Developed an augmented reality system using real-time 3d pose estimation to display holograms on a screen from the correct 3d perspective of a person standing next to it. This is a full stack project, with frontends for calibration procedures and displaying holograms, and backends for interfacing with hardware and numerical algorithms.
Developed a 'service broker' system for monitoring and launching all our services, and to allow services to find each other. This system makes it much easier to start up and develop product demos, as well as providing a convenient place to monitor running servces. The backend uses a combination of our own network stack, together with FastAPI, and the frontend is developed in Svelte with Tailwind CSS.
Maintained and upgraded the Jenkins CI/CD pipeline, improving the workflow for all our Python projects.
Performed research in applied mathematics after first studying pure mathematics for 2 years. Focussed on advanced numerical optimization algorithms, particularly for tensors and their applications to machine learning. Developed 3 high-quality numerical software libraries in Python and contributed to 2 open-source projects as part of several research projects resulting in 4 manuscripts.
Taught 3 courses per year as an assistant, receiving consistently positive feedback from students for clear solutions and lectures. Designed Python programming homework using Jupyter and unit tests for 5 courses well-received by both students and teaching staff.
2018/03—2022/12
PhD in Mathematics
|
University of Geneva
2015—2018
Msc. Mathematical Sciences
|
Utrecht University (cum laude)
2012—2015
Bsc. Mathematics
|
Utrecht University (cum laude)
Bsc. Physics and Astronomy
|
Utrecht University (cum laude)
2021/02
Neuroscience and Neuroimaging Specialization
|
John Hopkins University (Coursera certificate )
2020/09
Genomic Datascience Specialization
|
John Hopkins University (Coursera certificate )
2019/08
Advanced Machine Learning Specialization
|
Higher School of Economics (Coursera certificate )
Streaming Tensor Train Approximation
published in
SIAM Journal on Scientific Computing
joined work with
Bart Vandereycken and Daniel Kressner
TTML: tensor trains for general supervised machine learning
joined work with
Bart Vandereycken
On certain Hochschild cohomology groups for the small quantum group
published in
Journal of Algebra
joined work with
Nicolas Hemelsoet
A computer algorithm for the BGG resolution
published in
Journal of Algebra
joined work with
Nicolas Hemelsoet
Parallel 2-transport and 2-group torsors
Rik Voorhaar © 2024