Lingwei Chen, Ph.D.
Department of CSE
Wright State University
I am currently a tenure-track Assistant Professor in the Department of Computer Science and Engineering at Wright State University. Prior to that, I worked as a Postdoctoral Scholar in the College of Information Sciences and Technology at the Pennsylvania State University. I received my Ph.D. degree in Computer Science from West Virginia University advised by Prof. Yanfang (Fanny) Ye (moved to University of Notre Dame already), and my master's degree in Computer Science from Beijing Normal University.
My research interests are machine learning and data mining, with emphases in:
Trustworthy machine learning: adversary for social good, adversarial attacks and defenses, model explanations, and other trustworthy issues
Machine learning applications: code summarization/retrieval, security attack detections (e.g., fraud, bot, malware, vulnerability, etc.), social network analysis, and other applications by designing GNN/NLP models to address different learning issues, such as few-shot, data imbalance, and graph heterophily
For my publications and bibliometrics, please refer to Publications and Google Scholar.
Openings: I am looking for self-motivated Ph.D. students to work with me on various cool projects in machine learning and data mining. Please drop me an email with your CV if interested.
NEW [Oct 2023] A paper about fooling AI explanations was accepted to EMNLP 2023.
NEW [Sep 2023] A paper about vulnerability detection was accepted to ESWA 2023.
NEW [Sep 2023] A paper about few-shot node classification was accepted to ICDM 2023.
[Aug 2023] A paper about class-imbalanced bot detection was accepted to CIKM 2023.
[Jul 2023] A paper about adversary for social good was accepted to TKDD 2023.
[Mar 2023] My CRII proposal "CRII: SaTC: Towards Data-effective and Cost-efficient Security Attack Detections" was funded by NSF. Thank you, NSF!
[Mar 2023] A paper about cross-modal adversarial reprogramming was accepted to WWW 2023.
[Feb 2023] A paper about hierarchical GNN was accepted to PAKDD 2023.
[Dec 2022] A paper about code summarization was accepted to ECIR 2023.
[Oct 2022] Attended DARPA Forward Conference as DARPA Riser for proposal presentation.
[Jul 2022] Our propoed project "Artificial-Intelligence-Driven Binary-to-Source-Code Function Search" was funded by TRC/NHTSA.
[Jun 2022] A paper about adversarial attack on GNN was accepted to SecureComm 2022.
[Jun 2022] A paper about reinforcement compiler fuzzing was accepted to ICICS 2022.
[May 2022] Selected as DARPA Riser for DARPA Forward Conference.
[Apr 2022] A paper about code summarization was accepted to IJCNN 2022.
[Apr 2022] A paper about smart contract similarity detection was accepted to SEKE 2022.
[Mar 2022] A paper about few-shot attribute inference was accepted to SIGIR 2022.
[Dec 2021] A paper about adversarially reprogramming pretrained neural networks for malware detection was accepted to SDM 2022.
[Nov 2021] A paper about compiler fuzzing was accepted to IAAI 2022.
[Aug 2021] A paper about fraud detection was accepted to CIKM 2021.
[Aug 2021] Joined the Department of Computer Science and Engineering at Wright State University as an assistant professor.
[Apr 2021] A paper about defense against adversarial attacks was accepted to IJCNN 2021.
[Dec 2020] A paper about turning adversarial attacks into social media privacy protection was accepted to SDM 2021.
[Jul 2020] A paper "Plagiarism Detection of Multi-threaded Programs using Frequent Behavioral Pattern Mining" received SEKE 2020 Best Paper Award.
[Jun 2020] A paper about enhancing robustness of graph convolutional networks was accepted to ECML-PKDD 2020.
[Apr 2020] Two papers about multi-threaded program plagiarism detection and compiler identification respectively were accepted to SEKE 2020.
[Mar 2020] Our proposed project "Turning Attacks into Protection: Social Media Privacy Protection Using Adversarial Attacks" was funded by Seed Grant Award from Center for Security Research and Education (CSRE) at the Pennsylvania State University.