CV

Short CV. For the full and most up-to-date version, please download the PDF above.

Contact Information

Name Binjie Zhang
Professional Title Ph.D. Candidate, Computer Science
Email binjie97@u.nus.edu

Professional Summary

Ph.D. candidate at Show Lab, National University of Singapore. Research interests span LLM agents (harness, memory, tool use, self-evolution), vision-language and video understanding, world models, and lifelong / compatible representation learning.

Experience

  • 2026 - 2026

    Singapore

    AI Research Intern
    TikTok (ByteDance)
    Sole owner of several LLM-agent research and production projects, end-to-end from design to deployment.
    • Pivoted from a vision / world-model background to a large-scale LLM-agent stack within two weeks.
    • Designed and implemented a declarative, skill-based agent harness with LLM semantic routing and progressive disclosure.
    • Built an Agent-Native self-evolving training loop (Diagnose, Hypothesize, Experiment, Evaluate, Reflect) on top of internal training / data / monitoring / deployment platforms.
    • Researched training-free optimization of agent memory (retrieval, write, eviction) for long-horizon tool-use agents.
    • End-to-end ownership - design, implementation, cross-team integration, review, and production rollout.
  • 2023 - Present

    Singapore

    Ph.D. Researcher
    Show Lab, National University of Singapore
    Research on LLM agents, world / predictive models, and lifelong / compatible representation learning.
    • Reflection-augmented policy optimization for tool-using agents (ReGRPO).
    • Lifelong imitation learning for robotic manipulation (RCFC).
    • Egocentric future prediction conditioned on hand trajectories.
  • 2020 - 2023

    Shenzhen, China

    AI Research Intern
    Tencent ARC Lab - Compatible Representation Learning
    Backward-compatible representation learning and model upgrades for large-scale image and video retrieval systems.
    • Four first-author papers (ICLR’22, IJCAI’22 long oral, AAAI’23, arXiv’23) defining the team’s backward-compatible retrieval line.
    • Multi-GPU contrastive / CLIP-style training pipelines with regression-alleviating methods enabling hot-refresh upgrades without re-encoding billion-scale galleries.
    • Winner of the Tencent Technology Breakthrough Award (2022).
  • 2019 - 2020

    Shenzhen, China

    AI Research Intern
    Tencent ARC Lab - Cross-Modality Video Understanding
    Multimodal models for video-text retrieval and temporal grounding on large-scale video-language datasets; built the PyTorch data / training / evaluation codebase for the group’s multi-modal research.

Education

  • 2023 - 2027

    Singapore

    Ph.D.
    National University of Singapore (NUS)
    Computer Science
    • Advisor - Asst. Prof. Mike Zheng Shou (Show Lab).
    • Research on LLM agents, vision-language, world models, and compatible representations.
  • 2019 - 2022

    Beijing, China

    M.Eng.
    Tsinghua University (THU)
    Computer Science and Technology
    • Advisor - Prof. Chun Yuan.
    • Focus on compatible representation learning and cross-modal video understanding.
    • Excellent Master’s Graduate in Beijing; Outstanding Master’s Thesis.
  • 2015 - 2019

    Shanghai, China

    B.Eng.
    East China University of Science and Technology (ECUST)
    Information Engineering
    • Cumulative rank 1 / 92.

Academic Interests

LLM Agents: agent harness, skill systems, long-horizon memory, tool use, multi-modal CoT, reflection-augmented RL, self-evolving training loops
Vision-Language and Video: multi-modal foundation models, video-text retrieval, temporal grounding, egocentric video understanding
World and Predictive Models: future prediction, hand-trajectory conditioning, latent diffusion, embodied planning
Lifelong and Compatible Representation Learning: backward-compatible retrieval, hot-refresh model upgrades, prototype replay, coarse-to-fine compatibility

Awards

  • 2022
    Tencent Technology Breakthrough Award
    Tencent

    For Hot-Refresh Model Upgrades.

  • 2022
    SZCCF Science and Technology Award
    Shenzhen CCF

    For efficient compatible model upgrades.

  • 2022
    Excellent Master Degree Graduate in Beijing & Outstanding Master's Thesis
    Beijing Municipal Education Commission / Tsinghua University
  • 2018
    Annual College Personage Award
    ECUST

    Highest student honor at ECUST.

  • 2017
    National Scholarship for Undergraduates (twice)
    Ministry of Education of China

    2016 and 2017.

Skills

Research Areas: LLM agents (harness / memory / tool use / RL), vision-language models, world and predictive models, video understanding, lifelong and compatible representation learning
Languages and Tools: Python (primary), C/C++, SQL, Bash, LaTeX
ML and Agent Stack: PyTorch, HuggingFace, DeepSpeed, vLLM, LangGraph / LangChain, MCP, CLIP, Latent Diffusion
Infra: distributed multi-GPU training, sandboxed code execution, large-scale training platforms

Academic Service

  • Reviewer: ECCV, ICCV, CVPR, ICLR, AAAI, IJCAI.