基本信息
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职业迁徙
个人简介
Dr Wei Kang is currently a Research Scientist at Data61, CSIRO. Prior to that, he was a Research Fellow and Research Degree Supervisor at the School of ITMS, University of South Australia (UniSA), and also a Research & Data Scientist at the Data to Decisions Cooperative Research Centre (D2D CRC). He obtained his PhD in Computer Science from National University of Singapore in 2015.
Wei was a key research and data scientist in the project of Beat the News collaborated between UniSA and D2D CRC. Aimed at providing national security agencies with a capability for continuous, automated analysis of publicly available data, Wei focuses on detecting and predicting anomalies from big/complex data, such as socially disruptive events, and performing risk analysis to prevent potential danger and loss. Wei’s work mainly focuses on the following aspects in this project:
• Understand and assess the requirements of stakeholders, translate real-world / business challenges to analytical problems
• Build novel models using data mining and machine learning techniques to make predictions based on historical event data and other open source data such as news reports, tweets and Facebook newsfeeds
• Explore new features to improve these models and integrate them in a system.
• Evaluate and improve the performance of the models
• Perform risk analysis for events of interest in specific contexts in social media
• Utilize various systems and tools, e.g. Apache Spark, Jupyter, GitHub, Bitbucket, Confluence, Jira, Kanban, AWS, Ansible, etc.
Wei was a key research and data scientist in the project of Beat the News collaborated between UniSA and D2D CRC. Aimed at providing national security agencies with a capability for continuous, automated analysis of publicly available data, Wei focuses on detecting and predicting anomalies from big/complex data, such as socially disruptive events, and performing risk analysis to prevent potential danger and loss. Wei’s work mainly focuses on the following aspects in this project:
• Understand and assess the requirements of stakeholders, translate real-world / business challenges to analytical problems
• Build novel models using data mining and machine learning techniques to make predictions based on historical event data and other open source data such as news reports, tweets and Facebook newsfeeds
• Explore new features to improve these models and integrate them in a system.
• Evaluate and improve the performance of the models
• Perform risk analysis for events of interest in specific contexts in social media
• Utilize various systems and tools, e.g. Apache Spark, Jupyter, GitHub, Bitbucket, Confluence, Jira, Kanban, AWS, Ansible, etc.
研究兴趣
论文共 17 篇作者统计合作学者相似作者
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KNOWLEDGE-BASED SYSTEMS (2024)
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2024): 455-468
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