An Assistant Professor of the Institute of Technology Management at National Tsing Hua University.
Currently, I’m exploring how AI is changing various aspects of management and business decision-making, and how we,
as managers, can respond proactively to master it rather than let it master us.
If you happen to work on similar topics or would like to chat about anything else, please feel free to reach out!
PhD in Management (Innovation, Technology and Operations)
Rady School of Management, University of California - San Diego, June 2026
MSc in Statistics
School of Mathematics and Statistical Sciences, Arizona State University, May 2020
MSc in Management
W. P. Carey School of Business, Arizona State University, May 2018
BA in Economics
Department of Economics, Soochow University, June 2016
1. Designing Data Science Contests: The Role of Training vs Test Splits
• Co-authored with Zhe Zhang and Sanjiv Erat
• Minor revision at Management Science
• Winner, 2025 INFORMS TIMES Best Working Paper Award
• Featured in SSRN Top Downloads for Innovation & Operations (full paper link)
Abstract: Companies organize data science contests to source innovative machine learning solutions for business operations. The current study formulates a model of data science contests to investigate how participants choose their modeling approaches and the incentives they face in the competition, and reveals how data splitting practices can unintentionally incentivize suboptimal modeling strategies.
2. Human and AI Perspectives in Creativity Evaluation
• Co-authored with Sanjiv Erat
• Presented at the 2026 Annual POMS Conference
Abstract: With AI-based tools improving at an exponential pace, the day is perhaps not far off when management of knowledge work and of knowledge workers becomes just another skill that can be performed by AI supervisors. The current study investigates how a person’s creative performance is affected by the identity of the feedback giver and the nature of the feedback.
3. Splitting the Difference: Automatic Judging of Large Language Models
Abstract: LLM-as-Judge systems now replace costly human raters for benchmarking large language models, yet their reliability is underexamined. The current study analyzes how data splitting and cross validation affect their agreement with human preferences using Chatbot Arena and MT-Bench, guiding the design of scalable and trustworthy evaluation methods for next-generation language models.
1. Instructor
• Management (syllabus link),
which investigates how managers make decisions, coordinate people, allocate resources, and respond to change while using AI and big data thoughtfully,
with human judgment, strategy, and organizational effectiveness at the center.
• Business Project Management (syllabus link),
which illustrates how managers plan, coordinate, and monitor real-world projects through scheduling, resource allocation, progress tracking, and
risk management with tools such as ChatGPT, Radiant, and Microsoft Excel Gantt Charts.
2. Teaching Assistant
• AI-Assisted Customer Analytics (core in MSc in Business Analytics program)
○ Content: Applying machine learning to collect, analyze, and act on customer data and create value for both customers and firms
○ Software: ChatGPT, Python, R, Radiant, Docker
• Business Analytics (core in MSc in Business Analytics program)
○ Content: Making good decisions in complex business problems with statistical and quantitative models such as decision analysis, regression analysis, optimization and simulation
○ Software: Python, R, Radiant
• Operations, Information Systems and Data Analysis (core in MBA program)
○ Content: Synthesizing information and applying operational metrics for systematic design, business execution, and improvement of operations and partner relationships
○ Platform: Littlefield Simulation
• Supply Chain Analytics (elective in MSc in Business Analytics program)
○ Content: Understanding and managing the flows of materials and information in a supply chain
○ Topics: Newsvendor, Inventory Control, Demand Forecasting, Revenue Management
• Applied Market Research (elective in MBA program)
○ Content: Conducting research projects for data-driven decision making using surveys, interviews, and advanced tools such as adaptive conjoint analysis
○ Software: Radiant, Sawtooth