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Daniel Bogdoll

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Hello, let me introduce myself :) I 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 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 associate 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 https://aifb.kit.edu/web/Thema4946] (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 https://aifb.kit.edu/web/Thema4948] (PDF)
  4. Deep Learning World Models with Latent States for Autonomous Driving (PDF)
  5. [Anomaly Detection with World Models for Autonomous Driving https://aifb.kit.edu/web/Thema4949] (PDF)
  6. [Specialized Evaluation Metrics for Perception Tasks in Autonomous Driving https://aifb.kit.edu/web/Thema4947] (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 :)

Publications

Open Source

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Forschungsgebiete
Deep Learning, Anomaly Detection