I am an aspiring undergraduate proficient in Python, Pytorch, and quantum computing. I am currently pursuing a BS in Computer Science at the University of Wisconsin-Madison and seeking opportunities to further develop and apply my skills in a research or industry environment, particularly in quantum-related fields.During the summer after my first year, I interned at St. Jude Children's Research Hospital, where I joined a research and production group focused on computational chemistry, specifically applications of density functional theory (DFT). During my first year as an undergrad at IU-Bloomington, I conducted research specializing in quantum computing with AI integration under the mentorship of Dr. LaRacuente. My work was focused on assessing correlations between qubit features to predict error probability, utilizing data from 8 IBM system backends. I conducted extensive time series analysis for the 7-qubit IBM Perth system and employed LASSO regression techniques across 127-qubit systems, achieving a notable 10% increase in performance over the base model.During my second semester, I also conducted a comprehensive analysis on the effects of artificial noise on quantum machine learning model performance, noting a potential performance enhancement through the addition of amplitude dampening error.My experience extends to real-world problem-solving such as in the project titled, "Breaking the Cycle: Reducing Recidivism Rates in Iowa State Prisons", where my team placed 2nd nationally and earned a $15,000 reward for our work in reducing recidivism rates in Iowa State Prisons using a feedforward network.