CV

Personal Data

Name:
Address:


Email:

Dr.-Ing. Sebastian Bodenstedt
Reicker Str. 33c
01219 Dresden
Germany
info@bodenstedt.eu

Professional Experience

Since 05/2017:

National Center for Tumor Diseases (NCT) Dresden, Group Prof. Speidel

  • Deputy Department Head and postdoctoral researcher in the area of computer assisted surgery:
    • Computer Vision
    • (Surgical) Data Science
    • Machine Learning
      • Deep Learning
      • Uncertainty Quantificatio
    • Skill recognition
    • Surgical Training
    • Object- and event Recognition
    • Semantic Segmentation
    • Transition of technology into the OR

10/2012 – 04/2017:

Institute for Anthropomatics, Chair Prof. Dillmann, Karlsruhe Institute for Technology (KIT)

  • PhD candidate and research assistant in the area of computer assisted surgery:
    • Motion Analysis
    • Machine Learning/Deep Learning
    • Object- and event Recognition
    • (Stereo-)Image processing and reconstruction

10/2011 – 05/2012:

Institute for Anthropomatics, Chair Prof. Dillmann, Karlsruhe Institute for Technology (KIT)

  • Student research assistant in the research area for computer assisted surgery. Worked with:
    • (Stereo-)Image processing and reconstruction
    • Stereo-endoscopy
    • Recording DaVinci-interventions
    • Skill acquisition
    • Sensor integration
    • Multiple C/C++ projects
    • Computer and software administration & maintenance
  • Student research project for optimizing the calibration of a stereo endoscope. Worked with:
    • Multi-variant function optimization
    • Feature detection
    • Epipolar geometry

Skills

Languages:

  • German – Native speaker
  • English – Near native / Fluent
  • Spanish – Basic communication skills / Working knowledge

Programming Languages:

  • C/C++ – approx. 15 years of experience
  • Python – approx. 5 years of experience
  • Passing knowledge of
    • (Visual) Basic
    • Delphi/Object Pascal
    • Java
    • HTML/PHP/ASP
    • Assembler

Libraries:

  • Variety of data science/machine learning libraries, including (but not limited to)
    • OpenCV
    • Pytorch (preferred Deep Learning library)
    • Tensorflow
    • Lasagne/Theano
    • Numpy
    • Scikit
  • Parallelization/Speed Up
    • CUDA
    • TensorRT
    • OpenMP
    • MPI
  • Others
    • ROS
    • ITK/VTK/IGSTK
    • Arduino
    • MPLab

Publications

See my Google Scholar page.