About
Data Scientist computer vision.
Hi I am Sander, I currently am
years old, living in the Netherlands (Noord-Brabant).
At the moment, I am a data scientist the Nederlandse Spoorwegen (NS) focussed on computer vision projects.
I followed the Data Science in Engineering Masters Program at Eindhoven University of Technology where I
specialized in machine learning.
In my free time you'll often find me struggling to fix my home automations, in the gym, binge-watching the
next new highest rated shows or playing
videogames.
You can contact me via email:
- Email (NS): [email protected]
- Email (Private): [email protected]
Want to know more? Scroll down to find more information.
Resume
Professional Experience
Data Scientist
2022 - Present
NS, Utrecht
- Data Scientist of the Advanced analytics VISION team where we focus using computer vision projects
- Together with multiple stakeholders we are working on a automatic image inspection project. The objective is to reduce manual visual inspections, by leveraging computer vision models to detect possible defects in the pantographs and bogies of rolling stock.
Cloud Developer
2021 - 2022
NS, Utrecht
- Cloud Developer of the Topaas team which is responsible of managing and offering collaboration tools for the all IT teams within NS.
- Using Azure Functions in combination with .NET and NServicebus to automate aspects of the self-service platform. This includes but is not limited to assigning software licenses (e.g. Azure DevOps, Jira, Bitbucket), cleaning up unused services (e.g. Azure DevTest labs) and licenses, settings up tools (e.g. Azure DevOps Project).
- Follow the IT Traineeship to work on personal development and get experience within multiple IT departments of the NS.
Education
M.Sc. Data Science in Engineering
2019 - 2021
Average grade: 8.8 (Cum Laude)
Eindhoven University of Technology, Eindhoven
A Computer Science masters program with a specialization in Data Science. During this program I followed courses about deep learning, process mining, security, data visualization and statistics. For my graduation program I researched a variational autoencoder model for program synthesis of industry-grade programming languages.
B.Sc. Computer Science and Engineering
2016 - 2019
Average grade: 8.3
Eindhoven University of Technology, Eindhoven
A bachelor program in which I learned the basic principles and methods to develop software. The courses I followed range from web development to data modelling, app development, probability and artificial intelligence.
Cambridge FCE
2013
Portfolio
Tree2Tree
A Tree-based VAE-RNN autoencoder for C++
2021
A dedicated dedicated website for demonstrating the principles shown in the
paper:
Autoencoders as Tools
for Program Synthesis
Auto waker (Work in Progress)
A automatic android alarm app based on your calendar schedule
2020 - present
A flutter based app that uses the calendar of the device to automatically set alarms based on events
in your schedule.
For scheduling alarms, the app considers any additional wake up time (e.g. for breakfast) and travel
time to the event's location.
The travel time is computed using the Here rest API
and considers any mode of transportation.
Furthermore, the application can notify users the day before an alarm. Users may also customize many
options, such as:
the alarm ringtone, what days to schedule automatic alarms, snooze length, vibration settings, alarm
volume, snooze length,
between what times of the day to schedule automatic alarms and the application's theme.
Source Code Explorer
A web-based source code analysis tool
2020
Software projects can grow large, too massive to interpret efficiently globally. This may lead to software developers losing the overview of their software project. It is worthwhile to analyze the source code on a deeper level, while maintaining a satisfactory overview. This web application provides a visualization of the project is desired to analyze your code in a way such that the quality can be improved. The visualization can help with code discovery, project management, quality assurance, software analysis, code coverage analysis and code execution optimization.