ENGINEERING PROJECTS
Engineering, automation and data applied to real-world problems
Applied engineering work across advanced process control, automation and business intelligence, combining process knowledge, data and digital tools to solve complex operational problems
MPC · Advanced process control · python
Model Predictive Control
A portfolio of applied Model Predictive Control (MPC) projects exploring how predictive control, process modelling, and optimization can improve the performance of dynamic systems.
The projects cover different approaches to MPC, from state-space and transfer-function modelling and conventional predictive control to economic, data-driven, and hybrid strategies. Each project combines process understanding, controller development, simulation, and performance analysis to investigate how advanced control can be applied to increasingly complex engineering problems.
POWERBI· DAX · DATA MODELING
Business Intelligence Dashboards
A collection of interactive business intelligence dashboards developed to transform industrial and operational data into actionable insights. Covering process engineering, manufacturing, energy, and public datasets, each dashboard combines intuitive visualizations, advanced filtering, and executive-level KPIs to support faster, data-driven decision-making.
From production monitoring and process performance to operational analytics, geospatial visualization, and trend analysis, these projects demonstrate practical applications of Power BI for engineering, operations, and business intelligence, allowing users to explore data from high-level overviews down to individual assets, processes, and events.
AUTOMATION · python · DATA PROCESSING
Engineer Workflow Automation
Development of Python-based automation solutions to streamline repetitive engineering and data-processing workflows, reducing manual effort, execution time and the risk of human error.
From operational data preparation to automated Excel processing, these projects demonstrate the practical use of programming to improve real-world engineering workflows and turn time-consuming tasks into scalable processes.