Gilbert Tanner
Zürich Metropolitan Area Switzerland
Summary
🤩
Rockstar🎓
Top SchoolGilbert Tanner is a robotics engineer with 8 years of hands-on experience bridging research and production, currently pursuing a Master's in Robotics, Systems and Control at ETH Zürich after a strong BSc in Robotics and AI. He has built real-world systems—from LiDAR-based SLAM and collaborative multi-drone mapping in GPS-denied environments to embedded electronics and web interfaces for high-speed tunnel monitoring—combining ROS, sensor fusion, and systems integration. As a front-end contributor to the well-known keptn project he improved UI accessibility and workflow features, and his GitHub projects include machine-learning prototypes such as a Keras-based book recommender. Comfortable moving between low-level electronics and cloud-native tooling, he brings a systems-thinking approach that emphasizes seamless hardware–software interaction and practical deployment.
8 years of coding experience
3 years of employment as a software developer
Bachelor of Science - BSc, Robotics and Artificial Intelligence, 1.05, Bachelor of Science - BSc, Robotics and Artificial Intelligence, 1.05 at University KlagenfurtMatura, Electronics and computer science, 1.0, Matura, Electronics and computer science, 1.0 at HTL MössingerstraßeRobotics, Systems and Control, Robotics, Systems and Control at ETH Zürich
German, English
Stackoverflow
16reputation
54reached
7answers
0questions
Github Skills (32)
python10
scikit10
pandas10
machine-learning10
ui-design10
uid10
keras10
front-end-development10
recommender-system10
scikit-learn10
neural-network10
react10
javascript9
cypress9
typescript9
Programming languages (12)
Github contributions (5)
TannerGilbert/Tutorials
Nov 2018 - May 2022
Code for some of my articles
Role in this project:
Data Scientist
Data ScientistContributions:68 commits, 11 PRs, 59 pushes in 3 years 6 months
Contributions summary:Gilbert's contributions primarily involve the implementation of a book recommendation system. The code demonstrates the use of Keras for building and training a neural network model, including the creation of embedding layers for users and books, as well as the use of layers like Dense, Flatten, and Dot. The user also implements and uses the MinMaxScaler from sklearn. These commits indicate the user's focus on building machine-learning solutions for the repository.
deep-learningpythondata-visualizationmachine-learning
keptn/keptn
Nov 2021 - Nov 2022
Cloud-native application life-cycle orchestration. Keptn automates your SLO-driven multi-stage delivery and operations & remediation of your applications.
Role in this project:Front-end Developer
Front-end DeveloperContributions:39 reviews, 29 commits, 46 PRs in 11 months
Contributions summary:Gilbert primarily contributed to the bridge component of the Keptn project, focusing on user interface enhancements and bug fixes. Their work involved modifying existing UI components, such as those related to the bridge, sequence and environment views, adding features like tooltips, and correcting layout issues. The user also implemented new functionalities, such as linking to secret creation from the secret selection page and adding the pause icon. A significant portion of the changes involved refactoring, UI testing and accessibility adjustments.
multi-stageautomatescycledata-drivenorchestration
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