Data Scientist
Data Scientist/AI Consultant Master Degree Data Science Bachelor Degree Artificial Intelligence
I'm 30 years old, and very enthousiastic when working on projects. Researching the best possible solutions for any problem, attacking it from different angles, is what I do best. Studying at the Radboud University gave me good time managing and communication skills, as well as different environments to work in.
At my first jobs as a Data Scientist I learned my wyas around Azure and all its services. The translation from theoretical knowledge to practical was not easy, but has vastly improved over the last years.
In my free time I like to game, and spend time with friends. I have played in the Dutch College League (DCL) (now renamed to Dutch Student League), which is a competitive environment for students that play League of Legends, and was broadcast on Fox sports here in the Netherlands.
Over the years I have gained experience in multiple coding languages, as well as personal development in communication and happiness.
Here are my most important accomplishments and experiences that I have collected over the years.
Working with real time vessel data, analyzing fuel consumptions, and setting up pipelines for insightful PowerBI dashboards. Creating a model to predict pipe degredation of a dredger, based on previous sparse measurement data. Analyzing opportunities of tugboats to transition to electric types based on power consumption and possible downtime.
Cleaning and extracting useful information from IT support tickets, to then feed this information with RAG to an LLM based chatbot. The chatbot is then integrated into Microsoft Teams, and automated pipelines are configured for future data to be added to the knowledge base. This all I have learned and implemented by myself.
Recognising the pancreas, and potential pancreas cancer, from CT scans using U-NET (link) Maze-, Mandelbrot-, and landscape generation (link) Using ODE-net (and other classifiers) to predict timings for an earthquake given seismic data (link) This website (link) Creating a presentation that elaborates on Generative Examples used in practise, its uses and it drawbacks (WIP).
Introduction Robotics (Head TA, 5 years) Calculus (Head TA, 2 years) Frequentist Statistics (Head TA, 1 year) Probability Theory (2 year) Algorithms and Datastructures (1 year) Applied Mathematics (1 year) Probabilistic Deep Learning (1 year)
Videos explaining basic probability theory, Markov Chains, Complex plane, and Fourier Transformations
Helping high school students with subjects like Mathematics, Physics, Chemistry, Biology, and IT (7 years)