A highly motivated Applied Mathematics M.S. candidate with a strong foundation in climate sciences and computational mathematics. Experienced in utilizing advanced mathematical models and computational tools to understand and analyze complex physical systems, particularly in the context of oceanic and atmospheric processes. Proficient in Python and Java for implementing algorithms, conducting data analysis, and solving real-world problems. Research experience through internships and academic projects at the Scripps Institution of Oceanography, with a focus on analyzing large datasets. Passionate about integrating interdisciplinary approaches to foster innovative solutions for climate variability and resilience. Committed to contributing to the scientific community by promoting diversity, equity, and inclusion in research environments, and eager to further develop expertise in physical oceanography and climate science.