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Liu, Liu

Assistant Professor

Positions

Research Areas research areas

Research

research overview

  • Liu's research focuses on the intersection of marketing and machine learning, particularly in the areas of visual marketing, social media, product design, branding, and consumer choice modeling. Her recent work proposes a “visual listening in” approach to measure brand perceptions portrayed on social media and shows what insights brand managers can gather from consumer-created brand images. It leverages the state-of-art machine learning and deep learning methods to generate insights from visual data on social media. Another research stream develops novel machine learning methods that better capture complex consumer choice processes. It takes advantage of the efficiency and scalability of machine learning, and it is tailored specifically to marketing applications with a deep understanding of human behavior and economic theories.

keywords

  • visual marketing, social media, product design, consumer choice modeling, branding, machine learning

Publications

selected publications

Teaching

courses taught

  • MKTG 4300 - Pricing and Channels of Distribution
    Primary Instructor - Fall 2018 / Fall 2019
    Offered regularly to examine pricing and channel management, the two key components of companys' marketing strategies. Help students to understand the common types of pricing and channel strategies, the rationales behind these strategies. Train students to think analytically in order to apply these strategies. Required for marketing majors.
  • MSBC 5190 - Modern Artificial Intelligence: Introduction to AI for Business
    Primary Instructor - Spring 2022
    Provides students with a comprehensive introduction of recent developments in AI by covering fundamental AI concepts and practical applications of these concepts in business. Will review major advances in AI subfields of Deep Learning, Reinforcement Learning, Natural Language Processing, Computer Vision, Recommender Systems, Robotics, and others. Students will learn how to apply AI-based methods to solving practical business problems, acquiring acquire knowledge and hands-on experience of modern AI tools, including the Deep Learning framework Tensorflow. Recommended prerequisite: experience in Python and basic probability/statistics.

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