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Ling Jin 

Research Scientist
Lawrence Berkeley National Laboratory
Picture
Panelist: Algorithms and Data for Equity ​
Ling is a Research Scientist at Lawrence Berkeley National Laboratory and a multidisciplinary expert in air quality modeling, statistics, and resources economics. She strives to advance artificial intelligence and computing applications to the domains of climate/atmospheric science, travel behavior, and electricity market. Her recent projects include identifying pollution control strategies to improve the air quality of California’s disadvantaged communities, modeling travel mode and vehicle ownership dynamics to facilitate emerging technology adoption, and segmenting households with machine learning to improve the cost-effectiveness of demand-response programs in electricity market. Her work has been widely published by AGU, ACS, AAAI, IEEE, and ACM.

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  • Home
  • About
    • Blog
    • WiDStory
    • News
    • Research
    • Sponsors
    • Collaborators
    • Contact
    • Donate
  • Conferences
    • WiDS Regional Events 2023
    • WiDS Stanford 2023 Online
    • WiDS Stanford 2023 Agenda
    • WiDS Stanford 2023 Speakers
    • Ambassadors 2023 >
      • Ambassador Advisory Council
    • WiDS Ambassador Program
    • Past Conferences >
      • WiDS 2023
      • WiDS 2022
      • WiDS 2021
      • WiDS 2020
      • WiDS 2019
      • WiDS 2018
      • WiDS 2017
      • WiDS 2015
  • 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