Hey, I'm Fanseu Kamhoua Barakeel

A Computer Science and Engineering PhD student at HKUST.

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Who I am

I am a Christian Cameroonian. I am a curent Computer Science and Engineering (CSE) student at the Hong Kong University of Science and Technology (HKUST) under Professor Huamin QU, starting August 2023. I hold a Master of Science in Industrial Engineering from HKUST, and a Batchelor of Technology in this same discipline from Nelson Mandela University (NMU).

I have three years of research experience as a Research Assistant from the Chinese University of Hong Kong (CUHK) under professor James CHENG. I equally have industrial experience as a Software Engingeer specializing in R&D for algorithm developement and deployment in image processing for real-time embedded systems at Meridian Innovation (at HKSTP). When I’m not programming, reading papers, or trying to find a new idea, I love hanging out with peers, family, and freinds.

Publication list below, each with code available either on my GitHub or websites accessed by clicking the GitHub icon. Please feel free to use or build on any of my work, and please cite if used. Also reach out if you have any questions or suggestions!

What I do

I am pursuing a PhD in Computer Science and Engineering (CSE), with a focus on Data Visualization, Pattern Discovery, Artificial Intelligence, and Machine Learning.

My research interests span graph neural networks, graph matching, shape correspondence, and unsupervised learning methods. I am particularly interested in discovering patterns in complex structured data and developing algorithms that can learn effectively with limited labeled information.

Publications

NEXUS: Neighborhood-Enhanced Correspondence Optimization Strategy for Shape Correspondences

NEXUS: Neighborhood-Enhanced Correspondence Optimization Strategy for Shape Correspondences

Barakeel Fanseu Kamhoua, Kento Shigyo, Huamin Qu

Under Major Revision

Sparse Labels Node Classification: Unsupervised Learning for Mentoring Supervised Learning in Sparse Label Settings

Sparse Labels Node Classification: Unsupervised Learning for Mentoring Supervised Learning in Sparse Label Settings

Barakeel Fanseu Kamhoua, Lin Zhang, Yongqiang Chen, Tongliang Liu, Huamin Qu, Bo Han

Revised and Resubmitted (Journal)

HOPE: Shape Matching Via Aligning Different K-hop Neighbourhoods

HOPE: Shape Matching Via Aligning Different K-hop Neighbourhoods

Barakeel Fanseu Kamhoua, Huamin Qu

Published at NeurIPS 2024

GRACE: A General Graph Convolution Framework for Attributed Graph Clustering

GRACE: A General Graph Convolution Framework for Attributed Graph Clustering

Barakeel Fanseu Kamhoua, Lin Zhang, Kaili Ma, James Cheng, Bo Li, Bo Han

Published at ACM TKDD 2023

Exact Shape Correspondence via 2D graph convolution

Exact Shape Correspondence via 2D graph convolution

Barakeel Fanseu Kamhoua, Lin Zhang, Yongqiang Chen, Han Yang, MA Kaili, Bo Han, Bo Li, James Cheng

Published at NeurIPS 2022

Hypergraph Convolution Based Attributed Hypergraph Clustering

Hypergraph Convolution Based Attributed Hypergraph Clustering

Barakeel Fanseu Kamhoua, Lin Zhang, Kaili Ma, James Cheng, Bo Li, Bo Han

Published at CIKM 2021

Improving Graph Representation Learning by Contrastive Regularization

Improving Graph Representation Learning by Contrastive Regularization

Kaili Ma, Haochen Yang, Han Yang, Tatiana Jin, Pengfei Chen, Yongqiang Chen, Barakeel Fanseu Kamhoua, James Cheng

arXiv 2021

Understanding Graph Neural Networks from Graph Signal Denoising Perspectives

Understanding Graph Neural Networks from Graph Signal Denoising Perspectives

Guoji Fu, Yifan Hou, Jian Zhang, Kaili Ma, Barakeel Fanseu Kamhoua, James Cheng

arXiv 2020

Get in touch

Coffee Chat! Please do not hesitate to schedule a meeting. Alternatively, feel free to reach out directly by email at bfk@connect.ust.hk.

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