About Me
I transform complex data challenges into actionable insights and innovative solutions. As a Data Science graduate student at Kent State University (GPA: 3.88/4.0), I combine strong technical expertise with a passion for developing AI applications that make a meaningful impact. My research breakthrough in blood cell classification—achieving 98.51% accuracy through a novel hybrid deep learning architecture—has been published in the prestigious Springer Nature eBook series and will be presented at the Future of Information and Communication Conference (FICC) 2025 in Berlin, Germany. This work demonstrates how advanced AI can revolutionize medical diagnostics by automating previously manual processes. Beyond academia, my experience as a Data Modeler at Skywest Immigration Consultant taught me to translate raw data into strategic business value—improving reporting efficiency by 30% and reducing data processing time by 25%. I specialize in: Developing sophisticated deep learning models (CNN, ResNet, Inception, Xception) Advanced statistical analysis and predictive modeling End-to-end machine learning pipeline development Translating complex findings into compelling data narratives Currently exploring opportunities where I can apply my expertise in machine learning, healthcare AI, and data analytics to solve real-world challenges.