CV

You can find pdf here: CV.

Education

Jun 2026 - Present: LLM Algorithm Intern
- miHoYo
- Duties include: Research on agentic data processing for LLM training, building LLM-agent-based pipelines for data cleaning, synthesis, and quality control. Exploration of data scaling laws, characterizing how data scale, mixture, and quality affect model performance.
Apr 2026 - May 2026: Research Intern
- Warp Engine Intelligence
- Duties include: Led the design of a hierarchical benchmark and a multi-dimensional evaluation framework, and conducted a systematic survey of agent systems and materials benchmarks in the field. Researched multi-agent LLM systems for automating Density Functional Theory (DFT) computation.
Nov 2025 - Apr 2026: 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.

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)