CV
Contact Information
| Name | Marta LÓPEZ RAUHUT |
| Professional Title | PhD student |
| marta.lopez-rauhut@enpc.fr | |
| Phone | +33 07 66 77 45 00 |
| Location | 48 Av. Gabriel Péri, Noisy-le-Grand, Île-de-France 93160 |
Experience
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Apr 2024 - Sep 2024 Paris, France
Research Intern
École Nationale des Ponts et Chaussées
Created a dataset and trained baselines for segmenting historical maps, comparing supervised and weakly-supervised methods.
- Outsourced PyQGIS dataset creation script.
- Trained CycleGAN to convert between historical and present-day maps.
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Sep 2019 - Mar 2020 Santander, Spain
Extracurricular Activity Teacher
Marta María Cantera Ruiz
Taught an introductory programming course for elementary school students based on game development in Scratch.
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2018 - 2023 Santander, Spain
Volunteer Salesperson and Administrative Assistant
Fair Trade
Distributed fair trade products from brands such as Ethiquable and managed stock inventories.
Education
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Oct 2024 - present Paris, France
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Sep 2023 - Sep 2024 Paris, France
Master's Degree
Université Gustave Eiffel
Imaging Sciences
- CUDA
- OpenGL
- Signal Processing
- Artificial Intelligence
- Data Science
- Bézout excellence program
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Sep 2019 - Jul 2023 Santander, Spain
Bachelor's Degree
University of Cantabria
Computer Engineering
- Machine Learning and Data Mining
- Natural Language Processing
- Algorithm Design
- Extraordinary Prize for the best academic record
Publications
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Apr 2026 -
Sep 2025 -
Jan 2025 Intelligent energy pairing scheduler (InEPS) for heterogeneous HPC clusters
The Journal of Supercomputing
Languages
Spanish : Native speaker
English : Fluent
Polish : Fluent
French : Intermediate
Chinese : Intermediate
Certificates
- Chinese Proficiency Test HSK 3 - Confucius Institute Headquarters (Jun 2018)
- C2 Proficiency in English - Cambridge English (May 2018)
Projects
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Undergraduate Thesis - Intelligence Energy-Aware Task Scheduler for HPC Systems
Researched Reinforcement Learning techniques to tackle the scheduling problem in heterogeneous High-Performance Computing (HPC) clusters, with the goal of reducing energy consumption.