Hoang H. Nguyen

L3S Research Center

Room 005, Ground Floor

Appelstrasse 4

30167 Hannover, Germany

Hoang H. Nguyen (Eric Hoang) has joined the L3S Research Center of Leibniz University Hannover as a researcher and PhD candidate since February 2020. He was a visiting student and then a research associate at the School of Computing and Information Systems, Singapore Management University, from 2016 to 2018. In 2017, he received his Master of Engineering degree in Computer Science from Ho Chi Minh City University of Technology (HCMUT), Vietnam.

Nguyen has 10+ years of experience in Software Engineering and Graph Mining in the industry and academia. At L3S Research Center, he collaborates with researchers and law enforcement agencies (LEAs) from over fifteen countries and territories to develop new platforms to speed up investigative processes and support LEA decision-making. He also builds frameworks for storing and retrieving blockchain-powered social network data and detecting vulnerabilities in blockchain smart contracts.

His current research interests include Graph Mining, Machine Learning, Multimodal Network Analysis, Program Analysis, Software Security, and Blockchain Smart Contracts.

news

May 10, 2023	“Inductive and Transductive Link Prediction for Criminal Network Analysis” paper has been accepted for publication in the Journal of Computational Science.
Apr 28, 2023	“Multi-Vehicle Multi-Camera Tracking With Graph Based Tracklet Features” paper has been accepted for publication in the IEEE Transactions on Multimedia journal.
Mar 7, 2023	“MANDO-HGT: Heterogeneous Graph Transformers for Smart Contract Vulnerability Detection” paper is accepted at the MSR 2023 conference (Main Technical Track).
Feb 17, 2023	“Real-Time Multi-Vehicle Multi-Camera Tracking With Graph-Based Tracklet Features” paper has been accepted for publication in the Transportation Research Record journal.
Aug 23, 2022	“MANDO: Multi-Level Heterogeneous Graph Embeddings for Fine-Grained Detection of Smart Contract Vulnerabilities” paper is accepted at DSAA 2022 (Research Track).

selected publications

Inductive and Transductive Link Prediction for Criminal Network Analysis

Ahmadi, Zahra, Nguyen, Hoang H, Zhang, Zijian and 6 more authors

Journal of Computational Science 2023

Bib PDF

@article{ahmadi2023inductive,
  title = {Inductive and Transductive Link Prediction for Criminal Network Analysis},
  author = {Ahmadi, Zahra and Nguyen, Hoang H and Zhang, Zijian and Bozhkov, Dmytro and Kudenko, Daniel and Jofre, Maria and Calderoni, Francesco and Cohen, Noa and Solewicz, Yosef},
  journal = {Journal of Computational Science},
  volume = {},
  pages = {},
  year = {2023},
  publisher = {Elsevier},
  doi = {},
}

Multi-Vehicle Multi-Camera Tracking With Graph Based Tracklet Features

Nguyen, Tuan T., Nguyen, Hoang H., Sartipi, Mina and 1 more author

IEEE Transactions on Multimedia 2023

Bib PDF

@article{nguyen2023multi,
  title = {Multi-Vehicle Multi-Camera Tracking With Graph Based Tracklet Features},
  author = {Nguyen, Tuan T. and Nguyen, Hoang H. and Sartipi, Mina and Fisichella, Marco},
  journal = {IEEE Transactions on Multimedia},
  year = {2023},
  volume = {},
  number = {},
  publisher = {IEEE},
  pages = {1-13},
  doi = {10.1109/TMM.2023.3274369},
}

MANDO-HGT: Heterogeneous Graph Transformers for Smart Contract Vulnerability Detection

Nguyen, Hoang H., Nguyen, Nhat-Minh, Xie, Chunyao and 4 more authors

In Proceedings of the 20th International Conference on Mining Software Repositories May 2023

Bib PDF

@inproceedings{nguyen2023msr,
  author = {Nguyen, Hoang H. and Nguyen, Nhat-Minh and Xie, Chunyao and Ahmadi, Zahra and Kudenko, Daniel and Doan, Thanh-Nam and Jiang, Lingxiao},
  title = {MANDO-HGT: Heterogeneous Graph Transformers for Smart Contract Vulnerability Detection},
  year = {2023},
  month = may,
  doi = {},
  booktitle = {Proceedings of the 20th International Conference on Mining Software Repositories},
  numpages = {13},
  location = {Melbourne, Australia},
  series = {MSR '23},
}

MANDO-GURU: Vulnerability Detection for Smart Contract Source Code By Heterogeneous Graph Embeddings

Nguyen, Hoang H., Nguyen, Nhat-Minh, Doan, Hong-Phuc and 3 more authors

In Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering Nov 2022

Bib PDF

@inproceedings{nguyen2022fse,
  author = {Nguyen, Hoang H. and Nguyen, Nhat-Minh and Doan, Hong-Phuc and Ahmadi, Zahra and Doan, Thanh-Nam and Jiang, Lingxiao},
  title = {MANDO-GURU: Vulnerability Detection for Smart Contract Source Code By Heterogeneous Graph Embeddings},
  year = {2022},
  month = nov,
  isbn = {9781450394130},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/3540250.3558927},
  doi = {10.1145/3540250.3558927},
  booktitle = {Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering},
  pages = {1736-1740},
  numpages = {5},
  keywords = {Ethereum blockchain, graph neural networks, heterogeneous graphs, smart contracts, vulnerability detection},
  location = {Singapore, Singapore},
  series = {ESEC/FSE 2022},
}

MANDO: Multi-Level Heterogeneous Graph Embeddings for Fine-Grained Detection of Smart Contract Vulnerabilities

Nguyen, Hoang H., Nguyen, Nhat-Minh, Xie, Chunyao and 4 more authors

In Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics Oct 2022

Bib PDF

@inproceedings{nguyen2022dsaa,
  author = {Nguyen, Hoang H. and Nguyen, Nhat-Minh and Xie, Chunyao and Ahmadi, Zahra and Kudenko, Daniel and Doan, Thanh-Nam and Jiang, Lingxiao},
  title = {MANDO: Multi-Level Heterogeneous Graph Embeddings for Fine-Grained Detection of Smart Contract Vulnerabilities},
  year = {2022},
  month = oct,
  booktitle = {Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics},
  pages = {1-10},
  numpages = {10},
  keywords = {heterogeneous graphs, graph embedding, graph neural networks, vulnerability detection, smart contracts, Ethereum blockchain},
  location = {Shenzhen, China},
  doi = {10.1109/DSAA54385.2022.10032337},
  series = {DSAA '22},
}

SoChainDB: A Database for Storing and Retrieving Blockchain-Powered Social Network Data

Nguyen, Hoang H., Bozhkov, Dmytro, Ahmadi, Zahra and 2 more authors

In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval Jul 2022

Bib PDF

@inproceedings{nguyen2022sigir,
  author = {Nguyen, Hoang H. and Bozhkov, Dmytro and Ahmadi, Zahra and Nguyen, Nhat-Minh and Doan, Thanh-Nam},
  title = {SoChainDB: A Database for Storing and Retrieving Blockchain-Powered Social Network Data},
  year = {2022},
  month = jul,
  isbn = {9781450387323},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/3477495.3531735},
  doi = {10.1145/3477495.3531735},
  booktitle = {Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval},
  pages = {3036--3045},
  numpages = {10},
  keywords = {database, social networks, decentralized applications, datasets, decentralized social networks, blockchain, network analysis},
  location = {Madrid, Spain},
  series = {SIGIR '22},
}

API recommendation for event-driven Android application development

Yuan, Weizhao, Nguyen, Hoang H., Jiang, Lingxiao and 3 more authors

Information and Software Technology Jul 2019

Bib PDF

@article{yuan2019api,
  title = {API recommendation for event-driven Android application development},
  journal = {Information and Software Technology},
  volume = {107},
  pages = {30-47},
  year = {2019},
  issn = {0950-5849},
  doi = {https://doi.org/10.1016/j.infsof.2018.10.010},
  url = {https://www.sciencedirect.com/science/article/pii/S0950584918302222},
  author = {Yuan, Weizhao and Nguyen, Hoang H. and Jiang, Lingxiao and Chen, Yuting and Zhao, Jianjun and Yu, Haibo},
  keywords = {Android programming, Event callbacks, Code search, API recommendation, Information retrieval},
}