Tamino Waldeyer
Machine LearningEngineer
Prefered Techstack
About me
I am an automation-focused engineer combining SQL database design and Python tool development with research experience in machine learning. My background includes building end-to-end test automation frameworks and implementing BDD practices for cross-functional teams.
Experience
Development and maintenance of automated test suites for a laboratory information system (LIS) using Python and C#.
Developed an automated test data preparation tool using Python/wxPython integrated with an MSSQL backend via SQLAlchemy, enabling efficient test case management and eliminating repetitive manual scripting.
Integration of BDD (Gherkin/SpecFlow) with Ranorex API to simplify test writing and increase team productivity.
Research into machine learning models that enable scene understanding for autonomous vehicles and novel planning approaches.
Focus on target conditional generative adverserial networks (GANs) and transformer networks for single and multi vehicle trajectory prediction in urban driving scenarios.
Proposed novel trajectory prediction methodologies employing conditional GANs and Transformer models, which served as the foundation for a U.S. patent application [1].
Pre-development for Bosch Roxxter cleaning robot (mmWave radar sensor & chain drive prototype).
Testing and integration of IR/ToF sensors.
Implementation of various planning algorithms for the navigation of an Unmanned Aerial Vehicle (UAV) in the Robot Operating System (ROS) and the Gazebo Simulator.
Testing of planning solutions on robot platform (Pioneer 3-DX).
Publications
Projects
Implementation of MGAIL Algorithm
Multi-agent imitation learning implementation in PyTorch for autonomous systems.
sBon - Simple Bon System
Restaurant management system for order tracking, kitchen display, and streamlined operations.