Lifan Zhao
Lifan Zhao

PhD candidate

Shanghai Jiao Tong University

About Me

I am a final-year Ph.D. student in Computer Science at Shanghai Jiao Tong University, supervised by Prof. Yanyan Shen. I am broadly interested in meta-learning, online learning, and post-training for foundation models. My previous work mainly focus on data-driven applications including time series forecasting and recommender systems. I recently worked on Agentic AI at Tongyi Lab, Alibaba Group, and I am currently working on multi-modal time series reasoning at ByteDance.

I am on the job market now! Please reach out if you think I could be a fit for your group.

Interests
  • Meta-Learning
  • Online Learning
  • Data-Centric AI
  • LLM Post-Training
Education

  • Ph.D. in Computer Science

    Shanghai Jiao Tong University

  • B.Eng. in Software Engineering

    Shandong University

Recent Publications
Lifan Zhao, Yanyan Shen, Zhaoyang Liu, Xue Wang, Jiaji Deng (2025). Less is More: Unlocking Specialization of Time Series Foundation Models via Structured Pruning. The Thirty-ninth Annual Conference on Neural Information Processing Systems (NeurIPS'25).
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Lifan Zhao, Yanyan Shen (2025). Proactive Model Adaptation Against Concept Drift for Online Time Series Forecasting. Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'25).
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Lifan Zhao, Yanyan Shen (2024). Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators. The Twelfth International Conference on Learning Representations (ICLR'24).
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Zexi Zhang, Lifan Zhao, Yanyan Shen, Bin Yao (2024). StockCL: Selective Contrastive Learning for Stock Trend Forecasting via Learnable Concepts. Database Systems for Advanced Applications: 29th International Conference (DASFAA'24).
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Lifan Zhao, Shuming Kong, Yanyan Shen (2023). DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend Forecasting. Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'23).
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Yanyan Shen, Lifan Zhao, Weiyu Cheng, Zibin Zhang, Wenwen Zhou, Lin Kangyi (2023). RESUS: Warm-up Cold Users via Meta-learning Residual User Preferences in CTR Prediction. ACM Transactions on Information System (TOIS).
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Liping Wang, Jiawei Li, Lifan Zhao, Zhizhuo Kou, Xiaohan Wang, Xinyi Zhu, Hao Wang, Yanyan Shen, Lei Chen (2023). Methods for Acquiring and Incorporating Knowledge into Stock Price Prediction: A Survey.
Cite arXiv
Muyang Ma, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Lifan Zhao, Peiyu Liu, Jun Ma, Maarten De Rijke (2022). Mixed Information Flow for Cross-Domain Sequential Recommendations. ACM Transactions on Knowledge Discovery from Data (TKDD).
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Experience

  1. Soaring Star Talent Program Intern

    ByteDance

  2. Research Intern

    TongYi Lab, Alibaba Group

Education

  1. Ph.D. in Computer Science

    Shanghai Jiao Tong University

    Supervised by Prof. Yanyan Shen,

    Data Driven Software Technology Lab

  2. B.Eng. in Software Engineering

    Shandong University