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Mackenzie Simper

PhD Student
Stanford University

Picture

​Mackenzie is finishing up her PhD at Stanford in mathematics, advised by Persi Diaconis. Her research area is applied probability, and she excited to explore more data science in the future. Outside of research and teaching Mackenzie loves being outside through hiking, biking, and running. Her favorite Markov chain is the overhand shuffle of a deck of cards.

Workshop: Intro to Markov Chains and Bayesian Inference
May 25, 2022; 8:45-9:30am, PST
Markov chains are a special type of random process which can be used to model many natural processes. This workshop will be a gentle introduction to Markov chains, giving basic properties and many examples. The second part of the workshop will focus on one specific application of Markov chains to data science: Sampling from posterior distributions in Bayesian inference. Introductory background in probability, statistics, and linear algebra is assumed. 
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  • Home
  • About
    • Blog
    • WiDStory
    • News
    • Sponsors
    • Collaborators
    • Contact
    • Donate
  • Conference
    • Regional Conferences 2022
    • WiDS 2022 Videos
    • Schedule 2022 >
      • In-person Schedule 2022
      • Online Schedule 2022
    • Speakers 2022
    • Ambassadors 2022
    • WiDS Ambassador Program
    • Past Conferences >
      • WiDS 2021
      • WiDS 2020
      • WiDS 2019
      • WiDS 2018
      • WiDS 2017
      • WiDS 2015
    • Conference Committee
  • Datathon
    • Excellence in Research Award 2022
    • Datathon Resources
    • WiDS Datathon Workshops 2022
    • Datathon News
    • Datathon Collaborators
    • Datathon Committee
  • Podcast
    • Podcast Committee
  • Education
    • Workshops >
      • Workshop Instructors
      • Workhop Committee
    • Secondary Schools >
      • Secondary School Resources
      • Education Outreach Committee
      • Education Outreach Student Advisors