Dingyi Zhuang is a Senior Machine Learning Engineer at TikTok with nine years of experience building large-scale ML systems that bring cutting-edge research in time-series forecasting and supply chain optimization into production. He holds a Ph.D. from MIT and has a strong publication record (ICLR spotlight, AAAI oral, KDD, EMNLP, IEEE TPAMI) with ~1,100 citations and multiple Best Paper awards, reflecting research that tackles sparsity, uncertainty, and distribution shift in real-world settings. At TikTok he focuses on demand planning, inventory optimization, and foundation models for time series for the US TikTok Shop, having previously developed GNNs for AML detection and worked on multimodal spatial reasoning and urban systems. His work spans both theory and engineering—shipping production-ready forecasting pipelines while advancing methods for robustness under sparse signals—and he often brings urban computing insights from his MIT Transit Lab background into supply-chain problems.
9 years of coding experience
1 year of employment as a software developer
Bachelor's degree, Mechanical Engineering, Bachelor's degree, Mechanical Engineering at Shanghai Jiao Tong University
Doctor of Philosophy - PhD, Transportation, Doctor of Philosophy - PhD, Transportation at Massachusetts Institute of Technology
Master of Engineering - MEng, Transportation Engineering, Master of Engineering - MEng, Transportation Engineering at McGill University
Contributions:11 commits, 4 PRs, 9 pushes in 2 months
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