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Jenny Wang

Jenny Wang

Doctoral Student

Doctoral Student

Jenny S. Wang is a doctoral student in the Technology and Operations Management program at Harvard Business School (HBS).
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Jenny Shan Wang is a doctoral student in the Technology and Operations Management program at Harvard Business School (HBS). She is broadly interested in interpretable machine learning (ML), identity and inequality, and improving existing methods used to answer social and policy-relevant questions. Her recent projects have focused on developing tools that explore how LLMs are reshaping human interactions with technology. Previously, Jenny was a pre-doctoral researcher in the Computational Social Science (CSS) Lab at Microsoft Research. She graduated from Wellesley College with B.A. degrees in Computer Science and Economics.
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Jenny Wang
Contact Information
Research Summary Awards & Honors
Overview
Jenny is broadly interested in interpretable machine learning (ML), identity and inequality, and improving existing methods used to answer social and policy-relevant questions. Her recent projects have focused on developing tools that explore how LLMs are reshaping human interactions with technology.
Keywords: Machine Learning; Fairness; Information Technology; Decision Making; AI and Machine Learning
Jenny Shan Wang is a doctoral student in the Technology and Operations Management program at Harvard Business School (HBS). She is broadly interested in interpretable machine learning (ML), identity and inequality, and improving existing methods used to answer social and policy-relevant questions. Her recent projects have focused on developing tools that explore how LLMs are reshaping human interactions with technology. Previously, Jenny was a pre-doctoral researcher in the Computational Social Science (CSS) Lab at Microsoft Research. She graduated from Wellesley College with B.A. degrees in Computer Science and Economics.
Research Summary
Overview
Jenny is broadly interested in interpretable machine learning (ML), identity and inequality, and improving existing methods used to answer social and policy-relevant questions. Her recent projects have focused on developing tools that explore how LLMs are reshaping human interactions with technology.
Keywords: Machine Learning; Fairness; Information Technology; Decision Making; AI and Machine Learning
Awards & Honors
Recipient of a National Science Foundation Graduate Research Fellowship (GRFP).
Additional Information
  • Personal Website
Area of Study
  • Technology and Operations Management
Areas of Interest
  • artificial intelligence
  • machine learning
Additional Information
Personal Website

Area of Study

Technology and Operations Management

Areas of Interest

artificial intelligence
machine learning
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