Yue Liu
PHD Candidate
Singapore
Summary
🤩
Rockstar🎓
Top SchoolYue Liu is a PhD candidate in Mechanical Engineering at the National University of Singapore with seven years of experience applying data and image analysis to scanning probe microscopy. Combining a strong mechanics background from Wuhan University and Dalian University of Technology with hands-on research at NUS Materials Lab, Yue bridges experimental microscopy and machine learning-driven analysis. He contributed to open-source deep graph clustering tooling—adding data loaders, graph normalization, diffusion utilities and CPU/GPU k-means—demonstrating practical skills in graph-based data processing. Past industry exposure includes an internship at Rolls-Royce analyzing electrical materials, underscoring his ability to translate academic methods to industrial problems. Colleagues describe him as a methodical researcher who seeks elegant computational solutions to noisy, microscopy-scale datasets.
7 years of coding experience
Master's degree, Engineering Mechanics, Master's degree, Engineering Mechanics at Dalian University of TechnologyBachelor's degree, Engineering Mechanics, Bachelor's degree, Engineering Mechanics at Wuhan UniversityDoctor of Philosophy - PhD, Mechanical Engineering, Doctor of Philosophy - PhD, Mechanical Engineering at National University of Singapore
Github Skills (14)
data-preprocessing10
data-loading10
graph-algorithms10
machine-learning10
dataprep10
preprocessing10
python10
clustering10
load-data10
preprocess10
numpy10
data-mining9
pytorch9
graph-neural-network8
Programming languages (2)
Github contributions (5)
yueliu1999/Awesome-Deep-Graph-Clustering
Nov 2021 - Jan 2023
Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).
Role in this project:
Data Scientist
Data ScientistContributions:11 reviews, 213 commits, 21 PRs in 1 year 1 month
Contributions summary:Yue primarily contributed to the data loading and processing aspects of the deep graph clustering project. Their commits focused on creating a data loading function (`load_data`), which includes detailed dataset information and also added utilities for constructing and normalizing graph data. They also added functions to compute graph similarity and graph diffusion to be used in the project. Furthermore, they added k-means clustering implementation with both cpu and gpu.
data-mining-algorithmsrepresentation-learningdata-mininggraph-clusteringgraphclustering
yueliu1999/Awesome-Jailbreak-on-LLMs
Jul 2024 - Apr 2025
Awesome-Jailbreak-on-LLMs is a collection of state-of-the-art, novel, exciting jailbreak methods on LLMs. It contains papers, codes, datasets, evaluations, and analyses.
Contributions:2 reviews, 21 PRs, 127 pushes in 8 months
aijailbreakllmllmsprivacy
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