Charles Nicklas Christensen is a final year PhD student at University of Cambridge. His research is in applying computer vision methods to optical microscopy using deep learning, for instance ML-SIM and ERnet . ML-SIM is a method to train neural networks to reconstruct structured illumination microscopy images based on physically modelled synthetic training data.
See charles-christensen.com for more information including publications and projects.
My main primary interest in my PhD project has been in performing SIM reconstruction with deep neural nets, such as in one of my proposed methods ML-SIM, see more at ML-SIM.com and github.com/charlesnchr/ML-SIM.
- Computer Vision
- Image Analysis
- Deep Learning
- Super-resolution
- Computational Imaging
Education:
-
PhD in Computational Imaging, Est. 2022
University of Cambridge
-
MRes in Sensor Technologies and Image Processing, 2018
University of Cambridge
-
MScEng in Mathematical Modelling and Computation, 2017
Technical University of Denmark
-
BScEng in Physics and Nanotechnology, 2015
Technical University of Denmark
