School: University of North Carolina at Chapel Hill

EDIT ML Program Track: Advanced Research

About Me: I am poised to continue my academic journey at UNC-Chapel Hill, focusing on Business and Computer Science. My experience in environmental technology and data-driven innovation, combined with a strong foundation in computational research and machine learning, uniquely positions me to bridge technical solutions with business applications. Proficient in Python, R, and equipped with advanced skills in high-performance computing, I am ready to make impactful contributions in dynamic, data-centric business environments. My goal is to leverage my analytical abilities and leadership skills to drive technological advancements and strategic business solutions.

Project/Research Interests: I am deeply interested in leveraging artificial intelligence to advance diagnostic and treatment methodologies across gastroenterology, pathology, and radiation oncology. In gastroenterology, my focus is on enhancing predictive models that analyze clinical data to accelerate accurate diagnoses and personalized treatments, particularly for chronic conditions like Crohn’s Disease and IBS. For pathology, I aim to contribute to the development of AI-driven tools that improve the precision and speed of tissue sample analysis, thereby aiding in the timely and accurate identification of diseases. In radiation oncology, my interest lies in optimizing treatment plans through AI algorithms that can predict patient responses to different radiation therapies, potentially increasing the efficacy and reducing the side effects of treatments. My goal is to integrate my skills in data analysis and computational biology to contribute meaningfully to these fields, ultimately improving patient outcomes through technology.