CV

Updated in Oct 2026
English Resume
Chinese Resume

Education

• Master in Advanced Computing. Tsinghua University, Beijing, CN (Sep 2023 – Jun 2025).
• Bachelor of Engineering in Automation. Shanghai Jiao Tong University, Shanghai, CN. (Sep 2017 – June 2021).
• GCE A-Levels. Tunku Abdul Rahman University of Management and Technology, Kuala Lumpur, Malaysia (2015.05 – 2016.11).

Work/Internship Experience

• AI Application Engineer (Aug 2025 – Present)
  Z.ai (Zhipu AI), Beijing, China

  • Develop enterprise agent applications, focusing on Agent Harness design, multi-agent orchestration, and tool integration.
  • Lead technical planning and delivery, working with domain experts to translate business workflows into Agent capabilities.

• LLM Algorithm Engineer Intern (Jul 2024 – May 2025)
  Z.ai (Zhipu AI), Beijing, China

  • Agentic RAG
    • Conducted a comparative analysis of the company’s existing RAG framework against QWEN-Agent and the long-context model GLM-9B-128k.
    • Prepared evaluation scripts and datasets, including HotpotQA and NQ, augmented with additional distractors to increase difficulty.
    • Worked on reasoning-enhanced RAG through training data construction, supervised fine-tuning, and model evaluation.

• AI Engineer (Nov 2021 - Aug 2023)
  Wise AI, Kuala Lumpur, Malaysia

  • Face Anti-Spoofing
    • Led the R&D efforts for the development of a face anti-spoofing model.
    • Achieved compliance with ISO-30107 Level 1 Presentation Attack Detection Standards.
    • Managed the entire project lifecycle, including data collection, model design, training, evaluation, and enhancement.
  • Digital Avatar
    • Conducted R&D on the technologies behind digital avatars and broke them down into manageable components based on resource constraints.
    • Conducted in-depth research on topics such as talking head and voice cloning, contributing to the team’s expertise.
    • Led the development of a functional prototype of a digital avatar with voice cloning abilities.

Research/Project Experience

• ReaRAG: Knowledge-guided Reasoning Enhances Factuality of Large Reasoning Models with Iterative Retrieval Augmented Generation
  • Reasoning-enhanced RAG combining iterative retrieval with supervised fine-tuning for factual question answering.
  • Paper
• DiaKoP: Dialogue-based Knowledge-oriented Programming for Neural-symbolic Knowledge Base Question Answering (CIKM demo track 2024)
  • Developed a dialogue-based knowledge-intensive question answering system.
  • Designed and implemented both the frontend and backend of the system.
    • Frontend: developed based on Gradio to facilitate user interaction.
    • Backend: developed based on the FastChat framework to support model deployment, includes modules such as dialogue history tracking, natural language understanding, dialogue policy, and knowledge retrieval strategies.
• Text-to-UI: Text-to-User Interface
  • Collected datasets from the web comprising pairs of ``User Requirements - Tailwind CSS”.
  • Fine-tuned the CodeLlama model using DeepSpeed with the LoRA strategy. The fine-tuned model generates corresponding frontend interface code as output when provided with user requirements in natural language.
• MRI Brain Image Retrieval using GNNs
  • Modeled the relationships between images using Graph Neural Networks (GNN), formulate the retrieval task into graph node classification tasks.
  • Compared to baseline models, the GNN-based method improved retrieval accuracy by 2-8\%.