Siyavuya Madlanga

Worked on projects in the African energy and water sectors, aproactively on the lookout for profitable assignments. One of the most rewarding parts was collaborating within our sales and technical teams; was we worked on technicalls sound and financially viable solutions for our clients.

Microalgae and Macroplant Digitalization in View of Industry 4.0: Contributed to the digitalization of microalgae and macroplant research in line with Industry 4.0 standards. Implementing Remote-Controlled Laboratories: Developed remote-controlled laboratories using MATLAB AppDesigner and Tinkerforge modules. Technical Financial Planning and Laboratory Data Management: Assisted with financial planning for technical projects and managed laboratory data using MySQL

At the Engler-Bunte Institute of KIT, I assisted in recommissioning two biogas reactors. I also conducted regular analyses of the gases, i.e.CH4, H2, CO2, and organic acids. Another crucial aspect of my role was the preparation of sterile and anaerobic liquids, ensuring that we maintained consistent experimental conditions throughout. All of these responsibilities contributed to my active support in the daily operation of the laboratory system, furthering the institute's research activities.

Respponsible engineer for projects at the Matimba, Majuba, and Camden coal power plants. Designs and calculation work of power plant pipes, according to EN13480 and ASME B31.1 standards. Used Caesar II, for sophisticated modeling for Pipe Flexibility Analysis, ensuring robustness and durability in our plant infrastructure. I was also involved in the verification of Piping and Instrumentation Diagrams (P&ID) a compressed air line. I reverse-engineered Coal Mill parts, using Autodesk Inventor

Assisted with: pipeline network constructions using BS EN 13480; execution of pipeline height studies; and, isometric power plant component design.

Python Basics for Data Scientists with Pandas. Database communication with SQLAlchemy Supervised and Unsupervised Machine Learning Models: Supervised and unsupervised learning, harnessing the power of data for predictions. Used models: Logistic Regression, Decision Trees and Random Forests, Support Vector Machines (SVMs), and Neural Network Classification. Spark: Gained hands-on experience with Spark, enhancing my ability to handle big data and optimize processing tasks.

Master's thesis: I conducted a feasibility study titled "Microalgal biomass from the Hartbeespoort Dam for biogas plants, -a feasibility study" to investigate the practical application of water technologies in the partial treatment of open water bodies. Throughout my coursework, I engaged deeply with fundamental subjects such as Fluid Mechanics and Water Resources Engineering, providing me with a robust foundation in these crucial areas of expertise.