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|Vorname=Albert
 
|Vorname=Albert
 
|Nachname=Schotschneider
 
|Nachname=Schotschneider
|Akademischer Titel=M.Sc.
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|Akademischer Titel=M. Sc.
 
|Forschungsgruppe=Angewandte Technisch-Kognitive Systeme
 
|Forschungsgruppe=Angewandte Technisch-Kognitive Systeme
 
|Stellung=FZI-Mitarbeiter
 
|Stellung=FZI-Mitarbeiter
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|Bild=Schotschneider_Albert_small.jpg
 
|Bild=Schotschneider_Albert_small.jpg
 
|Info=<br>
 
|Info=<br>
Albert Schotschneider studied computer science and autonomous systems at the Technical University of Darmstadt. Since 2021, he is a research assistant at the FZI Research Center for Information Technology Karlsruhe in the department for Technical Cognitive Systems. His research interests are performance assessment, misbehavior and malfunction detection of driving components with self-optimization and re-training capabilities in autonomous driving using machine learning methods.
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Albert Schotschneider studied computer science and autonomous systems at the Technical University of Darmstadt. Since 2021, he is a research assistant at the FZI Research Center for Information Technology Karlsruhe in the department for Technical Cognitive Systems. His research interests are performance assessment, misbehavior detection, and model-failure detection of driving components in autonomous driving using machine learning methods.
  
 
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=== Open Bachelor/Master Theses ===
 
=== Open Bachelor/Master Theses ===
 
<ul>
 
<ul>
<li>[https://aifb.kit.edu/images/5/5c/2022-10-20-Ausschreibung-Localization.pdf Detecting Mislocalization using Deep Learning Methods for Autonomous Driving]</li>
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<li>AI-Based Approaches for Detecting Model Failures in V2X-Based Systems</li>
<br/>
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<li>[https://aifb.kit.edu/images/e/e8/BA_Evaluating-Metrics-for-Performance-Assessment-in-Autonomous-Driving.pdf Evaluating Metrics for Performance Assessment in Autonomous Driving]</li><br/>
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<li>Deep Learning-Based Methods for Detecting Model Failures Autonomous Driving</li>
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<br />
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<li>Analysis of Machine Learning Methods and Models for Threat Detection in V2X-Based Systems</li><br/>
 
</ul>
 
</ul>
 
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<br/>
If you are interested in one of these topics, don't hesitate to drop me an email with your CV and a few sentences, why you are a good fit!
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<hr>
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<center>
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<b>Interested in another similar topic?</b>
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</center>
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If you are interested in one of these topics (Safety-Validation, Model-Failure Detection) or have a similar topic in mind, don't hesitate to drop me an email with your CV and a few sentences, why you are a good fit! <br />
 +
Also, I offer Hiwi positions!
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<hr>
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|Info EN==== More Information [https://www.fzi.de/wir-ueber-uns/organisation/mitarbeiter/address/albert-schotschneider/ FZI Homepage] ===
 
|Info EN==== More Information [https://www.fzi.de/wir-ueber-uns/organisation/mitarbeiter/address/albert-schotschneider/ FZI Homepage] ===
 
|Publikationen anzeigen=Nein
 
|Publikationen anzeigen=Nein
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|Organisation=AIFB, KIT
 
|Organisation=AIFB, KIT
 
|Abschlussarbeiten anzeigen=Ja
 
|Abschlussarbeiten anzeigen=Ja
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}}
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{{Forschungsgebiet Auswahl
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|Forschungsgebiet=Deep Learning
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{{Forschungsgebiet Auswahl
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|Forschungsgebiet=Maschinelles Lernen
 
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Aktuelle Version vom 14. November 2023, 15:49 Uhr

Schotschneider Albert small.jpg


Albert Schotschneider studied computer science and autonomous systems at the Technical University of Darmstadt. Since 2021, he is a research assistant at the FZI Research Center for Information Technology Karlsruhe in the department for Technical Cognitive Systems. His research interests are performance assessment, misbehavior detection, and model-failure detection of driving components in autonomous driving using machine learning methods.


Open Hiwi Positions

Open Bachelor/Master Theses

  • AI-Based Approaches for Detecting Model Failures in V2X-Based Systems

  • Deep Learning-Based Methods for Detecting Model Failures Autonomous Driving

  • Analysis of Machine Learning Methods and Models for Threat Detection in V2X-Based Systems




Interested in another similar topic?

If you are interested in one of these topics (Safety-Validation, Model-Failure Detection) or have a similar topic in mind, don't hesitate to drop me an email with your CV and a few sentences, why you are a good fit!
Also, I offer Hiwi positions!




Abschlussarbeiten
Abschlussarbeiten







Forschungsgebiete
Maschinelles Lernen, Deep Learning