I am currently a Ph.D. candidate in Computer Application Technology at the College of Computer Science and Artificial Intelligence, Fudan University, advised by Prof. Cheng Jin. I also work closely with Prof. Weizhong Zhang. I received my B.S. degree in Computer Science and Technology from Fudan University in 2021.

Research Interests

My research interests include but are not limited to:

• Data Efficiency: Data selection, core-set construction, and optimizing the data foundation for model training.
• Model Efficiency: Model compression, efficient training and inference strategies, and Scaling Laws and architecture optimization for large-scale models.
• Model Robustness: Anomaly detection and Out-of-Distribution (OOD) detection to enhance model reliability.
• Multi-Agent LLMs & AI for Science: Multi-agent LLM systems for scientific computing (e.g., DFT), including their automation and evaluation methodologies.

Recent Publications

Holistic Scaling Laws for Optimal Mixture-of-Experts Architecture Optimization
Weilin Wan, Jingtao Han, Weizhong Zhang, Cheng Jin
arXiv preprint arXiv:2603.21862, 2026

Explore and Establish Synergistic Effects Between Weight Pruning and Coreset Selection in Neural Network Training
Weilin Wan, Fan Yi, Weizhong Zhang, Quan Zhou, Cheng Jin
Published in AAAI Conference on Artificial Intelligence (AAAI), 2026

Advanced Black-Box Tuning of Large Language Models with Limited API Calls
Zhikang Xie, Weilin Wan, Peizhu Gong, Weizhong Zhang, Cheng Jin
Published in AAAI Conference on Artificial Intelligence (AAAI), 2026

Computational Budget Should Be Considered in Data Selection
Weilin Wan, Weizhong Zhang, Cheng Jin
Published in Neural Information Processing Systems (NeurIPS), 2025

Academic Service

I actively participate in the peer review process for top-tier computer vision and machine learning conferences and journals.

• Conference Reviewer:
  • Neural Information Processing Systems (NeurIPS): 2024, 2025
    • 🏆 Selected as Top Reviewer (NeurIPS 2024, 2025)
  • International Conference on Learning Representations (ICLR): 2025, 2026
  • IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR): 2026
  • AAAI Conference on Artificial Intelligence (AAAI): 2026
• Journal Reviewer:
  • Transactions on Machine Learning Research (TMLR)