MSc COMPUTATIONAL COGNITIVE SCIENCE SUMMA CUM LAUDE (9.5/10)

September 2020 – August 2022

Participation in the programme allowed me to gain insights into a variety of research directions with courses in machine learning, natural language processing, advanced statistical modelling, design of multi-agent systems, cognitive robotics, and cognitive modelling. Most importantly, I was able to refine my research interests and prepare myself for a research career in computational neuroscience.

PRE-MASTER COMPUTATIONAL COGNITIVE SCIENCE

September 2019 – August 2020

To qualify for the Computational Cognitive Science Master Programme, I completed several course units that allowed me to refine my programming skills and reinforced my passion for computational neuroscience.

BSc IN PSYCHOLOGY (HONOURS) CUM LAUDE (8.8/10)

September 2017 – August 2020

During my undergraduate education, I developed a passion for statistical analysis of complex data, developed my academic writing skills, and learned to communicate scientific findings to different stakeholders.

Beside my studies, I participated in the Honours College Programme (45 ECTS), which allowed me to explore my strengths and roles in the context of multidisciplinary teamwork while developing intercultural competencies. Additionally, the programme allowed me to work in close collaboration with researchers and develop my own research interests.

R

lme4, mcgv, Tidyverse, Shiny

I mostly rely on R for statistical analysis of data, hypothesis testing, and visualization. For pupillometry and eye-tracking data I also make extensive use of R for pre-processing.

PYTHON

Tensorflow, PyTorch, SKlearn, Pandas, Numpy

I use Python whenever I need machine learning methods beyond GLMMs and GAMMs such as random forests or transformers. I usually then also perform pre-processing in Python (for example for corpus studies).

MATLAB

EEGLAB

I don’t like Matlab. But for EEG pre-processing and analysis it’s great.

JAVASCRIPT

node.js (express), REACT, jquery, and d3.js

I like to use Javascript and in particular React & d3.js to make data visualization more interactive. I made a tool that allows users to visualize their social network which researchers can use to better understand relationships within these networks.

C / C++

Eigen, Rcpp

Whenever R is too slow I migrate code parts to C++ to speed things up. In particular I like to use Eigen for numerical optimization problems.

SWIFT

UIKit, Core ML

I haven’t worked with Swift in a while now, but I really like the language.