Jinke Li (李金珂 / Ryan Li)

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Hello! My name is Jinke Li (李金珂/Ryan Li), a second-year Master's student specializing in Artificial Intelligence at the RVCLab of Zhejiang University. I am fortunate to be mentored by Professor Liangjing Yang, who hails from Singapore. Beyond academics, I am passionate about fitness and exploring diverse cultures around the globe. If you'd like to connect or collaborate, feel free to reach out—I always welcome new friendships! test_world

Projects

Project 1

UniSVG: A Unified Dataset for Vector Graphic Understanding and Generation with Multimodal Large Language Models

🏆 ACM MM 2025 (CCF-A) Dataset Track Accepted! 🏆

Jinke Li, Jiarui Yu, Chenxing Wei, Hande Dong, Qiang Lin, Liangjing Yang, Zhicai Wang, Yanbin Hao.

Project 2

Two-Stage Multi-Stained Cell Analysis with the Segment Anything Model for Pathological Image Segmentation

🏆 ICIC 2025 Oral (CCF-C) 🏆

Jinke Li, Fang Yan, Xiaofan Zhang, Liangjing Yang.

Project 3

A Review of Contact-Based Robotic Micromanipulation Systems: Technology and Applications

🏆 Journal of Intelligent & Robotic Systems 🏆

Yun Long, Tianle Weng, Tiexin Wang, Jinke Li, Songjie Xiao, Bing Li, Liangjing Yang.

Work Experiences

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Product Manager Intern (AI Background)

Company:Tencent

Time: August 2025 - Now

Responsibilities:

  • Conducted research on various forms of AI Coaches in the gaming industry and produced a comprehensive report.
  • Participated in the design of in-game AI Coach solutions for a turn-based monster battle game.
  • Managed project scheduling and overall progress, from data integration and knowledge base construction to phased feature implementation.
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AI Technology Strategy Intern

Company:Rednote

Time: May 2025 - June 2025

Responsibilities:

  • Conduct research and analysis on emerging AI technologies to support strategic decision-making.
  • Collaborate with cross-functional teams to design and implement AI-driven solutions.
  • Prepare detailed reports and presentations on AI trends and their potential impact on business operations.
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LLM Application Research Intern

Company:Tencent

Time: June 2024 - June 2025

Responsibilities:

  • Multimodal Large Model Application Research: Conducted research on the application of multimodal large language models for converting scalar graphs/text into SVG vector graphics, covering areas such as vector graphic generation, understanding, and Q&A.
  • Dataset Construction and Model Finetuning: Built the first comprehensive dataset for vector graphic-related tasks to train multimodal large models. Fine-tuned multiple mainstream models (e.g., LLaVA 1.5, Qwen 2.5 VL) based on this dataset, achieving performance surpassing SOTA (GPT-4V, Gemini Pro) on SVG-related tasks.
  • Academic Contribution: Published a research paper based on the findings and admitted to ACM MM 2025. Project Website
  • AI Product Manager Intern: Participated in the product planning and design of AI design analysis features and ideation tools in Tencent's design editor, collaborating with visual designers and front-end engineers to define product functionality and drive implementation.
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Artificial Intelligence and Smart Healthcare Researcher Intern

Company:Shanghai Artificial Intelligence Laboratory

Time: July 2023- September 2023

Responsibilities:

  • Medical Image Processing Research: Conducted analysis and research on popular medical image processing models, including U-Net, Deeplab, and Segment Anything Model, focusing on image segmentation and processing.
  • Dataset Collection and Model Development: Collected and processed over 10 pathological datasets, comprising 28,000 images across more than 5 modalities, and developed a foundational model for Two-Stage Multi-Stained Cell Analysis.
  • Academic Achievement: Published research findings as an oral presentation at ICIC 2025 (CCF-C).
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Electrical Engineer Intern

Company:Zhejiang Svac Optoelectronics Technology Co., Ltd.

Time: June 2022- July 2022

Responsibilities:

  • Design of Detection Device: As an electrical engineer, utilized AutoCAD to design the detection device for the company's latest generation of vacuum coating machines.
  • Implementation: Successfully deployed the designed detection device, which is now in operational use.