Zhikun

My name is Zhikun Lu. I am a PhD candidate in Business (Operations Management track, STEM) from Goizueta Business School, Emory University. My research focuses on causality-driven decision making (what is CDDM?) with applications in online retail, supply chains, and digital entertainment, utilizing techniques from causal inference, machine learning, and optimization. During my PhD, I have collaborated with leading tech companies, including Alibaba, Amazon, and Tencent, developing causal-machine-learning-based optimization models to improve various business outcomes, such as sales, customer lifetime value, and user engagement. I am passionate about discovering innovative ideas, mastering new skills, and applying them to address real-world business challenges.
I am on the 2024-2025 job market.		Contact: zhikun[dot]lu[at]emory[dot]edu
Google Scholar	SSRN Author Page	Emory Profile	Curriculum Vitae

Awards

1. Runner-up, 2024 POMS College of Supply Chain Management Student Paper Competition
– “The Value of Last-mile Delivery in Online Retail”

2. Finalist, 2023 MSOM Student Paper Competition
– “Sooner or Later? Promising Delivery Speed in Online Retail”

3. Winner, 2021 ICIS Best Paper in Track Award (Digital and Mobile Commerce)
– “Sooner or Later? Promising Delivery Speed in Online Retail”

Research

[Data Science and Operations]

1. "Sooner or Later? Promising Delivery Speed in Online Retail," with Ruomeng Cui, Tianshu Sun, and Joe Golden, 2024, Manufacturing & Service Operations Management (a top business journal, UTD24, FT50)

2. "The Value of Last-mile Delivery in Online Retail" with Ruomeng Cui, Tianshu Sun, and Lixia Wu, Major Revision at Management Science (a top business journal, UTD24, FT50)

3. "Incentives in Online Gaming: Optimal Policy Design with Dynamic Causal Machine Learning" with Ruomeng Cui and Yang Su, Woking Paper
– INFORMS Annual Meeting, Seattle, WA (2024)

4. "Food Delivery Platform Expansion Strategies: A Structural Approach" with Ruomeng Cui and Wenchang Zhang, Woking Paper
– POMS Annual Meeting, Atlanta, GA (2025, scheduled)

[Economics and Finance] (these projects were initiated before my PhD in Business)

5. "How Contagious Was the Panic of 1907? New Evidence from Trust Company Stocks," with Caroline Fohlin, 2021, AEA Papers and Proceedings (a leading journal for econ faculty)

6. "Preferential Credit Policy with Sectoral Markup Heterogeneity" with Kaiji Chen, Yuxuan Huang, Xuewen Liu, and Yong Wang, Revise & Resubmit

7. "A Model of China’s Economic Vertical Structure" with Xi Li, Xuewen Liu, and Yong Wang, Revise & Resubmit

8. "Short Sale Bans May Improve Market Quality During Crises: New Evidence from the 2020 Covid Crash" with Caroline Fohlin and Nan Zhou, Under Review
– See VoxEU Column for a non-technical summary

Industry Experience

1. Data Scientist Intern at Tencent, Palo Alto, CA, USA, Jan 2024 – Jul 2024

2. Applied Scientist Intern at Amazon, Bellevue, WA, USA, May 2023 – Sep 2023

3. Algorithm Engineer Intern at Alibaba Group, Hangzhou, China, Jun 2021 – Aug 2022