Samirah Amadu's CV

Samirah Amadu

CV

Hello! I’m Samirah Amadu a Computer Vision Engineer from Vienna, Austria.

I focus on solving computer vision problems while utilizing classical techniques, 3D reconstruction, and deep learning. I’m proficient in applying tools such as TensorFlow, Open3D, Matplotlib, and OpenCV to optimize, develop, and investigate 3D computer vision problems. What excites me the most is transferring state-of-the-art developments in computer vision into commercial applications and working with a cross-functional team to achieve a shared goal.

Experience

Computer Vision Engineer, Anyline GmbH (06/2024 – present)

  • Utilized classical computer vision and deep learning techniques to extend a Python-based computer vision pipeline and introduce new features for tire tread depth calculation.
  • Analyzed the feasibility of introducing new features by assessing their effects on the performance of our tire tread application.
  • Developed interactive visualizations using Streamlit with Open3D to analyze 3D tire scans, allowing the investigation of customer problems.
  • Collaborated in a multinational, and cross-functional team to develop a mobile tread depth scanning solution and facilitated the knowledge transfer to non￾computer vision engineers.

Computer Vision Engineer, Prism Labs GmbH (10/2020 – 05/2024)

  • Researched state-of-the-art literature in 3D reconstruction, shape correspondence and scene flow.
  • Implemented neural network architectures from published literature into a commercial ecosystem.
  • Systematically evaluated neural network architectures to assess their performance.

Robot Vision Teaching Assistant, Graz University of Technology (03/2021 – 07/2021)

  • Prepared assignments for the course participants.
  • Assessed the assignment quality of participating students.
  • Introduced a new approach for task distribution using Google Colab.

Computer Vision Intern, Prism Labs GmbH (08/2020 – 09/2020)

  • Researched the topic Scene Flow using state-of-the-art literature.
  • Integrated FlowNet3D into a commercial ecosystem.
  • Utilized TensorFlow and CUDA to implement the neural network model.

Education

Master of Science in Computer Science

Graz University of Technology

  • Computer Science master with a major in Computer Vision and minor in Robotics.
  • Masters thesis topic: Surface Embeddings for Model-based Scene Flow for Human Body 3D Reconstruction.

Bachelor of Science in Computer Science

University of Birmingham

  • Graduated with first-class honors.
  • Bachelor thesis: Photogrammetry (3D Stereo Reconstruction from Images).

Skills

Technical Skills

Python     +++++
C++        +++
Matlab     +++
Tensorflow ++++
OpenCV     ++++
CUDA       +++
Linux      +++++
Windows    +++++
Git        +++++
Docker     +++

Language Skills

German     native
English    C2
Japanese   B1