Fanchen Bu
Scholar

Fanchen Bu

Google Scholar ID: XjNu7-AAAAAJ
Ph.D. Student, KAIST
Graph miningGraph algorithmsCombinatorial optimizationGraph learning
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Citations & Impact
All-time
Citations
247
 
H-index
9
 
i10-index
8
 
Publications
20
 
Co-authors
35
list available
Contact
Emailboqvezen97@kaist.ac.krCVOpen ↗GitHubOpen ↗LinkedInOpen ↗
Publications
10 items
A Survey on Centrality and Importance Measures in Hypergraphs: Categorization and Empirical Insights
2025
Cited
0
HyperSearch: Prediction of New Hyperedges through Unconstrained yet Efficient Search
2025
Cited
0
Identifying Group Anchors in Real-World Group Interactions Under Label Scarcity
2025
Cited
0
On Training-Test (Mis)alignment in Unsupervised Combinatorial Optimization: Observation, Empirical Exploration, and Analysis
2025
Cited
0
Mitigating Over-Squashing in Graph Neural Networks by Spectrum-Preserving Sparsification
2025
Cited
0
TiGer: Self-Supervised Purification for Time-evolving Graphs
2025
Cited
0
DiffIM: Differentiable Influence Minimization with Surrogate Modeling and Continuous Relaxation
2025
Cited
0
On Measuring Unnoticeability of Graph Adversarial Attacks: Observations, New Measure, and Applications
2025
Cited
0
Resume (English only)
Academic Achievements
  • - [C20] Edge Probability Graph Models Beyond Edge Independency: Concepts, Analyses, and Algorithms
  • - [C19] Identifying Group Anchors in Real-World Group Interactions Under Label Scarcity
  • - [C18] HyperSearch: Prediction of New Hyperedges through Unconstrained yet Efficient Search
  • - [J5] Revisiting LightGCN: Unexpected Inflexibility, Inconsistency, and A Remedy Towards Improved Recommendation
  • - [W1] On Training-Test (Mis)alignment in Unsupervised Combinatorial Optimization: Observation, Empirical Exploration, and Analysis
  • - [C17] PyTorch-based Geometric Learning with Non-CUDA Processing Units: Experiences from Intel Gaudi-v2 HPUs
  • - [C16] RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmark
  • - [C15] Mitigating Over-Squashing in Graph Neural Networks by Spectrum-Preserving Sparsification
Research Experience
  • - Visiting Researcher: 2025.03 - 2025.06, CENTAI Institute, Host: Dr. Bonchi, Francesco, Collaborator: Dr. Miyauchi, Atsushi
  • - Research Assistant: 2021.09 - 2022.02, Korea Advanced Institute of Science and Technology (KAIST), Data Mining Lab, Supervisor: Prof. Shin, Kijung
Education
  • - Doctor: 2022.03 - Present, Korea Advanced Institute of Science and Technology (KAIST), Electrical Engineering, Supervisor: Prof. Shin, Kijung
  • - Master: 2019.09 - 2021.08, Korea Advanced Institute of Science and Technology (KAIST), Control Lab, Supervisor: Prof. Chang, Dong Eui, GPA: 4.21/4.3, Thesis: A Novel Optimization Algorithm with Orthogonality for Deep Neural Networks Inspired by Feedback Integrators
  • - Bachelor: 2015.09 - 2019.08, University of Chinese Academy of Sciences (UCAS), Computer Science and Technology, GPA: 3.71/4, Thesis: Vehicle Trajectory Prediction Based on Deep Learning (Supervisor: Prof. Zhao, Dongbin)
Background
  • Research interests: graph mining, graph algorithms, and combinatorial optimization. Background: PhD student in the Data Mining Lab at KAIST, under Prof. Shin, Kijung.
Miscellany
  • Personal interests: music, math, thinking, and exercise
Co-authors
35 total
Kijung Shin
Kijung Shin
Associate Professor, KAIST
Jaemin Yoo
Jaemin Yoo
Assistant Professor, KAIST
Soo Yong Lee
Soo Yong Lee
KAIST, Ph.D. Student
Sunwoo Kim
Sunwoo Kim
Ph.D Student at KAIST AI
Geon Lee
Geon Lee
KAIST AI
Hyeonsoo Jo
Hyeonsoo Jo
Ph.D student, Graduate School of AI, KAIST
Co-author 7
Co-author 7
Tina Eliassi-Rad
Tina Eliassi-Rad
Professor & The Inaugural Joseph E. Aoun Chair, Northeastern University