Diego Aguirre

About

$ cat profile.txt | head -5

Developer, Data Scientist, & Entrepreneur

I'm Diego Aguirre, a senior at Cornell University studying Data Science and Physics. I focus on machine learning and software engineering, bringing a user-centric mindset to translate real problems into reliable, scalable systems.

My experience spans Python development, ML modeling, data analysis, and full-stack implementation. I've built projects ranging from sentiment analysis and stock-prediction pipelines to automation tools and smartphone apps.

Outside class and work, I explore emerging technologies, prototype new products, and make music.

$ stats --summary

0 Total GitHub Commits | 0+ Projects | 5+ Languages

$ ls skills/

python machine_learning data_science human_centered_design web_development communication ai_research product_management full_stack_engineering

Projects

Stock Hub

Multi-model stock forecasting with FastAPI, React, and Railway deployment.

fastapi redis railway aws-s3 uvicorn gunicorn background-tasks health-checks automation react

Try the Demo

TheraMistyOverview

Multi-modal speech therapy system for Misty II robot with real-time processing.

python fastapi asgi uvicorn pydantic websocket real-time huggingface-transformers vllm peft lora openai gpt-4o multimodal-llm whisper mediapipe misty-ii robotics

SentimentWatch

Full-stack sentiment analysis app with VADER analyzer and finance-specific rules.

Real-time Data Memory Optimization Data Pipelines Cloud Architecture Heroku Vercel MongoDB Atlas CI/CD CORS Management Rate Limiting Confidence Scoring

Try the Demo

DeegzBot

AWS automation bot for DJ business social media growth and engagement.

Selenium Flask Dashboard AWS EC2 Randomized Delays PyQt5 Headless Chrome TaskScheduler ErrorHandling systemd Python

InferEcon - Econometrics Toolkit

Python toolkit replicating Stata's econometric functionality with 23 functions.

python scipy statsmodels scikit-learn eda panel-data fixed-effects regression-diagnostics data-visualization plugin-architecture configuration-ui html-reporting

Try it live

Emotional Sentiment Analysis

Supervised learning for emotional sentiment using BERT, GRU, and XGBoost.

pytorch transformers bert tensorflow keras gru rnn tqdm accuracy-metrics scikit-learn nlp text-classification sentiment-analysis tf-idf logistic-regression xgboost hyperparameter-tuning