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Cindy Orozco Bohorquez

Ph.D. Candidate in Computational and Mathematical Engineering
Stanford University
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I am a PhD candidate at the Institute for Computational and Mathematical Engineering (ICME) at Stanford. I hold a bachelor's in civil engineering and mathematics from Universidad de los Andes, Colombia, and a master's in applied mathematics from King Abdullah University of Science and Technology, Saudi Arabia. My work combines modern tools of data analysis and optimization with traditional numerical analysis results. In addition to study the theoretical behavior of optimization algorithms using "real" data, I am interested in other components that affect the day-to-day data science, such parallel computing and education of applied mathematics. This workshop is an appetizer of an introductory summer workshop in Parallel Computing that I developed and taught during the last years at ICME. The high-level approach of the workshop is inspired on my own rocky journey learning parallel computing.

Workshop: Parallel Computing 101: All you need to know about the hardware that powers data science
When solving a data science problem, we always rely on a computer to find the solution. And one of our top questions is "How much time is it going to take?". In this workshop, we will talk about the main factors that affect the answer to this question, such as: hardware anatomy, parallelization techniques and the computation-communication dilemma. No prerequisites or coding experience are required to attend the workshop.
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  • Home
  • About
    • Blog
    • WiDStory
    • News
    • Research
    • Sponsors
    • Collaborators
    • Contact
    • Donate
  • Conferences
    • WiDS Stanford 2023 Agenda
    • WiDS Stanford 2023 Speakers
    • WiDS Regional Events 2023
    • Ambassadors 2023 >
      • Ambassador Advisory Council
    • WiDS Ambassador Program
    • Past Conferences >
      • WiDS 2022
      • WiDS 2021
      • WiDS 2020
      • WiDS 2019
      • WiDS 2018
      • WiDS 2017
      • WiDS 2015
    • Conference Committee
  • Datathon
    • Datathon Details
    • Datathon Resources >
      • Datathon Press Release
    • WiDS Datathon Workshops 2023
    • Datathon News
    • Datathon Collaborators
    • Datathon Committee
  • Podcast
    • Podcast Committee
  • Education
    • Workshops >
      • Workshop Instructors
      • Workhop Committee
    • Next Gen >
      • Next Gen Resources
      • Next Gen Committee