**Machine Learning Engineer | Neurotechnology **
I’m a Data Scientist and Software Engineer with over 6 years of experience in Python and a passion for building intelligent systems that make a real-world impact. My work spans signal decoding, real-time ML pipelines, and neurotech-inspired AI tools.
🔭 Currently: Machine Learning Engineer at Quantum Ventura, designing deep learning models for the U.S. Department of Energy
🧠 Passionate about neurotechnology, AI for well-being, and human-centered design
📅 Book a 15-minute chat: Calendly Link
- ⚙️ Build distributed pipelines with Airflow, PySpark, and GCP
- 🧠 Design deep learning systems to decode EEG and biosignals
- 🛠️ Craft full-stack apps in FastAPI, React, Next.js
- 🎯 Work across domains: neurotech, carbon emissions, fintech, and emotional AI
- Forecasted CO₂ emissions in carbon capture facilities using XGBoost, LightGBM, and causal impact analysis
- Conducted in-depth analysis of time-series data and sensor readings to support model reliability
- Built Brazil’s first automated over-collateral calculator for livestock loans
- Improved loan approval accuracy by 30% using React, PostgreSQL, and TypeScript
- Automated external data retrieval with crawlers + AWS pipelines
- Researched EEG signal quality and developed a real-time validation tool
- Built APIs + CLI in Python for sensor diagnostics → improved accuracy + retention
Languages: Python, JavaScript (TypeScript), SQL, Java
ML/AI: PyTorch, TensorFlow, Scikit-learn, Keras, RAG, LLMs, SVD
Backend: FastAPI, Django, Node.js, REST APIs
Frontend: React, Next.js, Tailwind
Data + Infra: Airflow, MLflow, GCP, AWS, Docker, PostgreSQL, MongoDB, Snowflake
Tooling: Git, Pytest, dbt, Tableau, JUnit
🎓 M.S. in Data Science — University of San Francisco (GPA: 4.0)
🎓 Bachelor's in Computer Science & Psychology — McGill University
🥇 Golden Key Honor Society – Top 15% of class
Thanks for stopping by! This profile README is a snapshot of my work, passions, and path in AI + neurotech.