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Vanessa Parli | Stanford HAI

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peopleStaff

Vanessa Parli

Director of Research

External Bio

Vanessa Parli is the Director of Research at HAI. She leads the HAI grant programs, research convenings, student groups and “state of AI” reports such as the AI 100 and the AI Index where she is a member of the Steering Committee. Her team also analyzes the effectiveness of these programs to continuously improve HAI’s ability to foster interdisciplinary research collaborations internal and external to Stanford. Prior to Stanford, Vanessa worked in management consulting where she utilized statistics, machine learning and other data science methodologies to advise government agencies, large biotech companies and nonprofit organizations. Vanessa holds an MS in Engineering Management and Computational Mathematics from Johns Hopkins University and a BA in Industrial Engineering from Arizona State University.

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Latest Related to Vanessa Parli

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The AI Race Has Gotten Crowded—and China Is Closing In on the US

Wired
Regulation, Policy, GovernanceEconomy, MarketsFinance, BusinessGenerative AIIndustry, InnovationMachine LearningSciences (Social, Health, Biological, Physical)Apr 07

Vanessa Parli, Stanford HAI Director of Research and AI Index Steering Committee member, notes that the 2025 AI Index reports flourishing and higher-quality academic research in AI.

media mention
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Here are 3 Big Takeaways from Stanford's AI Index Report

Tech Brew
Sciences (Social, Health, Biological, Physical)Machine LearningRegulation, Policy, GovernanceIndustry, InnovationApr 07

Vanessa Parli, HAI Director of Research and AI Index Steering Committee member, speaks about the biggest takeaways from the 2025 AI Index Report.

news

How Disruptive Is DeepSeek? Stanford HAI Faculty Discuss China’s New Model

Vanessa Parli
Machine LearningFeb 13

All Related

The Global AI Vibrancy Tool 2024
Yoav Shoham, Ray Perrault, Katrina Ligett, John Etchemendy, Nestor Maslej, Loredana Fattorini, Vanessa Parli
Deep DiveNov 14, 2024
Research
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This methodological paper presents the latest iteration of the Global AI Vibrancy Tool, an interactive suite of visualizations designed to facilitate cross-country comparisons of AI vibrancy across 36 countries, using 42 indicators organized into 8 pillars. The tool offers customizable features that enable users to conduct in-depth country-level comparisons and longitudinal analyses of AI-related metrics.

The Global AI Vibrancy Tool 2024

Yoav Shoham, Ray Perrault, Katrina Ligett, John Etchemendy, Nestor Maslej, Loredana Fattorini, Vanessa Parli
Deep DiveNov 14, 2024

This methodological paper presents the latest iteration of the Global AI Vibrancy Tool, an interactive suite of visualizations designed to facilitate cross-country comparisons of AI vibrancy across 36 countries, using 42 indicators organized into 8 pillars. The tool offers customizable features that enable users to conduct in-depth country-level comparisons and longitudinal analyses of AI-related metrics.

Democracy
Industry, Innovation
Government, Public Administration
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Research
Inspiring Action: Identifying the Social Sector AI Opportunity Gap
Sarah Di Troia, Kelly Fitzsimmons, Vanessa Parli, Haifa Badi Uz Zaman, Juan Pava
Deep DiveFeb 08, 2024
Policy Publication
Cover for working paper that reveals the untapped potential for leveraging AI for mission-related impact.

This working paper reveals the untapped potential for leveraging AI for mission-related impact.

Inspiring Action: Identifying the Social Sector AI Opportunity Gap

Sarah Di Troia, Kelly Fitzsimmons, Vanessa Parli, Haifa Badi Uz Zaman, Juan Pava
Deep DiveFeb 08, 2024

This working paper reveals the untapped potential for leveraging AI for mission-related impact.

Education, Skills
Cover for working paper that reveals the untapped potential for leveraging AI for mission-related impact.
Policy Publication
Generative AI: Perspectives from Stanford HAI
Peter Norvig, Erik Brynjolfsson, James Landay, Michele Elam, Russ Altman, Daniel E. Ho, Rob Reich, Surya Ganguli, Christopher Manning, Curtis Langlotz, Percy Liang, Fei-Fei Li, Vanessa Parli
Deep DiveMar 01, 2023
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A diversity of perspectives from Stanford leaders in medicine, science, engineering, humanities, and the social sciences on how generative AI might affect their fields and our world

Generative AI: Perspectives from Stanford HAI

Peter Norvig, Erik Brynjolfsson, James Landay, Michele Elam, Russ Altman, Daniel E. Ho, Rob Reich, Surya Ganguli, Christopher Manning, Curtis Langlotz, Percy Liang, Fei-Fei Li, Vanessa Parli
Deep DiveMar 01, 2023

A diversity of perspectives from Stanford leaders in medicine, science, engineering, humanities, and the social sciences on how generative AI might affect their fields and our world

Generative AI
Research