Jennifer Wortman Vaughan

schoolMicrosoftbar_chart#328 Global Rank
Total Papers
17
HCI Rank
#328
Research Areas
5
Years Active
8

Personal Information

  • KeywordsAI transparencyresponsible AIalgorithmic fairnessAI interpretabilityhuman-AI interaction
  • OrganizationMicrosoft Research, New York City
  • Education (Institution)University of Pennsylvania (Ph.D. in Computer and Information Science)
  • Emailjenn@microsoft.com

Social Media & Links

Biography

Jennifer Wortman Vaughan is a computer scientist specializing in building responsible AI systems. She is currently the Senior Principal Research Manager at Microsoft Research in New York City. She is a core member of the Microsoft FATE (Fairness, Accountability, Transparency, and Ethics) group and contributes to the Aether transparency working group, focusing on advancing responsible AI through technology and processes. Her research interests include AI transparency, algorithmic fairness, human-centered evaluation of generative AI, and designing AI systems that enhance human capabilities. Before joining Microsoft Research, she was a Computing Innovation Fellow at Harvard University and an Assistant Professor at UCLA. Passionate about community building, she is a co-founder of Women in Machine Learning (WiML) and has served as an organizer for several major academic conferences.

Work Experience

  • 2012–present·Microsoft Research, New York City·Senior Principal Research Manager
    • Member of the FATE group, focusing on the accountability, transparency, and ethics of AI systems.
    • Researches the integration of responsible AI principles with industrial practices and provides recommendations for enhancing tools and processes.
  • 2010–2012·Harvard University·Computing Innovation Fellow
    • Conducted research in the EconCS group and the theory of computation group, exploring the intersection of computational social sciences.
  • 2009–2010·University of California, Los Angeles·Assistant Professor
    • Focused on research in the areas of machine learning and algorithmic economics.

Education

  • 2004–2009·University of Pennsylvania·Ph.D.
    • Field of Study: Computer and Information Science
    • Research focus: Learning models and algorithms for preferences, behaviors, and beliefs in collective settings.
  • 2002–2004·Stanford University·M.S.
    • Field of Study: Computer Science
  • 1998–2002·Boston University·B.S.
    • Field of Study: Computer Science

This biography was generated by AI from publicly available information and may contain delays or inaccuracies.

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