MS in Data Science @ Columbia University
Aspiring Machine Learning Engineer focused on applied ML, deep learning, and data-driven product development.
I previously worked in finance and now build ML systems bridging modeling, product sense, and real-world impact. My interests span:
- Machine Learning & Deep Learning
- NLP & LLM fine-tuning
- Recommender Systems & Ranking
- Health & Wellness Data
Building an approximate-nearest-neighbor search model (Amazon-style) for product matching using embeddings, bigram language models, perplexity evaluation, and torch-based training loops.
Fine-tuning small LLMs and RAG for structured tasks
R-based data exploration and visualization of diet, physical activity, and health indicators across NHANES cycles and BRFSS (ggplot2, tidyverse, heatmaps, missingness diagnostics).
A collection of machine learning fundamentals, models, experiments, and exploratory notebooks.
Python • R • SQL
PyTorch • scikit-learn • HuggingFace • NumPy/Pandas • ggplot2 • Tidyverse • NetworkX
📫 Email: eed2167@columbia.edu
🔗 LinkedIn: https://www.linkedin.com/in/emma-dilauro