
- Timeline
- About me- Data Scientist @ Dribia | Research Scientist @ UPC (prev. EPFL) 
- Education - Jesuïtes bellvitge - centre d'estudis joan xxiii-High school diploma with honors technological studies 9.29/10 (with honors)
 - Universitat politècnica de catalunya-Bsc. data science and engineering computer science
 - Ecole polytechnique fédérale de lausanne-Bsc. thesis, visiting researcher 10/10 (with honors)- Working on my Senior Thesis, namely "Neural Architecture Search for Efficient MLP-Based Networks". In this work we are trying to find a method that allows for Automatic Architecture Search that leads not only to correct solutions but efficient ones, outperforming state of the art NAS methods in terms of result efficiency. Equivalent to EPFL's MSc. Thesis.Topics: Deep Learning, NAS, Train-free AS, gMLP, MLP-Mixer. 
 
- Experience - Academia solJun 2021 - Jun 2021Algorithmics and programming teacher- I gave classes to a group of 9 BSc students on programming and algorithms, for an intensive course of 15 hours. 
 - FermatDec 2021 - Feb 2023- Data Analysis pipeline for client acquisition. Advanced analytics for internal usage study. Backend design and API programmer. Data analysis pipeline and ETL - Data Analyst and Backend EngineerJun 2022 - Feb 2023
- Intern Data AnalystDec 2021 - Jan 2022
 
 - École polytechnique fédérale de lausanneJul 2023 - Nov 2023Machine learning researcher- After my Senior Thesis, "Neural Architecture Search for Efficient MPL-Based Networks" I continued researching in the LIONS lab in order to make a plublication to CVPR'24. Finally the research came to an end. 
 - Dribia data researchNov 2023 - now- ML Engineer and Developer in several in-production data science projects for multinational clients. Focus on traffic time series forecasting, convex optimization and causal inference. - Data ScientistJul 2024 - now
- Junior Data ScientistNov 2023 - Jul 2024
 
.webp) - Universitat politècnica de catalunya (upc)Sept 2024 - nowResearch scientist- - Working on Multi-Node AI Workload Optimization and Placement in HIPICS group at UPC, in collaboration with Qualcomm under the Càtedra CHIP project.- Goal: develop optimization techniques to split state-of-the-art large-scale models into limited computation clusters in order to reduce the workload of computational resources during training. 
 
- Licenses & Certifications - C1 advanced cae (score 205/210)Cambridge university press & assessmentJun 2022
 
- Honors & Awards- Awarded to Tomás Gadea AlcaideHigh School Honors - jun. 2019
 
- Languages- esEspañol
- caCatalà
- enEnglish
- frFrançais
 
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