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Hongkai (Donny) Lou

Graduate StudentEmail Hongkai (Donny) Lou

Hongkai (Donny) Lou graduated from the University of California, Los Angeles (GO BRUINS!), in 2024 with a double major in Applied Mathematics and Statistics. Throughout his academic journey, Hongkai has shown a strong dedication to integrating mathematics, statistics, and data science, consistently demonstrating exceptional analytical and problem-solving skills. During his time at UCLA, he was recognized on the Dean’s Honor List for multiple years and participated in the Honor Program, underscoring his commitment to academic excellence. Hongkai's research experience is diverse and impactful, spanning multiple high-profile projects and internships. At the Stavropoulos Center for Complex Quantum Matter, he conducted advanced signal processing for Electron Paramagnetic Studies of Spinel Oxides under the mentorship of Dr. David Beke and Professor Laszlo Forro, utilizing techniques such as Fourier transform smoothing and Savitzky-Golay filtering. In his role as a Research Assistant at UCLA, working with Professor Oscar Hernan Madrid Padilla, he refined non-parametric regression techniques by integrating local median binning estimators with trend filtering, conducting extensive Monte Carlo simulations to test and optimize these methods. Additionally, during his internship at Shanghai Zhongshan Hospital, Hongkai applied machine learning techniques to analyze pancreatic cancer data, developing a logistic regression model for cancer stage classification and creating a health information dashboard to visualize patient data. As an aspiring data scientist, Hongkai is passionate about leveraging data-driven insights to solve complex challenges and drive innovation across various fields. He is particularly interested in the intersection of computational and statistical disciplines, aiming to integrate these approaches to create meaningful and transformative outcomes. Eager to further his expertise, Hongkai looks forward to exploring advanced machine learning, big data, and interdisciplinary applications across industries.