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Luis Felipe Brenes

@luisfelipebrenes

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Data scientist specializing in deep learning and optimization for logistics and healthcare.

Costa Rica

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What I'm looking for

I seek roles applying deep learning and optimization to impactful products—collaborative teams, applied research opportunities, and growth toward production ML and system-level responsibilities.

I am a data scientist with a Master in Computer Science who builds deep learning and optimization solutions for real-world problems, particularly in logistics and health diagnostics. My work blends machine learning, metaheuristics and careful dataset design to deliver production-ready models.

During my master's I designed deep learning algorithms for detecting major depressive disorder from voice recordings and created the first Spanish-speaking voice depression dataset, and I now implement optimization algorithms for the logistics sector at AB-inBev | Experis. I have published research and applied Python, TensorFlow/Keras, Pandas and evolutionary computation in both academic and applied settings.

I bring strong interdisciplinary experience from digital music production to computer science, a record of scholarships and awards for academic excellence, and a collaborative, impact-driven approach to projects and teams.

Experience

Work history, roles, and key accomplishments

Current

Data Scientist (Logistics)

Current

AB-InBev | Experis

Sep 2024 - Present (1 year 1 month)

Design and implemented optimization algorithms using machine learning and metaheuristics to deliver data-driven logistics solutions; deployed pipelines and models for production since September 2024.

Python Pyspark SQL Databricks Machine Learning Optimization Meta Heuristics Deep Learning

Graduate Student Researcher

Tec de Monterrey

Aug 2022 - Jun 2024 (1 year 10 months)

Designed deep learning algorithms and created a Spanish voice dataset to detect major depressive disorder, leading to a published research protocol and experimental validation.

Deep Learning Python Data Labeling CNN RNN Signal Processing

Education

Degrees, certifications, and relevant coursework

Tecnológico de Monterrey

Master in Computer Science, Computer Science

2022 - 2024

Grade: 97/100

Activities and societies: Graduate student researcher; research on deep learning for depression detection; received Bright Minds and other scholarships.

Master in Computer Science focused on deep learning and optimization, involving research on detection of major depressive disorder using voice recordings.

Tecnológico de Monterrey

Bachelor in Digital Music Production, Digital Music Production

2016 - 2021

Grade: 92/100

Activities and societies: Received OAS - AMEXCID and CONACYT scholarships; co-curricular roles in music events and volunteering (guitar lessons, fundraising).

Bachelor in Digital Music Production with coursework spanning audio production, interactive audio tools, and software such as Pro Tools and Logic Pro X.