Daniel Bogdoll

• M.Sc. Daniel Bogdoll

• FZI-Mitarbeiter
• Email: daniel bogdoll∂kit edu

• Forschungsgruppe: Angewandte Technisch-Kognitive Systeme
• FZI Forschungszentrum Informatik
  Haid-und-Neu-Straße 10-14
  76131 Karlsruhe
• vCard

Hello, let me introduce myself :) I'm Daniel and 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 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 anomaly 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. Benchmarking Anomaly Detection on Camera and Lidar Data with 3D Voxel Representation (PDF)
2. Anomaly Detection with World Models for Autonomous Driving (PDF)

Open Hiwi positions

1. [https://aifb.kit.edu/images/c/c6/Autonomes_Fahren-_Seltene_und_herausfordernde_Szenarien_in_der_Simulation.pdf Autonomes Fahren: Seltene und herausfordernde Szenarien in der Simulation]

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

• Google Scholar
• Semantic Scholar
• GitHub

Open Source

• ad-datasets: Overview of datasets in the field of autonomous driving
• ad-deadlines: Overview of conference deadlines in the field of autonomous driving
• LaTeX template for IEEE and arXiv publications

Let's connect

• Homepage
• LinkedIn
• GitHub

Forschungsgebiete

Deep Learning, Anomaly Detection