Kevin Fu
About Kevin Fu
Kevin Fu is a Research Assistant at the San Diego Supercomputer Center, where he investigates indexing and querying algorithms for timeseries data. He holds a Bachelor's degree in Mathematics and Computer Science from UC San Diego and has previous experience as a summer intern at The Whitney Lab for Perception and Action at UC Berkeley.
Work at San Diego Supercomputer Center
Kevin Fu has been employed as a Research Assistant at the San Diego Supercomputer Center since 2021. In this role, he investigates indexing and querying algorithms specifically for timeseries data. He conducts analyses and benchmarks timeseries analysis methods, utilizing Twitter hashtag data to support his research. His work is conducted under the guidance of Dr. Amarnath Gupta, contributing to advancements in data processing and analysis.
Education and Expertise
Kevin Fu is pursuing a Bachelor's degree in Mathematics and Computer Science at UC San Diego, with an expected graduation date in 2025. His academic journey includes studying at West Valley College from 2020 to 2021. He completed his secondary education at Lynbrook High School, graduating in 2021. His educational background provides a strong foundation in mathematical theories and computational techniques.
Background
Kevin Fu has gained practical experience through various internships and programs. He worked as a Summer Intern at The Whitney Lab for Perception and Action at UC Berkeley in 2019 for one month. Additionally, he participated in the CMU Pre-College Program at Carnegie Mellon University in 2020 for one month. These experiences have contributed to his understanding of research methodologies and data analysis.
Research Focus
Kevin Fu's research primarily focuses on indexing and querying algorithms for timeseries data. His current work at the San Diego Supercomputer Center involves analyzing and benchmarking methods for timeseries analysis, particularly using data derived from Twitter hashtags. This research aims to enhance the efficiency and effectiveness of data retrieval and analysis in various applications.