Aylin Özek

Developing interactive React-based visualizations for VR learning analytics using Plotly for post-session analysis of eye-tracking, movement, and student behavior data across multiple visualization components.

Visualizing wearable sensor data to support research and analysis using Python and R Supporting the team with data curation and data analysis Creating questionnaires on SoSciSurvey Reviewing literature on Built Environment and Human Resilience

Developed machine learning models for predicting postprandial glucose responses using multimodal health data combining meal images and CGM data coming from ~45 participants: - Analyzed continuous glucose monitoring (CGM) data collected at 15-minute intervals over 10 days, meal intake and baseline characteristics to investigate factors influencing glucose dynamics. - Analyzed CGM data for candidate meal detection. - Applied unsupervised learning to obtain postprandial glucose response profiles. - Applied fe

Provided support in documentation, testing and development of the open source Java framework for music data analysis: AMUSE (Advanced MUSic Explorer)

Dealer Business Development and Business Intelligence PEP Intern

Created and executed test cases based on test scenarios for mobile and web banking applications.

The aim of this internship was to combine scientific work in the field of numerical mathematics and machine learning. Employed neural networks for solution of ODEs.

ERASMUS

Thesis: Predictive and Unsupervised Machine Learning of Postprandial Glucose Dynamics from Multimodal Data Combining Meal Images and Continuous Glucose Monitoring

ERASMUS

Thesis: Machine Learning Algorithms and Applications