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Jeff Chiang is an Assistant Adjunct Professor specializing in the intersection of big data, artificial intelligence, and clinical research. His work tackles the computational challenges that arise in the field of medicine, particularly in identifying risk factors and developing predictive models for negative outcomes related to age-related macular degeneration. Chiang's team emphasizes the innovative integration of health information from diverse sources to address the limitations of data availability while minimizing bias. He leads the Computational Medicine Technology Core at UCLA, focusing on building the technical infrastructure necessary for deploying computational models in clinical settings. Chiang holds a B.S., M.A., and PhD in psychology (cognitive science) from UCLA. Prior to joining the faculty, he held research positions in the industry and within the Department of Computational Medicine.
Department of Economics admits primarily for the PhD program.