About me

I am an Assistant Professor in Information Systems at the University of Texas at Arlington. I received my Ph.D. in Information Systems from the University of Maryland.

My research interests lie in the development and application of deep learning methodologies for inferring consumer behavior from unstructured data, with a particular focus on leveraging these insights to inform and optimize business decision-making. I am also interested in aligning large language models (LLMs) with organizational objectives to enhance their practical utility in business contexts.

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Research Interests

  • Research Design and Consumer Behavior Analysis Icon

    LLM & Multi-Agent

    Aligning LLMs with business objectives

  • Machine Learning and AI Development Icon

    Multimodal Learning

    Developing multimodal learning methods from different modalities

  • Data Mining and Business Intelligence Applications Icon

    HCI

    Developing algorithms to improve HCI systems

  • Deep Learning and Computer Vision Research Icon

    Consumer Inference

    Using AI methods to infer consumer behavior and consumer engagement

Recent News

  1. Received COB Research Grant, $5,000

  2. Received COB Research Award 2025: $10,000

About Me

Education

  1. Nanjing University of Information Science and Technology

    2010 — 2014 Nanjing, China

    B.S. in Financial Engineering

  2. Rutgers University

    2016 — 2017 Newark, NJ

    M.S. in Quantitative Finance

  3. University of Maryland

    2018 — 2024 College Park, MD

    Ph.D. in Information Systems

Industry Experience

  1. Data Scientist at WhitePark Capital

    Jan 2018 — Aug 2018 New York, NY

  2. Research Intern at AT&T Labs

    May 2019 — Sep 2019 San Francisco and San Ramon, CA

  3. Machine Learning Intern at AT&T Labs

    Technical Development Program May 2020 — Sep 2020 San Ramon, CA

Awards and Grant

  1. COB Research Grant, $5000, University of Texas Arlington, 2025

  2. COB Research Award, $10000, University of Texas Arlington, 2025

  3. Outstanding Research Assistant, University of Maryland, 2023 - 2024

  4. Student Travel Award, IEEE Big Data, 2023

  5. Student Scholarship, INFORMS Workshop on Data Science, 2023

  6. FDA-CERSI Fellowship, 2023-2024

  7. Jacob K. Goldhaber Travel Grant Award, University of Maryland, 2023

  8. Best Student Paper Runner-Up Award, Workshop on Information Technologies and Systems (WITS), Copenhagen, Demark, Dec 2022

  9. Outstanding Research Assistant, University of Maryland, 2021 - 2022

  10. Faculty-Student Research Award (FSRA), $10000, University of Maryland, 2021 - 2022

  11. University Assistantship, University of Maryland, 2019 - 2023

Service

  1. Associate Editor

    • PACIS 2026, INFORMS 2026

  2. Journal Review

    • ISR, MISQ, POMS, TMIS

  3. Conference Review

    • IS: CIST, ICIS, WITS, INFORMS Workshop on Data Science CS: KDD, WCAC, ACL, WACV, NeurIPS

  4. Program Committee

    • CS: COLING 2025, ICASSP 2026 IS: WITS 2025, CIST 2025

Personal Interests

Reading hobby illustration - Academic Research and Learning
Traveling hobby illustration - International Academic Conferences
Cooking hobby illustration - Work-Life Balance

I enjoy a balance of active, adventurous, and tech-focused hobbies that keep me engaged in different ways. Playing basketball is one of my favorite pastimes, as it combines fitness, competition, and teamwork. I also love traveling and exploring nature, especially hiking, where I can experience new places and appreciate the outdoors. Alongside my adventurous side, I have a strong interest in technology—I enjoy building computers and diving into new “techie” projects that let me be creative and problem-solve.

Research

  • LLM & Multi-Agent

    LLM & Multi-Agent

    Aligning large language models with organizational and societal objectives to enhance their practical utility in real-world business and decision-making contexts.

  • Aligning Images with Intent: A Multi-Agent Framework for Prompt Optimization in Generative Visual Marketing

    With Bingze Xu and Kunpeng Zhang

    Under Review Business

  • Large Language Model for Business-Value Alignment

    With Kunpeng Zhang, Balaji Padmanabhan and Bingze Xu

    To be Submitted Business

  • A Theory-Driven Context-Dependent LLM Knowledge Extraction Model for Misinformation Detection

    With Maya Mudambi, Siva Viswanathan and Balaji Padmanabhan

    In Progress Business
  • Multimodal Learning

    Multimodal Learning

    Developing deep learning models that fuse visual, audio, and text modalities to understand complex human signals such as personality, emotion, and intent.

  • A Multimodal Framework for Video-Based Apparent Personality Understanding

    With Kunpeng Zhang and Balaji Padmanabhan

    Major Revision Information Systems Research Business

  • Multimodal Co-attention Transformer for Video-Based Personality Understanding

    Mingwei Sun and Kunpeng Zhang

    Published IEEE BigData 2023  ·  Acceptance rate: 17.5% CS

  • Sec2Sec Co-Attention Transformer for Video Emotion Prediction

    Mingwei Sun and Kunpeng Zhang

    Published IEEE ICASSP 2024, Seoul, Korea CS
  • HCI

    HCI

    Developing algorithms to improve HCI systems.

  • A Diffusion Model for Image-Audio Alignment

    With Biyang Xin, Shijie Zhang and Xitong Li

    In Progress

  • A Text-Backed Audio Generative Model

    With Shufan Chai, Shijie Zhang and Xitong Li

    In Progress

  • An EEG to Audio Generative Model

    With Shen Xie, Shijie Zhang and Xitong Li

    In Progress
  • Consumer Inference

    Consumer Inference

    Inferring latent consumer preferences and behavior from unstructured data to generate actionable insights that improve marketing and business strategy.

  • Signals of Efforts or Evidence of Automation? The Countersignaling Effect of Prompt Disclosure

    With Jiding Zhang, Che-Wei Liu, Xiaowei Liu and Jiang Duan

    Under Review Business SSRN

  • From Ideation to Automation: Stochastic Reliance in Probabilistic Creative Systems

    With Jisu Cao, Che-Wei Liu and Xiaowei Liu

    To be Submitted Business

Contact

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