Hugo Math
Externer Doktorand
Chair for Machine Learning & Computer Vision
| Phone: | +49 (821) 598 4386 |
| Email: | Hugo.Math@bmwgroupbmwgroup.com () |
| Room: | 1025 (N) |
| Address: | Universit?tsstra?e 6a, 86159 Augsburg |
CV
Lebenslauf:
- 2023 - Now: PhD candidate in Deep learning at 新万博体育下载_万博体育app【投注官网】 of Augsburg and BMW Promotion program
- 2022 - 2023: Master of Business Administration at IAE Dijon
- 2018 - 2023: Master of Science in Engineering at Polytech Dijon (新万博体育下载_万博体育app【投注官网】 of Burgundy)
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Areas of interest:
- Deep Learning applied to machine generated data
- Self-supervised learning
- Sequence classification
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About me:
I am currently a PhD candidate at the 新万博体育下载_万博体育app【投注官网】 of Augsburg and part of the BMW promotion program. My main research area focuses on how to leverage machine generated data from cars with deep learning methods to automize defects detection. This involves NLP based models, sequence classification and unsupervised learning in a big data environment.
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Publications
2025
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2025 |
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Hugo Math, Rainer Lienhart and Robin Sch?n. 2025. Harnessing event sensory data for error pattern prediction in vehicles: a language model approach. DOI: 10.1609/aaai.v39i18.34138 |
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Hugo Math, Robin Sch?n and Rainer Lienhart. 2025. One-shot multi-label causal discovery in high-dimensional event sequences. |
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Hugo Math and Rainer Lienhart. 2025. Towards practical multi-label causal discovery in high-dimensional event sequences via one-shot graph aggregation. DOI: 10.48550/arXiv.2509.19112 |