Emma Pierson (computer scientist)

Emma Pierson (Arlington, Virginia) is an American computer scientist who specializes in artificial intelligence.[1] She graduated from Thomas Jefferson High School for Science and Technology.[2] She earned a degree in physics and then a master's in computer science from Stanford University, where she studied cognitive psychology and biocomputation. She received a PhD in 2020 at Stanford under Jure Leskovec. She was awarded a Rhodes Scholarship[2] for her work in using computers to solve biological problems, and specifically to work on cancer treatments.[3]

For the actress, see Emma Pierson.

For Nicholas Kristof's "On the Ground" (in The New York Times), she contributed "How to Get More Women to Join the Debate", a contribution on gender and social media,[4] and a follow-up on her methodology.[5] Pierson works with the GTEx Consortium using algorithms to study tissue-specific gene expression in an attempt to understand complex diseases in which limited availability of samples makes traditional research methods impractical.[6]

References
  1. Pierson, Emma (31 December 2012). "Knowing You Carry a Cancer Gene". The New York Times. Retrieved August 19, 2022.
  2. Kunkle, Frederick (24 November 2013). "Four Virginian students among Rhodes Scholarship recipients - The Washington Post". The Washington Post. Retrieved 13 September 2015.
  3. Chatoor, Nehan (January 9, 2014). "Passion and academic acumen lead Pierson to Rhodes". Stanford, California: The Stanford Daily. Retrieved 17 September 2015.
  4. Pierson, Emma (6 January 2015). "How to Get More Women to Join the Debate". The New York Times. Retrieved 13 September 2015.
  5. Pierson, Emma (9 March 2015). "How to Get More Women to Join the Debate, Part II". The New York Times. Retrieved 13 September 2015.
  6. Pierson, Emma; Koller, Daphne; Battle, Alexis; Mostafavi, Sara; Mostafavi, S.; Ardlie, K. G.; Getz, G.; Wright, F. A.; Kellis, M.; Volpi, S.; Dermitzakis, E. T. (May 13, 2015). "Sharing and Specificity of Co-expression Networks across 35 Human Tissues". PLOS Computational Biology. 11 (5): e1004220. Bibcode:2015PLSCB..11E4220P. doi:10.1371/journal.pcbi.1004220. PMC 4430528. PMID 25970446.
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