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1. Root-Cause-Analysis-of-Construction-Accident-Reports-Using-NLP-ML-and-LLMs Root-Cause-Analysis-of-Construction-Accident-Reports-Using-NLP-ML-and-LLMs Public

   This mini project demonstrates a full pipeline for analyzing construction accident reports using Natural Language Processing (NLP), classical machine learning, and large language models.

   Jupyter Notebook

2. VR-Construction-Training-with-Real-Time-Feedback VR-Construction-Training-with-Real-Time-Feedback Public

   This repository contains a mini project demonstrating data-driven XR/VR training for construction worker tasks. The project simulates joint angles, task time, and discomfort, then visualizes them i…

   Jupyter Notebook

3. Wearable-Fatigue-Forecasting-for-Construction-Workers Wearable-Fatigue-Forecasting-for-Construction-Workers Public

   Predict short-term worker fatigue (next 5, 15, 30, 60 minutes) using physiological data from wearable sensors. This project aims to enable proactive safety management and early intervention to redu…

   Jupyter Notebook

4. king-county-house-prices king-county-house-prices Public

   “A data-driven analysis and prediction of King County house prices using Python and linear regression, highlighting key factors influencing housing value and demonstrating end-to-end machine learni…

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5. webscraping-programming-languages webscraping-programming-languages Public

   Capstone project demonstrating web scraping, data cleaning, and visualization of programming languages, their average salaries, and learning difficulty using Python, BeautifulSoup, Pandas, and Matp…

   Jupyter Notebook

6. Preprocessing-Pipeline-for-Blind-Sweep-Ultrasound-Data-for-Abdominal-Circumference-Prediction Preprocessing-Pipeline-for-Blind-Sweep-Ultrasound-Data-for-Abdominal-Circumference-Prediction Public

   Preprocessing pipeline for blind‑sweep ultrasound data that converts raw volumes into enhanced, normalized tensors for fetal abdominal circumference prediction.

   Jupyter Notebook