Personal details

Name: Alexey Abramov
Place of Birth: Moscow, Russian Federation
Habitation: Augsburg / Munich, BY, Germany

E-mail: alexey.abramov.salzi{-at-}gmail.com
Web page: salzi.blog
GitHub: @aabramovrepo


Russian: native speaker
German: fluent
English: fluent


Here you can download my resume: Alexey_Abramov_CV.pdf

Professional experience
7/2022 – today: Senior Software Engineer
Argo AI, Munich, Germany


  • AI / ML for Prediction in Autonomy
1/2021 – 6/2022: AI / CV Engineer
Continental ADC, Munich, Germany


  • Reference Data for Advanced Driver Assistance Systems
5/2015 – 12/2020: Development Engineer Environment Model
Continental Teves AG, Frankfurt am Main / Munich, Germany


  • Algorithms and Camera-Based Systems for Autonomous Vehicles
  • Online Road Modeling using Sensor Fusion
  • Lane Perception using High-Resolution Camera
  • Deep Learning for  Lane Perception, Enhanced Environment Modeling
  • Domain Adaptation for Object Detection
5/2013 – 4/2015: Development engineer environment model
Bertrandt Ingenieurbüro GmbH, Munich, Germany


  • Automated Driving (Continental & BMW)
  • Lane Perception using High-Resolution Camera
  • Enhanced Environment Modeling
8/2012 – 4/2013: Postdoctoral Researcher (Post-Doc)
Georg-August-Universität, Göttingen, Germany

Computational Neuroscience Group

  • Development of Algorithms and Camera-Based Systems in Terms of the EU Research Project “GARNICS” – Gardening with a Cognitive System
4/2008 – 7/2012: Ph.D. in Computer Science
Georg-August-Universität, Göttingen, Germany
Supervisors: Prof. Dr. Florentin Wörgötter, Dr. Babette Dellen

Computational Neuroscience Group

  • Compression of visual data into symbol-like descriptors in terms of a cognitive real-time vision system [link]
9/2002 – 2/2008: MSc and BA in Computer Science
National Research Nuclear University MEPhI
Moscow Engineering Physics Institute
Национальный исследовательский ядерный университет “МИФИ”
Московский инженерно-физический институт


  • Computers, Computer Operations, Systems and Networks
  • High-Performance Computer Systems and Technologies
Software / Tools
  • OS: Linux, Windows
  • Development: Python, C++11-17, Nvidia CUDA
  • Version Control: Git, GitHub, DVC
  • Libraries: OpenCV, Point Cloud Library (PCL), Boost, Qt, NumPy, SciPy, Matplotlib, Open3D, seaborn
  • Deep Learning Frameworks: PyTorch, Tensorflow, Caffe
  • Tools: ROS, pytest, Catch2, GoogleTest
  • Machine Learning: scikit-learn, scikit-image, pandas
Research / Software Engineering
  • Computer Vision and Image Processing
  • Artificial Intelligence, Deep Learning, Machine Learning
  • Autonomous Driving, Environment Modeling
  • Camera-Based Road Marking and Lane Detection
  • Image / Video Segmentation and Object Tracking
  • Stereo Vision
  • Python / C++ Software Development
  • Real-Time Computer Vision Systems
  • Image Domain Adaptation
  • Robotics