADA and Industrial IoT with modern data-driven approaches including Python, machine learning, digital signal processing and time-series analysis.

I am particularly interested in developing engineering systems that connect the physical world with software, analytics and intelligent decision-making — from electrical energy monitoring and forecasting to signal-based detection and renewable-energy modelling.

01

Industrial Automation

PLC, SCADA, instrumentation and industrial communication systems.

02

Data & Machine Learning

Feature engineering, forecasting, classification and data-driven engineering.

03

Signal Processing

DSP, FFT, filtering, time-domain analysis and intelligent signal interpretation.

04

Energy Systems

Energy monitoring, load forecasting and physics-informed renewable-energy modelling.

TECHNICAL SKILLS

Tools I use to build engineering systems.

A combination of industrial automation, software engineering, machine learning, signal processing and energy-system technologies.

⚙️ Industrial Automation

Siemens TIA Portal PLC SCADA Industrial IoT Process Instrumentation Control Systems Node-RED

💻 Programming & Data

Python C/C++ SQL Git Jupyter Pandas NumPy

🤖 Machine Learning

Scikit-learn LightGBM Random Forest Feature Engineering Time-Series Forecasting Classification

📡 Signal Processing

Digital Signal Processing FFT Frequency Analysis Filtering SciPy Signal Detection

⚡ Energy & Visualization

Energy Monitoring Energy Forecasting Grafana Matplotlib ENTSO-E Data Renewable Energy

🏢 Enterprise Tools

SAP Microsoft Excel VLOOKUP Data Analysis Technical Documentation

FEATURED PROJECTS

Engineering projects.

A selection of practical projects combining automation, machine learning, signal processing and energy systems.

Non-Intrusive Load Monitoring using Siemens PAC4200
01

Non-Intrusive Load Monitoring

Siemens SENTRON PAC4200 + Machine Learning

Developed a Non-Intrusive Load Monitoring system capable of identifying individual electrical appliances from aggregate measurements obtained from a Siemens SENTRON PAC4200 power meter.

Key Highlights

  • Real-world electrical data acquisition using Siemens SENTRON PAC4200
  • Feature engineering from active/reactive power, current distortion, power factor and transient behaviour
  • Random Forest classifier for appliance identification
  • Real single-appliance recordings used for verification
  • Complete measurement, feature extraction, classification and visualization pipeline
Python Siemens PAC4200 Machine Learning Random Forest Signal Processing Industrial IoT
View Project on GitHub →
German electricity load forecasting project
02

Electricity Load Forecasting

ENTSO-E + Weather Features + LightGBM

Developed a 24-hour German electricity-load forecasting pipeline using historical ENTSO-E energy data, weather information, calendar variables and machine learning.

Key Highlights

  • Electricity demand data obtained from ENTSO-E
  • Weather and calendar feature integration
  • Time-series feature engineering using lag variables and rolling statistics
  • LightGBM-based electricity load forecasting
  • Backtesting against persistence and benchmark methods
  • 24-hour forecasting pipeline for German electricity demand
Python ENTSO-E LightGBM Pandas Time Series Forecasting
View Project on GitHub →
Morse code audio decoder using digital signal processing
03

Morse Code Audio Decoder

Python + DSP + Adaptive WPM Detection

Developed a real-time Morse code audio decoder using digital signal processing and adaptive timing analysis to detect, decode and interpret Morse signals from audio input.

Key Highlights

  • WAV, MP3 and microphone audio input
  • FFT-based carrier-frequency detection
  • Butterworth bandpass filtering
  • Hilbert-envelope based signal processing
  • Adaptive Words Per Minute (WPM) estimation
  • Real-time Morse signal detection and decoding
  • Character-level N-gram language modelling
Python NumPy SciPy FFT DSP Signal Detection
View Project on GitHub →
Physics-informed 5 MW wind turbine power forecasting
04

Physics-Informed Wind Power Forecasting

5 MW Wind Turbine Model + Random Forest Residual Learning

Developed a physics-informed hybrid wind-power forecasting approach based on a 5 MW wind turbine model and machine learning-based residual correction.

Key Highlights

  • Physics-based modelling of a 5 MW wind turbine
  • Wind-speed to power conversion using turbine characteristics
  • Physics-based baseline used as the foundation for forecasting
  • Random Forest used to learn residual errors
  • Hybrid physics + machine learning forecasting approach
  • Modular Python implementation designed for reproducible experiments
Python Physics-Informed ML Random Forest Wind Energy Forecasting Machine Learning
View Project on GitHub →
Industrial Water Tank Monitoring System
05

Industrial Water Tank Monitoring System

Siemens S7-1200 + TIA Portal + Node-RED + InfluxDB + Grafana

Developed an Industrial IoT-based water tank monitoring and control system integrating Siemens S7-1200 PLC simulation, Node-RED, InfluxDB and Grafana for real-time process monitoring, control and historical data visualization.

Key Highlights

  • Designed PLC-based tank simulation and control logic using Siemens TIA Portal and S7-1200
  • Monitored tank level, pressure and temperature together with pump, valve and cooling-fan states
  • Integrated Node-RED for real-time PLC communication, data acquisition and operator controls
  • Implemented InfluxDB for time-series process data storage and historical logging
  • Developed Grafana dashboards for real-time monitoring and process trend analysis
  • Implemented alarm detection, setpoints and PLC heartbeat monitoring
Siemens S7-1200 TIA Portal Node-RED InfluxDB Grafana Industrial IoT
View Project on GitHub →

EDUCATION

Academic background.

2025 – Present

Master of Engineering — Automation & IT

Technische Hochschule Köln

Gummersbach, Germany

Focus: Industrial Automation · PLC/SCADA · Machine Learning · Signal Processing · Industrial IT

2018 – 2022

Bachelor of Engineering — Instrumentation & Control Engineering

Sarvajanik College of Engineering & Technology

Surat, India

Focus: Control Systems · PLC/SCADA · Process Instrumentation · Robotics · Measurement Systems · Signal Processing

CERTIFICATIONS & ACHIEVEMENTS

Recognition, results & technical credentials.

A selection of academic achievements, engineering awards, professional recognition and technical certifications.

Letter of Recommendation for Non-Intrusive Load Monitoring Project
01

Letter of Recommendation — NILM Laboratory Challenge

Technische Hochschule Köln · 2026

Recognition for strong performance in the Non-Intrusive Load Monitoring laboratory challenge, including machine learning, event detection, Modbus data processing and monitoring dashboard development.

View Recommendation →
McKinsey.org Forward Program badge
02

McKinsey.org Forward — Professional Development Program

McKinsey.org · 2026

Successfully completed the McKinsey.org Forward online learning program, developing practical skills in structured problem-solving, effective communication, adaptability and resilience, and foundational digital tools.

View Certificate →
Live Load-Forecasting Challenge 2026 certificate
03

2nd Place — Live Load-Forecasting Challenge 2026

TH Köln · Team Neura · 2026

Achieved 2nd place in the AIT group with a mean absolute error of 1,408 MW over 41 scored days, outperforming the official ENTSO-E day-ahead forecast.

View Certificate →
SPOTSeven Optimization Challenge 2025/26 certificate
04

3rd Place — SPOTSeven Optimization Challenge

TH Köln · Team Garuda · 2025/26

Secured 3rd position in an optimization challenge involving a 10-link robot arm operating under maze-like hard constraints.

View Certificate →
Team Award for Engineering of New ORP Sensor
05

Team Award — ORP Sensor Engineering

MFG JMD IIR Maintenance · 2024

Team recognition for engineering a new ORP sensor with transmitter installation and configuration for controlling HIIR effluent.

View Certificate →
Expression of Appreciation for DTA Turnaround
06

Expression of Appreciation — DTA Turnaround

MFG JMD DTA · 2023

Recognition for contribution to successful turnaround completion through planning, constraint identification and resolution, coordination and continuous monitoring of planned activities.

View Certificate →
Team Award for PLC to VISS Ethernet Communication
07

Team Award — PLC / VISS Ethernet Communication

MFG JMD IIR Maintenance · 2024

Team recognition for migrating FO network communication from PLC to VISS through Ethernet communication and achieving significant cost optimization.

View Certificate →
Expression of Appreciation for DCS Page Development
08

Expression of Appreciation — DCS Page Development

MFG JMD DTA Utilities Production · 2023

Recognition for designing a common accessible DCS page for the Utility-J3 area to improve operability for panel officers.

View Certificate →
Swagelok Tube Fitting Installation Inspection Essentials certificate
09

Swagelok Tube Fitting Installation Inspection Essentials

Swagelok · Certificate TF-2024-082 · 2024

Technical training in tube fitting installation and inspection essentials, completed on 23 April 2024.

View Certificate →

CONTACT

Let's build something useful.

I'm open to engineering opportunities, collaborative projects and technical discussions across automation, industrial IT, machine learning and energy systems.

GET IN TOUCH

Have a project, opportunity or idea?

Whether you're looking for an automation engineer, discussing an engineering project or exploring a technical collaboration, feel free to reach out.

Send me an email →
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LOCATION Gummersbach, Germany Germany