Pengtao Chen

Ph.D. Student

Embedded Deep Learning and Visual Analysis Lab
School of Information Science and Technology
Fudan University (FDU)

Address: 2005 Songhu Rd, Yangpu, Shanghai, China, 200438

E-mail: Pengt.Chen@gmail.com

Biography []

I received the B.S. degree from the School of Information Engineering, Zhejiang University of Technology, Hangzhou, China, in 2022, advised by Prof. Qi Xuan. I am currently a fitst-year Ph.D. student at the School of Information Science and Technology, Fudan University, Shanghai, China, supervised by Prof. Tao Chen. My current research interests include Computer Vision, Deep Learning, Model Compression and Model Design.

Publications [] [] [] []

(# Equal Contribution; * Corresponding Author.)

2022

TSGN: Transaction Subgraph Networks Assisting Phishing Detection in Ethereum.

Jinhuan Wang, Pengtao Chen, Xinyao Xu, Jiajing Wu, Meng Shen, Qi Xuan^*, Xiaoniu Yang.

Under review, 2022

(Phishing Identification) By introducing TSGN into multi-edge transaction networks, the proposed multi-TSGN model can reduce the time complexity of large-scale network modeling, retain real-time transaction flow information and capture important topological patterns of phishing scams.

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Preprint]

2021

Sampling Subgraph Network with Application to Graph Classification.

Jinhuan Wang, Pengtao Chen, Bin Ma, Jiajun zhou, Zhongyuan Ruan, Guanrong Chen, Qi Xuan^*.

IEEE Transactions on Network Science and Engineering(TNSE), 2021

(Data Augmentation) SGN model lacks diversity and is of quite high time complexity, making it difficult to widely apply in practice. In this paper, we introduce sampling strategies into SGN, and design a novel sampling subgraph network model, which is scale-controllable and of higher diversity.

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IEEE Link] [

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Broad Learning Based on Subgraph Networks for Graph Classification.

Jinhuan Wang, Pengtao Chen, Yunyi Xie, Yalu Shan, Qi Xuan^*, Guanrong Chen.

Graph Data Mining Algorithm, Security and Application, 2021

(Data Augmentation) A broad learning system (BLS) is introduced into graph classification, which fully utilizes the information provided by the S2GNs of different sampling strategies and thus can capture various aspects of the network structure more efficiently.

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Springer Link]

TSGN: Transaction Subgraph Networks for Identifying Ethereum Phishing Accounts.

Jinhuan Wang, Pengtao Chen, Shanqing Yu, Qi Xuan^*.

International Conference on Blockchain and Trustworthy Systems(BlockSys), 2021

(Phishing Identification) We build transaction networks (TN) to analyze illegal phenomenons such as phishing scams in blockchain from a network perspective. In this paper, we propose a Transaction SubGraph Network (TSGN) based classification model to identify phishing accounts in Ethereum.

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Springer Link]

Education

	School of Information Science and Techonlogy, Fudan University, Shanghai, P.R. China Ph. D., from Sep. 2022 (expected) Majored in Electronic Science and Technology.
	Jianxing Honors College, Zhejiang University of Technology, Hangzhou, P.R. China B. Eng., from Sep. 2018 to June 2022 Majored in Automation. Rank: 1/134 (less than 1%); GPA: 4.2/5.0.

Selected Honors and Awards

May 2022, Outstanding Graduate of Zhejiang Province.
Dec. 2021, Zhejiang Provincial Government Scholarship.
Dec. 2020, National Scholarship(The ONLY student in School of Information Engineering).
Oct. 2020, The 12th National College Student Mathematics Competition, Second Prize.
Oct. 2019, The 11th National College Student Mathematics Competition, First Prize.