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DArmandoSalinas/README.md

Diego Armando Salinas Lugo

AI & Machine Learning Engineer

Building end-to-end ML systems — from data pipelines and predictive models to deployed APIs and agentic AI.

Portfolio LinkedIn Email

About me

I design and ship production-oriented ML solutions across healthcare, predictive maintenance, forecasting, and NLP. My work spans classical ML, deep learning, explainable AI, and LLM-powered applications deployed on FastAPI, Streamlit, and Google Cloud.

🏆 Featured projects

Project Description Stack
predictive-maintenance-rul XGBoost RUL (RMSE 16.7 cycles) + FastAPI + Streamlit + LangGraph agents on GCP XGBoost FastAPI LangGraph GCP
HeartDisease-Predictor Leak-free UCI heart disease pipeline with LOSO validation, SHAP & LIME scikit-learn SHAP Jupyter
Motor-performance-prediction Real-time motor health monitoring from accelerometer, audio & temperature sensors Python IoT Signal Processing
California-House-Price-Estimator RandomForest pipeline + FastAPI + interactive HTML frontend FastAPI scikit-learn
RossmannSales_FNN Feedforward neural network for Kaggle store sales forecasting TensorFlow Keras
Predicting-ADHD-sex fMRI + psychosocial ML with fairness analysis and explainability SHAP LIME Healthcare AI
RAG Source-grounded PDF research assistant with visible citations LangChain ChromaDB OpenAI
Wellhave ML burnout prediction + LLM wellness coaching (FastAPI + React Native) FastAPI LLM Mobile

🛠 Tech stack

Languages & ML
Python TensorFlow PyTorch scikit-learn XGBoost

Deployment & APIs
FastAPI Streamlit Docker Google Cloud

AI & Data
OpenAI LangChain Pandas Jupyter

📫 Let's connect

Open to ML engineering, healthcare AI, and intelligent systems collaborations.

GitHub Portfolio

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  1. Leveraging-XGBoost-for-Text-Classification-on-Emotion-Recognition Leveraging-XGBoost-for-Text-Classification-on-Emotion-Recognition Public

    XGBoost emotion recognition on text: preprocessing, feature extraction, tuning, and evaluation across six emotion classes.

    Jupyter Notebook 1

  2. PID-and-Fuzzy-logic-for-Intelligent-Systems-and-Robotics PID-and-Fuzzy-logic-for-Intelligent-Systems-and-Robotics Public

    TurtleBot autonomous navigation with fuzzy logic and PID control: edge following, obstacle avoidance, and sensor-driven decisions.

    Python 1

  3. RossmannSales_FNN RossmannSales_FNN Public

    End-to-end deep learning pipeline for Rossmann store sales forecasting: feature engineering, 3-layer FNN with dropout, early stopping, and Kaggle submission export.

    Jupyter Notebook 1

  4. movie-recommendation-system movie-recommendation-system Public

    Hybrid movie recommender combining collaborative and content-based filtering with a Flask web interface.

    Jupyter Notebook 1

  5. ADHD-Outcome-Prediction-Data-Exploration-Preprocessing ADHD-Outcome-Prediction-Data-Exploration-Preprocessing Public

    ADHD outcome modeling Stage 1: behavioral, demographic, and neurological EDA with rigorous preprocessing.

    Jupyter Notebook 2

  6. Predicting-ADHD-sex Predicting-ADHD-sex Public

    ADHD and sex prediction from fMRI and psychosocial data with fairness evaluation and LIME/SHAP explainability.

    Jupyter Notebook 1