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SIGMOD

Hi, I'm Wenqian Zhang

Ph.D. Candidate @ UNSW | Accelerating Large-Scale Graph Computations

View Publications Download Resume
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Efficiency Gain

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Memory Reduction

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Students Taught

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Top-Tier Papers

Selected Projects

Billion-Scale Hypergraph Engine

C++ · Rust · Spark

High-performance in-memory engine for core decomposition on hypergraphs with 10^9+ hyperedges.

Distributed Graph Analytics

Kubernetes · Flink · Java

Cloud-native deployment of graph algorithms with auto-scaling and fault tolerance.

Research Focus

Core Decomposition

Scalable algorithms for k-core and nucleus decomposition in billion-scale graphs.

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Hypergraph Analytics

Efficient computation on high-order relational structures.

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Distributed Systems

Spark/Flink deployment, Kubernetes orchestration for graph workloads.

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Beyond Academia

☕

Coffee-powered debugging sessions

🎵

Lo-fi beats while writing papers

🎮

Strategic games enthusiast

✨

Open source contributor

Get in Touch

Interested in collaboration, research discussions, or just saying hi? I'd love to hear from you.

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About & Education

Sep 2025 - Present

Ph.D. in Computer Science

UNSW (University of New South Wales)

Topic: Efficient Algorithms for Large-scale Graph Analysis.

Faculty Scholarship, Top 2 Most Welcoming Demonstration
Sep 2023 - Aug 2025

MPhil in Computer Science

UNSW

Thesis: Scalable Core Decomposition in Large Networks.

Postdoctoral Writing Fellowship
Sep 2020 - Aug 2023

B.Sc. in Computer Science

UNSW

Graduated with Distinction.

Dean's List 2022

Publications

Accepted - SIGMOD 2025

Accelerating Core Decomposition in Billion-Scale Hypergraphs

First Author

Improved efficiency by 7x and reduced memory by 36x compared to state-of-the-art.

Published - ICDM Workshop 2023

Efficient Distributed Core Graph Decomposition

First Author

Optimized algorithms deployed on Spark/Flink via Kubernetes clusters.

Under Review - SIGMOD

Nucleus Decomposition Revisited: An Efficient Counting-Based Approach

Co-Author

Proposing a novel counting-based framework for dense subgraph discovery.

Technical Arsenal

Languages & Systems — emphasizing C++/Rust for low-level performance.

Languages

C++底层性能
95%
Rust底层性能
90%
Java
85%
Python
82%
SQL
88%

Systems & Tools

Apache SparkApache FlinkKubernetesDockerLinux

Teaching Experience

  • Database Systems (COMP3311/9311)Instructed 500+ students on SQL and Relational Algebra.
  • Data Analytics for Graphs (COMP9312)Taught advanced graph theory and algorithms.