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PhilippXXY/README.md

Philipp J. Schmidt

I am a doctoral researcher at Porsche AG and a PhD student at the Technical University of Munich (TUM).

My research focuses on applying deep learning to real-world problems, particularly in two areas.

  • Root Cause Analysis — Identifying and diagnosing faults in distributed systems using logs, traces and other observability data, primarily through my research at Porsche.
  • Acoustic Imaging — Exploring deep learning approaches to acoustic source localisation and imaging, with Meta Reality Labs Research.

You can find my publications and patents on Google Scholar, and either access my CV on LinkedIn or on my personal website.

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  1. retrospective-event-correlation-proof-of-concept retrospective-event-correlation-proof-of-concept Public archive

    Proof-of-Concept implementation of the Retrospective Event Correlation Engine for automotive diagnostic systems. Correlates Diagnostic Trouble Codes with HPC logs using statistical analysis and ano…

    Java

  2. upsampler-lam-benchmarking upsampler-lam-benchmarking Public archive

    Benchmarking framework for evaluating super-resolution upsamplers in combination with Latent Acoustic Mapping (LAM).

    Python