Albert Gong
About Albert Gong
Albert Gong is a Research Assistant at Yale University, where he has worked since 2020. He has a background in computer science and mathematics, with previous research experience at Duke University and Northeastern University.
Work at Yale University
Albert Gong has been employed as a Research Assistant at Yale University since 2021. In this role, he has contributed to various projects focused on machine learning and optimization. His work includes deriving new mathematical interpretations of gradient methods from a continuous-time perspective, under the guidance of Andre Wibisono. His ongoing research efforts continue to enhance the theoretical understanding of convex optimization algorithms.
Previous Experience at Duke University
Prior to his current position, Albert Gong worked at Duke University as a Student Researcher from 2017 to 2019. During this time, he engaged in research activities that laid the foundation for his future work in machine learning and optimization. His experience at Duke University contributed to his development as a researcher in the field.
Internship at Northeastern University
In 2018, Albert Gong served as a Summer Research Intern at Northeastern University for a duration of two months. This internship provided him with practical experience in research, further enhancing his skills and knowledge in the field of computer science and mathematics.
Educational Background
Albert Gong completed his high school education at the North Carolina School of Science and Mathematics, earning a High School Diploma from 2017 to 2019. He then pursued higher education at Yale University, where he studied Computer Science and Mathematics, achieving a Bachelor of Science (BS) degree from 2019 to 2023. His academic background has equipped him with a strong foundation in both theoretical and applied aspects of his field.