1. Philosopher Inequality for Online Assortment Optimization
with Ming Hu and Shreyas Sekar
Extended abstract in the Proceedings of the 27th ACM Conference on Economics and Computation (EC '26)
2. Constant-Factor Algorithms for Revenue Management with Consecutive Stays
with Ming Hu
Under revision at Operations Research
3. Diversity-Fair Online Selection
with Ming Hu and Yanzhi Li
R&R at Operations Research
4. Joint Inventory and Assortment Optimization under General Choice Models
with Qiaochu Fu, Woonghee Tim Huh, and Yanzhi Li
Under revision at Operations Research
with Max Zuo-Jun Shen and Yanzhi Li
Under minor revision at Manufacturing & Service Operations Management
6. Multi-Purchase Markov Choice Model: Estimation and Assortment Optimization
with Woonghee Tim Huh, Menglong Li, and Yanzhi Li
• Ming Hu, Shreyas Sekar, and Tongwen Wu. Philosopher Inequality for Online Assortment Optimization. Proceedings of the 27th ACM Conference on Economics and Computation (EC '26)
• Tongwen Wu, Yu Yang, Yanzhi Li, Huiqiang Mao, Liming Li, Xiaoqing Wang, and Yuming Deng. Representation Learning for Predicting Customer Orders. ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD ’21). 2021. pp. 3735–3744.
• Tongwen Wu, Zizhen Zhang, Yanzhi Li, and Jiahai Wang. Collective Mobile Sequential Recommendation: A Recommender System for Multiple Taxicabs. International Conference on Tools with Artificial Intelligence (ICTAI). 2019. pp. 1260-1264
• Tongwen Wu, Huiqiang Mao, Yanzhi Li, and Di Chen. Assortment Selection for a Frontend Warehouse: A Robust Data-Driven Approach. International Conference on Computers and Industrial Engineering (CIE 2019). 2019.