Current Projects

  1. Dokyun Lee, Eric Zhou, Chengfeng Mao, Gerald Kane. Interpretable Machine Learning For Theory Building: Human-AI Collaboration.
    Accepted to MISQ Author Workshop. Work in progress.

    “Recent advances in Interpretable Machine Learning (IML) offer potential flexible, scalable solutions to help humans develop novel hypotheses, especially with exponential growth in unstructured data. We demonstrate by applying a novel IML algorithm on three datasets to reproduce theory-driven insights from literature.”

  2. Focused Concept Miner User Guide for alpha/beta release. See the original paper, Focused Concept Miner (FCM): Interpretable Deep Learning for Text Exploration and for details.