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allmen/README.md

👋 Hi, I’m Abdullahi Yahaya

Ph.D. Researcher | Drexel University
Civil, Architectural, and Environmental Engineering

I work at the intersection of sustainable building design, indoor air quality (IAQ), and smart building systems. My research and projects focus on optimizing energy efficiency and occupant comfort using data-driven modeling, simulation, and AI-based control strategies.

💡 Areas of Focus

  • 🏢 Building Energy Modeling & Control
  • 🌿 Indoor Air Quality & Environmental Optimization
  • 🌎 Smart & Net-Zero Building Design
  • 📊 Data Integration & AI for Building Performance

💻 Featured Projects

🏙️ Enhanced Occupancy Detection System

Integrates housing, weather, air quality, and health data for performance analytics.

🌿 Building Automation System

AI-based adaptive control framework for energy-efficient, occupant-centered environments.

📊 Spam Classification Platform

Combined ML and DL (BERT, DistilBERT) to detect spam with high accuracy. Includes a full pipeline from preprocessing to deployment with an interactive web interface.

📫 Connect with Me

LinkedIn
Email

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  1. email-spam-classifier email-spam-classifier Public

    Accurate spam email detection using machine learning and BERT. Includes training scripts, evaluation tools, and a web interface for real-time classification.

    Python

  2. Occupant_Detection Occupant_Detection Public

    This repository contains code and resources related to the implementation of Physics-Based Regularized Bayesian Neural Networks (PBR-BNN) for precise occupant detection in the context of building e…

    Jupyter Notebook

  3. Building-Automation-System Building-Automation-System Public

    Building Automation System (BAS) designed to intelligently manage building equipment, including lighting, temperature, and access control by integrates real-time monitoring, smart scheduling, and a…

    Python

  4. superstore-sales-analysis-tableau superstore-sales-analysis-tableau Public

    This project showcases an interactive sales analysis dashboard built using Tableau, leveraging a Superstore dataset to provide insightful visualizations for data-driven decision-making.

  5. Building-Energy Building-Energy Public

    Energy consumption prediction using different ML techniques

    Jupyter Notebook

  6. energy_consumption_prediction energy_consumption_prediction Public

    Forked from iamirmasoud/energy_consumption_prediction

    Energy consumption prediction using LSTM/GRU networks in PyTorch

    Jupyter Notebook