Tamino Waldeyer
Software Engineer with focus on Machine Learning and Test Automation
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
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Development and maintenance of automated test suites for a laboratory information system (LIS) using Python and C#.
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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.
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Integration of BDD (Gherkin/SpecFlow) with Ranorex API to simplify test writing and increase team productivity.
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Research into machine learning models that enable scene understanding for autonomous vehicles and novel planning approaches.
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Focus on target conditional generative adverserial networks (GANs) and transformer networks for single and multi vehicle trajectory prediction in urban driving scenarios.
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Proposed novel trajectory prediction methodologies employing conditional GANs and Transformer models, which served as the foundation for a U.S. patent application [1].
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Pre-development for Bosch Roxxter cleaning robot (mmWave radar sensor & chain drive prototype).
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Testing and integration of IR/ToF sensors.
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Implementation of various planning algorithms for the navigation of an Unmanned Aerial Vehicle (UAV) in the Robot Operating System (ROS) and the Gazebo Simulator.
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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.