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Daniel Bogdoll

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Hello, let me introduce myself :) I am Daniel and studied Computational Engineering Science at RWTH Aachen University from 2011 to 2019 with a focus on Machine Learning. In my theses, I worked on A*-based trajectory planning and LCSS-based route matching. In 2017, I completed a research stay in the Silicon Valley in the area of sensor data augmentation. Subsequently, in 2018, I founded the shared mobility startup SAYM.

Since November 2020, I am a research scientist at the FZI Research Center for Information Technology in the Technical Cognitive Systems (TKS) department and a PhD student at AIFB. My focus is on corner-case detection for autonomous vehicles. I am also deeply interested in the societal implications of autonomous vehicles in the (near) future.

Open Bachelor/Master Theses

  1. Deep Learning Anomaly Detection with Model Contradictions for Autonomous Driving (PDF)
  2. 3D Voxel Benchmark for Anomaly Detection in Autonomous Driving (PDF)
  3. Benchmarking Anomaly Detection on Camera and Lidar Data with 3D Voxel Representation (PDF)
  4. Deep Learning World Models with Latent States for Autonomous Driving (PDF)
  5. Anomaly Detection with World Models for Autonomous Driving (PDF)
  6. Specialized Evaluation Metrics for Perception Tasks in Autonomous Driving (PDF)


If you are interested in a student position in one of these fields, just send me an e-mail with your CV, your grades, and two sentences, why you are interested in the position. No cover letter necessary :)

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Open Source


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Abschlussarbeiten
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Forschungsgebiete
Deep Learning