I am a second year MBA candidate studying Business Analytics with concentrations in Business Technology and Operations Research at the Tepper School of Business at Carnegie Mellon University. I am advised by Professor Dokyun Lee.

I will be applying to PhD programs for Fall 2021 entry.

Prior to Tepper, I graduated from Washington University in St. Louis with degrees in Finance and Marketing from the Olin Business School in 2018. Post-graduation, I worked as an analyst at a large market research firm where I consulted for CPG clients seeking to innovate on their products.

I am a self-learned Machine Learning and Deep Learning practitioner. A future goal of mine is to make Machine Learning accessible to students and professionals from all backgrounds. With a broader pool of collective intelligence across disciplines, I believe we can improve the human experience through a deeper understanding of the world.

My Research Interests

Methodologically, I am interested in developing human-computer collaboration paradigms and new technology to ethically and sustainably integrate human and AI intelligence to augment managerial decision making and policy development.

Substantively, I seek to apply and evaluate human-computer collaboration systems to examine provocative questions in human-machine symbiosis and collective intelligence. Specific applications include AI-driven product ideation and AI-mediated interaction in the mobile economy and social media.

Philosophically, I believe that a human-centric approach to operationalizing pervasive, intimate systems can transform social and economic interactions to increase welfare.

Current Projects

  1. Dokyun Lee, Eric Zhou, Chengfeng Mao, Gerald Kane. Interpretable Machine Learning Can Be Useful Tools For Theory Building: A Human-AI Collaboration.
    Accepted to MISQ Author Workshop 2020. Work in progress.

    “Recent advances in Interpretable Machine Learning (IML) offer potential flexible, scalable solutions to augment novel hypothesis development, 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.”


9/21/20 - Focused Concept Miner Command Line Interface and User Guide & Demonstration have been publicly released! Learn more at FCMiner.com.