Emma Pierson (computer scientist)

For the actress, see Emma Pierson.

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 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]

  1. ^ Pierson, Emma (31 December 2012). "Knowing You Carry a Cancer Gene". The New York Times. Retrieved August 19, 2022.
  2. ^ a b 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.