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Membre depuis le 2 septembre 2019
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Experience: I have over 2 years of experience developing a medical grade software tool for surgery planning (FEops HeartGuide™). To meet medical standards for CE marking, the code needed to be precise, well-structured, thoroughly tested and meticulously documented. This is the level of quality you can expect from me. My main passion is in Artificial Intelligence and Deep Learning research. I have completed several AI related projects such as object classifiers, general adversarial networks, natural language processing and object tracking. You can find these projects on my GitLab page. I am currently traveling through Colombia.
$40 USD/hr
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Software Engineer: Finite Element Analysis patient-specific modeling

Aug 2017 - Aug 2019 (2 years)

At FEops I worked on a variety of tasks. My main task was python software development of pre- and post- processing software for patient specific Finite Element Analysis (FEA) simulation models of artificial heart valves. This software is CE marked and pending FDA approval as a medical device. In addition to development I also helped out with the CE documentation and literature reviews related to the product. In addition, I processed patient CT data and constructed FEA simulation models.

Radiology internship

Nov 2015 - Feb 2016 (3 months)

During this internship at the AMC hostpital in Amsterdam, I worked together with the radiology and radiotherapy departments where I investigated the formation of MRI artifacts around biliary stents. These artifacts are usually adjacent to pancreatic tumors, obstructing treatment planning for irradiation therapy. Understanding such artifacts allows reconstruction of the MRI images to enable more precise radiation therapy planning.


Master of Science: Biomedical engineer

2010 - 2017 (7 years)


Artificial Intelligence Nanodegree (2018)


A 4 month online program from Udacity covering many artificial intelligence techniques such as tree search methods, heuristics, Bayesian inference, hidden Markov models, etc.

Deep Learning Nanodegree (2019)


A 4 month online course from Udacity covering many aspects of deep neural networks. For this course I built and trained RNN's, CNN's, GAN's, as well as build a NN from scratch using only Numpy. This course also included training in the use of AWS for training neural networks.

Coordinating Radiation Expert (2019)

University of Nijmegen

A certificate to prove qualification in radiation expertise (level 3). With this certificate I am qualified to handle radioactive materials and coordinate the use of such materials in laboratories.


Quantitative assessment of biliary stent artifacts on MR images: Potential implications for target..

Biliary stents may cause susceptibility artifacts, gradient‐induced artifacts, and radio frequency (RF) induced artifacts on magnetic resonance images, which can hinder accurate target volume delineation in radiotherapy. In this study, the authors investigated and quantified the magnitude of these artifacts for stents of different materials.


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