CV

Academic CV for Zerun Niu.

Contact Information

Name Zerun Niu
Email zerun.niu@sydney.edu.au

Experience

  • 2026 - present

    Sydney, Australia

    Casual Academic Tutor
    The University of Sydney
    Tutorial delivery and student learning support for university coursework.
    • Delivered weekly tutorials, class activities, small-group discussions, and Q&A on course content and university learning platforms.
    • Supported students in developing academic communication, teamwork, and professionalism skills through guided exercises and feedback.
    • Created an inclusive tutorial environment to help students transition into university study and participate confidently.
    • Coordinated with unit staff and followed teaching guides to run tutorials consistently and effectively.
  • 2024 - present

    Sydney, Australia

    Research Assistant
    DUAL Group, The University of Sydney
    Research engineering and experimentation for distributed learning and efficient AI systems.
    • Built reproducible training and evaluation pipelines with configs, seeds, logging, and automated reporting.
    • Supported submission and revision cycles by implementing baselines, targeted ablations, and publication-quality figures and tables.
    • Addressed reviewer feedback through additional experiments and clarity edits in method and experiment sections.
    • Coordinated experiment ownership, timelines, and artifact handoff across code, plots, and tables to reduce duplicated effort.
    • Designed and deployed the official DUAL Group website for members, publications, and research projects.

Summary

Education

  • 2025 - present

    Sydney, Australia

    Master of Philosophy
    The University of Sydney
    Computer Science
    • Supervisor: Nguyen Tran
    • Research focus: Federated Learning, Semantic Communication, and Efficient AI Systems
  • - 2025

    Sydney, Australia

    Bachelor of Advanced Computing
    The University of Sydney
    Data Science
    • Graduated with Distinction.
    • Final years WAM: 77/100
    • Relevant coursework: Machine Learning, Deep Learning, Natural Language Processing, Distributed Systems

Publications

Projects

  • Adaptive Low-Rank Optimization for Federated Learning

    Undergraduate thesis integrating DyLoRA into a federated learning pipeline.

    • Reduced communication cost by 80% without loss of accuracy.
    • Improved training stability across clients with reproducible PyTorch experiments.
    • Result: 85/100, High Distinction.
  • DUAL Group Website

    Designed and deployed the official website for the Distributed compUting, optimizAtion, and Learning group.

    • Introduced group members, publications, and research projects.
    • Website: https://dual-grp.github.io/website-dual/

Teaching

Skills

GenAI and Multimodal: LLM/VLM orchestration, agents, tool use, multimodal adapters, LoRA, alignment, safety guardrails, jailbreak defense, RAG, automated evaluation, and human-in-the-loop evaluation.
Efficient Tuning: LoRA, DyLoRA, PEFT workflows, quantization, distillation, and efficient adaptation under constrained compute budgets.
ML Engineering: PyTorch, Hugging Face Transformers, PEFT, scikit-learn, reproducible training pipelines, experiment tracking, modular pipeline design, and API development.
Distributed and Data Systems: Ray, Dask, Databricks, Spark, Hadoop, Airflow, FastAPI, latency and performance optimization, tracing, and observability.
Programming: Python, SQL, Java, C/C++, Git/GitHub, Linux, Jupyter, PostgreSQL, MySQL, MongoDB, Pandas, and NumPy.

Awards

  • 2025

    Adaptive Low-Rank Optimization for Federated Learning, score 85/100.