Seyit Höcük

Seyit is a Data Scientist at CentERdata since March 2018. He is experienced in analyzing data, finding AI-solutions, and in applying machine learning techniques.

Seyit graduated in Physics and Astronomy at the University of Groningen. He has been awarded a PhD in Astrophysics with specific knowledge in hydrodynamic simulations and in the theories of star-forming regions. This includes expertise in radiation physics, thermodynamics, and in astrochemistry. After a postdoctoral research position as a specialist in the interstellar medium at the Kapteyn Astronomical Institute, he continued to develop to become a senior scientist in molecular and solid state astrochemistry at the Max Planck Institute (MPE) in Garching / Munich.

In general, Seyit is skilled in scientific programming, statistical analysis, supercomputing, handling Big Data, and in translating theoretical issues to practical solutions (applied Data Science). Seyit has scientific publications in theoretical and numerical research in peer-reviewed international journals.

At CentERdata, Seyit is part of the Data Science team and collaborates with other researchers in the field of applied machine learning, deep learning, NLP, and in creating new insights and working with complex Big Data systems. He is particularly involved in projects related to fraud detection, crime prevention, predicting rare diseases, image recognition, OCR, process mining, recommender systems, pattern recognition from sensor signal (accelerometers), data visualization, search engines, webscraping, and various topics using text analytics and NLP.

Next to technical skills, Seyit also coordinates Data Science Labs, organizes events, and spends time on project acquisition. He likes to engage in networking, trying to establish networks with thought leaders in Data Science and AI. Seyit often leads projects and collaborates with people from various backgrounds and expertises.


 Data science
 Data Analysis
 Machine learning
 Deep Learning
 Explainable AI