Eduard Feicho, Developer in Berlin, Germany
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Eduard Feicho

Verified Expert  in Engineering

Computer Vision Developer

Berlin, Germany
Toptal Member Since
March 28, 2022

Eduard is a computer scientist from Germany with a passion for computer vision. He has extensive experience in the automotive sector as an ex-BMW, Hella, and Volkswagen self-driving car engineer. In London, UK, Eduard has developed and kickstarted Zappar's ZapBox: Mixed Reality for $30 project.


Hella Aglaia Mobile Vision GmbH
Python, Deep Learning, TensorFlow, Docker, C++, PCL, OpenCV, Object Detection...
Zappar LTD
iOS, C++, Python, Deep Learning, Bundle Adjustment, Structure from Motion (SfM)...
Python, OpenCV, Node.js, Angular, Machine Learning, Data Science, AngularJS...




Preferred Environment

OS X, Sublime Text 3, Jupyter, Xcode

The most amazing...

...product I've kickstarted is a $30 mixed reality headset called ZapBox. It's a low-barrier solution for room-scale MR experiences based on Zappar's platform.

Work Experience

Software Engineer

2018 - 2021
Hella Aglaia Mobile Vision GmbH
  • Researched and developed 3D object detection methods with deep learning for LiDAR point clouds.
  • Worked on a multi-camera and LiDAR fusion approach for object detection from prototype to production. Grew the team from one to five members.
  • Supervised a master thesis student on dynamic occupancy grid mapping with particle filter using radar data. Led to a joint publication.
Technologies: Python, Deep Learning, TensorFlow, Docker, C++, PCL, OpenCV, Object Detection, Tracking, LiDAR, Keras, PyTorch, Ubuntu, Windows, Data Science, SQL, Calibration, Epipolar Geometry, Scrum, Visual Studio 2010, Jupyter Notebook, Jupyter, C, Algorithms, Artificial Intelligence (AI), Image Processing

Computer Vision Research Contractor

2015 - 2017
Zappar LTD
  • Developed a novel pattern and detection method. Created fast, robust, and precise localization methods for marker-based augmented reality at a room scale. Helped kickstart the new ZapBox mixed reality headset product and its production.
  • Developed a visual search index for research and development (R&D) purposes.
  • Developed a novel pattern detection method and OCR classifier for mobile phone research and development (R&D).
Technologies: iOS, C++, Python, Deep Learning, Bundle Adjustment, Structure from Motion (SfM), 3D Reconstruction, Simultaneous Localization & Mapping (SLAM), OCR, Data Science, Agile, Scrum, Epipolar Geometry, Jupyter Notebook, Jupyter, C, Augmented Reality (AR), Mobile Vision, Algebra, Matrix Algebra, Linear Algebra, 3D Geometric Analysis, OpenGL, Graphics Processing Unit (GPU), Algorithms, Artificial Intelligence (AI), Image Processing

Back-end Mapping Specialist

2015 - 2015
  • Analyzed 35,000 satellite images for image quality problems, including stitching quality, to guide the second product release risk assessment. After selling a million books and getting Google ventures on board, this was the company's second product.
  • Developed a reactive web labeling tool for satellite images.
  • Invited a team of undergraduate students to label 35,000 satellite images and obtain a week-long internship.
Technologies: Python, OpenCV, Node.js, Angular, Machine Learning, Data Science, AngularJS, Amazon Web Services (AWS), Algorithms, Image Processing

Image Processing Engineer

2014 - 2014
Skin Analytics
  • Pivoted the company strategy by developing a dermoscopic mole segmentation method. This was the foundation of the company's rescue funding of £500,000 after running into startup cash-flow issues.
  • Completed a government research grant worth £100,000 and focused on full-body mole screening.
  • Supported the computer vision team, which developed a dry-skin beauty classifier and mobile application.
Technologies: C++, Python, OpenCV, Image Segmentation, Image Classification, Image Stitching, Jupyter, Jupyter Notebook, C, Algorithms, Artificial Intelligence (AI)

Master Thesis Student

2013 - 2013
  • Developed a massively parallel particle filter and evaluated the classifier performance regarding occupancy grid mapping and static or dynamic classification.
  • Researched a novel particle filter approach and facilitated better understanding and evaluation of such method inside the R&D group, which led to new publications.
  • Combined the particle filter approach with Dempster-Shafer grids, which led to the publication of a new IEEE paper.
Technologies: C++, NVIDIA CUDA, Tracking, Sensor Fusion, LiDAR, Machine Learning, Data Science, Bayesian Statistics, Bayesian Inference & Modeling, Simultaneous Localization & Mapping (SLAM), OpenGL, Visual Studio, Visual Studio 2010, PCL, Robotics, MATLAB, MATLAB Statistics & Machine Learning Toolbox, C, Graphics Processing Unit (GPU), GPU Computing, Algorithms, Artificial Intelligence (AI), Image Processing

ZapBox: Mixed Reality Kit for $30 by Zappar
This is a market-based mixed reality solution for mobile phones. I helped develop the R&D director's vision of room-scale 3D marker reconstruction methods that allowed fast and precise mobile phone localization. A new pattern detection method was developed. A 3D pose graph with ambiguous poses was initialized and disambiguated. Ultimately, I used a bundle adjustment to optimize the reconstruction and detected loop closures.
2009 - 2013

Master's Degree in Computer Science

RWTH Aachen University - Aachen, Germany


Deep Learning Foundation



Google Summer of Code 2012 with OpenCV Internship



TensorFlow, PCL, OpenCV, Keras, PyTorch, OpenGL, Node.js


Sublime Text 3, Xcode, Visual Studio, Visual Studio 2010, MATLAB, Jupyter, MATLAB Statistics & Machine Learning Toolbox


C++, Python, Objective-C, JavaScript, C, Swift, SQL


Data Science, Agile, Scrum


OS X, iOS, Docker, NVIDIA CUDA, Windows, Jupyter Notebook, Ubuntu, Amazon Web Services (AWS)


Angular, AngularJS


Computer Vision, Machine Learning, 3D Reconstruction, Bayesian Inference & Modeling, Robotics, Self-driving Cars, Deep Learning, Object Detection, Tracking, Bundle Adjustment, Structure from Motion (SfM), Simultaneous Localization & Mapping (SLAM), OCR, Image Segmentation, Image Classification, Image Stitching, Sensor Fusion, LiDAR, Calibration, Epipolar Geometry, Bayesian Statistics, Augmented Reality (AR), Algebra, Matrix Algebra, Linear Algebra, Algorithms, Artificial Intelligence (AI), Image Processing, Generative Adversarial Networks (GANs), 3D Geometric Analysis, Graphics Processing Unit (GPU), Mobile Vision, GPU Computing

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