CV

You can find pdf here: CV.

Education

• Ph.D. in Computer Application Technology, Fudan University, 2027 (expected)
• B.S. in Computer Science and Technology, Fudan University, 2021

Work experience

• Nov 2025 - Present: LLM Pre-training Algorithm Intern
  • Xiaohongshu
  • Duties include: Investigated Scaling Laws and structural parameter optimization for MoE models; designed a pipeline mapping compute budgets to optimal structural parameter allocations. Researched efficient and robust data mixture algorithms, utilizing low-rank matrices to model interaction relationships across different data domains.
• Spring 2020 - Summer 2020: Deep Learning Intern
  • Fosun Lead Intelligence (Shanghai) Pharmaceutical Technology Co., Ltd.
  • Duties included: Conducting research on Tumor Precision Medicine based on deep learning; Designed and developed Graph Message Passing Neural Networks (GMPNN) tools for molecular property analysis.

Publications

Holistic Scaling Laws for Optimal Mixture-of-Experts Architecture Optimization

Explore and Establish Synergistic Effects Between Weight Pruning and Coreset Selection in Neural Network Training

Advanced Black-Box Tuning of Large Language Models with Limited API Calls

Computational Budget Should Be Considered in Data Selection

Out-of-distribution detection using neural activation prior

Pose-Motion Video Anomaly Detection via Memory-Augmented Reconstruction and Conditional Variational Prediction

Teaching

Introduction to Computer Systems (ICS), AIE210006.01

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
  • AAAI Conference on Artificial Intelligence (AAAI): 2026
• Journal Reviewer:
  • Transactions on Machine Learning Research (TMLR)