基本信息
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职业迁徙
个人简介
Research Interests
I am interested in text mining, information retrieval, natural language processing and their application to software engineering and security. Here are a list of topics I am currently interested in or investigating:
Natural language and code representation: with the advent of Software 2.0, it is important to help software developers automating/semi-automating tasks to speed up their development process, e.g., code completion, community question answer ranking. I am interested in modeling the natural language and code data to help software engineers better accomplish their tasks: multi-modal NL-code representation, modeling NL-code mixed language sources (e.g., StackOverflow), cross-domain modeling and transfer for NL-code data, information retrieval for NL/code data [FSE 2018 workshop], pre-processing and tokenization for NL-code data.
Natural language understanding for security: Natural language is the main source for human to understand security and privacy operation. Natural language sources for security/privacy includes security warnings (e.g., Android permission warning [VL/HCC 2018]), vulnerability reports, software descriptions [RE 2018], privacy documents, etc. We can assist human to better understand security with the help of natural language techniques such as information extraction, reading comprehension, information retrieval, text generation, and text summarization. In particular, natural language sources in the security domain is highly domain-specific (e.g., the vocabulary for an IoT corpus would be strictly confined by the IoT operations available) and lacks labelled data. Therefore, it also critical to leverage label propagation, weak supervision, domain adaptation, or knowledge base approaches for these tasks.
I am interested in text mining, information retrieval, natural language processing and their application to software engineering and security. Here are a list of topics I am currently interested in or investigating:
Natural language and code representation: with the advent of Software 2.0, it is important to help software developers automating/semi-automating tasks to speed up their development process, e.g., code completion, community question answer ranking. I am interested in modeling the natural language and code data to help software engineers better accomplish their tasks: multi-modal NL-code representation, modeling NL-code mixed language sources (e.g., StackOverflow), cross-domain modeling and transfer for NL-code data, information retrieval for NL/code data [FSE 2018 workshop], pre-processing and tokenization for NL-code data.
Natural language understanding for security: Natural language is the main source for human to understand security and privacy operation. Natural language sources for security/privacy includes security warnings (e.g., Android permission warning [VL/HCC 2018]), vulnerability reports, software descriptions [RE 2018], privacy documents, etc. We can assist human to better understand security with the help of natural language techniques such as information extraction, reading comprehension, information retrieval, text generation, and text summarization. In particular, natural language sources in the security domain is highly domain-specific (e.g., the vocabulary for an IoT corpus would be strictly confined by the IoT operations available) and lacks labelled data. Therefore, it also critical to leverage label propagation, weak supervision, domain adaptation, or knowledge base approaches for these tasks.
研究兴趣
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Jiangrui Zheng,Xueqing Liu, Guanqun Yang, Mirazul Haque, Xing Qian,Ravishka Rathnasuriya,Wei Yang,Girish Budhrani
arxiv(2023)
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DEPLOYABLE MACHINE LEARNING FOR SECURITY DEFENSE, MLHAT 2021 (2021): 55-78
user-61442502e55422cecdaf6898(2019)
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2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)pp.323-325, (2018)
2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)pp.279-280, (2018)
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