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Department of Chemical Engineering and Biotechnology

 

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.

Interests
  • 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

     

Research

Laser Analytics group — Clemens Kaminski

Artificial Intelligence Group, Computational Biology — Pietro Lio

 

Biography

MSc.Eng in Mathematical Modelling and Computation from Technical University of Denmark

BSc.Eng in Physics and Nanotechnology from Technical University of Denmark.

PhD Student
 Charles Nicklas  Christensen

Contact Details

Cambridge
Email address: 

Affiliations

Collaborator profiles: