The Data Science Lab (DS Lab) is an interdisciplinary research hub dedicated to developing intelligent, data-driven solutions to complex societal challenges in health, environment, and sustainability. By integrating machine learning, deep learning, IoT systems, sensor fusion, and predictive analytics, the Lab transforms high-dimensional data into actionable insights for real-world decision-making. A flagship project, in collaboration with Phutung Lab, applies Raman Spectroscopy and AI-based classification to distinguish Gram-positive and Gram-negative bacteria, advancing rapid diagnostic technologies. The Lab also develops real-time sensor fusion and predictive analytics frameworks for early wildfire detection in partnership with the School of Plant and Environmental Sciences at New Mexico State University. Additionally, it works on forecasting waterborne disease outbreaks using IoT-enabled water quality monitoring and epidemiological modeling, guided by collaboration with the School of Public Health at the University of Illinois Chicago. Collectively, these initiatives position the DS Lab as a transformative force driving innovation in healthcare, environmental protection, and public health resilience through global collaboration.