- Modeling and simulation of a reactive batch distillation plant using MATLAB and Python do-mpc, employing an innovative combination of physics-based and machine learning models (neural networks with MATLAB Deep Learning Toolbox).- Parameter estimation for a dynamic plant model using real process data with Simulink Design Optimization.- Development and implementation of an advanced Model Predictive Controller (MPC) and State Estimation (UKF) using Plantegrity® and C++, aiming to improve process performance and reduce production costs.- Batch trajectory optimization using Python do-mpc to reduce batch time and energy consumption.Creation and implementation of a user-friendly visualization system (HMI) for Model Predictive Control and State Estimation, facilitating plant operation and simplifying maintenance.- Conducting tests and examining MPC controllers with disturbances in the plant to evaluate the robustness and reliability of MPC.- Presentation and explanation of the benefits of Model Predictive Control and State Estimation solutions for plant operators and stakeholders.- Conducting a thorough literature review (50+ Reserach Papers) to understand the state of the art in modeling, trajectory optimization and model predictive control of batch industrial processes. - Successful completion of the thesis with an excellent grade of 1,1

- Design of controllers and simulations in MATLAB and Simulink.- Performing PLC programming in Step7.- Responsible supervision of students in the laboratory for process automation during internships.- Development of physics-guided neural networks using TensorFlow and Keras in Python for modeling processes and systems.- Programming a user-friendly GUI dashboard solution using PyQt, Grafana, InfluxDB, and scikit-learn in Python for efficient visualization and classification of electrical time series data from an SLM machine.- Conducting extensive literature research and summarizing research papers to support projects and decision-making.

- Training in programming and configuration of Honeywell Experion® PKS (Process Control System) as well as Siemens TIA Portal using function block diagrams, structured text, and sequential function charts.- Performing visualization and HMI programming for new plant expansion projects.- Learning FAT (Factory Acceptance Testing) and PID tuning to improve process control.- Specification, procurement, installation, calibration, and maintenance of measuring instruments, control valves, and actuators.- Creating E&I (Electrical and Instrumentation) loop diagrams and hardware planning using MS Excel and MS PowerPoint.- Troubleshooting and resolving issues in automated systems.- Acquiring basic knowledge of SAP Plant Maintenance.- Coordinating with operations and process engineering for automation projects and plant maintenance.- Collaborating with suppliers of instruments and automation components.