Dokyun (DK) Lee

Kelli Questrom Associate Professor in Management Associate Professor, Information Systems

Dokyun (DK) Lee studies the {application, development, impact} of AI in e-commerce and the digital economy with focus on text.

Specific agenda includes (1) developing and applying interpretable machine learning & natural language processing algorithms for economics of unstructured data, and (2) applying generative models on text for algorithmic theory building. He also runs the BITLab (Business Insights through Text Lab) to study application domains such as content engineering and advertising, social media marketing, brand sentiment, technological innovation, and persuasion.

His work has been published at journals and conferences including Management Science, Information Systems Research, Journal of Marketing Research, AAAI, AIES, and WWW. He is a recipient of ISS Gordon B Davis Young Scholar, 2021 Marketing Science Institute Young Scholar, CDO Magazine Academic Data Leader, ISR Best Paper Award, MSBA Teaching Award, Management Science Distinguished Service Award, and Best Conference Paper Awards. His work is supported by organizations such as Adobe, Bosch Institute, Google Cloud, Marketing Science Institute, McKinsey & Co, Nvidia, and Net Institute.

DK holds a Bachelor’s degree in Computer Science from Columbia University (Machine Learning Focus), a Master’s degree in Statistics (Master’s Thesis: Johnson-Lindenstrauss Lemma and its Effect on Supervised Learning) from Yale University and PhD from the Operation, Information and Decisions department of the Wharton School (Thesis: Three Essays in Big Data Consumer Analytics in E-Commerce). Before academia, DK worked at 4 tech start-ups and Blackrock as a quantitative software engineer and at Thomson Reuters as an ML contractor building a natural language processing engine for financial data.

Please contact for Academic-Industry research collaboration, consulting, and speaking inquiries.

    Education
  • Phd, The Wharton School, 2015
  • MA, Yale University, 2010
  • BA, Columbia University, 2009
    Publications
  • Zhang, S., Lee, D., Singh, P., Srinivasan, K. (2021). "What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features", Management Science
  • Zhang, S., Lee, D., Singh, P., Mukhopadhyay, T. (2021). "EXPRESS: Demand Interactions in Sharing Economies: Evidence from a Natural Experiment Involving Airbnb and Uber/Lyft", Journal of Marketing Research 002224372110621-002224372110621
  • Burtch, G., He, Q., Hong, Y., Lee, D. (2021). "How Do Peer Awards Motivate Creative Content? Experimental Evidence from Reddit", Management Science
  • Lee, D., Hosanagar, K. (2021). "How Do Product Attributes and Reviews Moderate the Impact of Recommender Systems Through Purchase Stages?", Management Science, 67 (1), 524-546
  • Proserpio, D., Hauser, J., Liu, X., Amano, T., Burnap, A., Guo, T., Lee, D., Lewis, R., Misra, K., Schwarz, E., Timoshenko, A., Xu, L., Yoganarasimhan, H. (2020). "Soul and machine (learning)", Marketing Letters, 31 (4), 393-404
  • Liu, X., Lee, D., Srinivasan, K. (2019). "Large-Scale Cross-Category Analysis of Consumer Review Content on Sales Conversion Leveraging Deep Learning", Journal of Marketing Research, 56 (6), 918-943
  • Lee, D., Hosanagar, K. (2019). "How Do Recommender Systems Affect Sales Diversity? A Cross-Category Investigation via Randomized Field Experiment", Information Systems Research, 30 (1), 239-259
  • Lee, D., Hosanagar, K., Nair, H. (2018). "Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook", Management Science, 64 (11), 5105-5131
  • Hosanagar, K., Fleder, D., Lee, D., Buja, A. (2014). "Will the Global Village Fracture Into Tribes? Recommender Systems and Their Effects on Consumer Fragmentation", Management Science, 60 (4), 805-823
    Research Presentations
  • Lee, D. , Tambe, P. , Zhaoqi, C. InnoVAE: Generative AI for Understanding Patents and Innovation, KAIST, 2021
  • Lee, D. , Tambe, P. , Zhaoqi, C. InnoVAE: Generative AI for Understanding Patents and Innovation, University of Wisconsin Madison, 2021
  • Lee, D. , Tambe, P. , Zhaoqi, C. InnoVAE: Generative AI for Understanding Patents and Innovation, University of Washington, 2021
  • Lee, D. , Tambe, P. , Zhaoqi, C. InnoVAE: Generative AI for Understanding Patents and Innovation, University of Hamburg, 2021
  • Lee, D. , Tambe, P. , Zhaoqi, C. InnoVAE: Generative AI for Understanding Patents and Innovation, UT Austin (Marketing), 2021
  • Lee, D. , Tambe, P. , Zhaoqi, C. InnoVAE: Generative AI for Understanding Patents and Innovation, Harvard University (TOM), 2021
  • Lee, D. , Manzoor, E. , Zhaoqi, C. Focused Concept Miner, Michigan State University, 2021
  • Lee, D. , Manzoor, E. , Zhaoqi, C. Focused Concept Miner, UBC, 2021
  • Lee, D. , Tambe, P. , Zhaoqi, C. InnoVAE: Generative AI for Understanding Patents and Innovation, Northwestern University
    Awards and Honors
  • 2021, MSI Young Scholar 2021
  • 2021, MSBA Faculty Excellent Award for Teaching
  • 2021, Best Paper in Psychology of Technology Award
  • 2021, Management Science ISR Division 2018-2020 Best Paper Award, Institute for Operations Research and the Management Sciences
  • 2020, WISE 2020 Best Student Paper Award
  • 2020, Best Student Paper Runner Up
  • 2020, Best Paper Award In Information System Research 2021
  • 2020, CDO Magazine 2021 List of Leading Academic Data Leaders
  • 2020, ISS Inaugural Gordon B. Davis Young Scholar
  • 2020, Management Science ISR Division 2017-2019 Best Paper Award, Institute for Operations Research and the Management Sciences