As a graduate student at Indiana University, I am pursuing a Master of Science degree in Informatics, with a focus on complex networks and systems. I am part of an NSF National Research Traineeship in complex systems, where I use tools from dynamical systems, information theory, and machine learning to study ecology and evolution. Some of my main projects include testing information theoretic tools' ability to identify network structures behind synthetic time series data, developing a machine learning pipeline for the prediction of complex traits in metagenome data, and characterizing ecological patterns that emerge from evolutionary processes. I have also gained experience in using high-performance and high-level programming languages, such as R and Python, and communicating my work to diverse audiences, such as physics professors and biology undergraduates. I am passionate about applying my quantitative and analytical skills to solve real-world problems and enable companies to reach their full potential. I am looking for opportunities to leverage my expertise in complex systems and data science in industry settings, where I can contribute to innovation, collaboration, and growth.