I am a deep leaning R&D engineer working on HD map generation for autonomous driving at TomTom. Prior to this, I was a Ph.D. candidate at Radboud University, the Netherlands and I worked on the applications of deep learning techniques on neuro-image analysis (Oct. 2013 - June 2017).
My Ph.D. project was in collaboration between the Machine Learning and the
Diagnostic Image Analysis Groups and was under the supervision of Dr. Bram Platel, Prof. Elena Marchiori, Prof. Nico Karssemeijer and Prof. Tom Heskes.
• Machine Learning
Ph.D. in Machine Learning for Medical Image Analysis at Radboud University, 2013-2017.
News:• Dec. 2018: I was pleased to give an invited talk on "AI for Map Making" at the Nijmegen Deep Learning Meetup.
• Aug. 2018: our paper titled "EL-GAN: Embedding Loss Driven Generative Adversarial Networks for Lane Detection", was accepted to ECCV 18 Computer Vision for Road Scene Understanding and Autonomous Driving Workshop.
• On March 8, 2018, I publically defended my Ph.D. thesis entitled: "Machine Learning for Quantification of Small Vessel Disease Imaging Biomarkers". See some images here.
• Feb. 2018: Our paper "Student Beats the Teacher: Deep Neural Networks for Lateral Ventricles Segmentation in Brain MR" is presented at SPIE Medical Imaging.
• As of July 1, 2017, I started as an R&D engineer for autonomous driving at TomTom. Learn more about our team here.
• May 2017: Our paper, "Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation" is accepted for MICCAI 2017.
• From Nov. 2016 to Apr. 2017, I had a six months research visit to the Surgical Planning Laboratory at Harvard Medical School, under the supervision of Prof. William Wells III.