YS/CV

RESEARCH & CREDENTIALS

Research, papers, and education

AI infrastructure, efficient execution environments, unsupervised world-model pretraining, earlier generative-model research, publications, patent, and education.

2 papers · 1 patent

01

Research

Efficient execution environments for AI workloads

Current research · AI infrastructure · Runtime / WASM / DAG

Studies how model-generated dynamic tasks can be compiled and executed safely in parallel while controlling isolation boundaries, tool capabilities, scheduling overhead, and failure recovery.

Latent Rules Without Rewards: Unsupervised Environment Identification for Continual RL

Current research · Under review · Unsupervised world-model pretraining

Studies how latent rule representations of environment structure can be learned from interaction trajectories without task labels or rewards, then used for environment identification and transfer.

Robustness of latent-space watermarks in diffusion models

Earlier research · Imperial Independent Study Option · Stable Diffusion v1.5 · COCO · AUC/LPIPS

Evaluated six latent-space watermarks under image distortions, latent perturbations, and model-level regeneration attacks, and proposed a low-cost watermark-removal attack.

02

Papers and patent

  1. Paper

    STAM-LSGRU: a spatiotemporal radar echo extrapolation algorithm with edge computing for short-term forecasting

    Cheng, H., Cui, M., & Shi, Y. (2024). Journal of Cloud Computing 13, 100. DOI: 10.1186/s13677-024-00660-6.

  2. Paper

    Distributed service caching with deep reinforcement learning for sustainable edge computing in large-scale AI

    Liu, W., Bilal, M., Shi, Y., & Xu, X. (2025). Digital Communications and Networks 11(5), 1447–1456. DOI: 10.1016/j.dcan.2024.11.009.

  3. Patent

    A Blockchain Address Identity Inference Method and System Based on Deep Graph Neural Network

    Granted Chinese invention patent; co-inventor. The work originated in Shisho Guard’s blockchain address identity inference system.

03

Education

04

Awards and skills

Competition awards

  • First Prize, 17th National College Student Information Security Contest
  • First Prize, 15th China College Students Service Outsourcing Innovation and Entrepreneurship Competition
  • Second Prize, 16th National College Student Information Security Contest
  • First Prize, Jiangsu Selection of the Challenge Cup National College Student Academic and Technology Competition

Skills

Programming
TypeScript, Python, Go, C#, C++, CUDA, JavaScript
AI and systems
LLM agents, tool use, RAG, PyTorch, WASM/WASI, Linux, Docker, SLURM, AWS Lambda
Games and tools
Unity, SceneKit, Minecraft datapacks, compilers and LSPs, automated judging, SSE/WebSocket
Languages
English: IELTS 8.0 (Listening 9.0, Reading 9.0, Writing 7.0, Speaking 7.5); Japanese: basic working communication