About Yong-Bin Kang

Welcome to Yong-Bin Kang’s homepage! I am a senior data science research fellow for the Centre of Excellence for Automated Decision Making and Society (ADM+S) at Swinburne University, Australia. Since June 2018, I have been now employed as a senior research fellow at Swinburne, helping lead/co-lead industry and government funded research projects in the areas of natural language processing (NLP), machine learning (ML), and data mining (DM).

I am an intellectually curious and analytical data scientist with the ability to systematically conceptualise problems and discover hidden insights from real-life problems by using quantitative and qualitative data analysis techniques. My research expertise and interests are mainly in the fields of NLP, ML, and DM. I have experience in working, managing and delivering large industrial, multi-disciplinary research projects in data science such as patent analytics, clinical data analytics, scientific-article analytics, social-media data analytics, expert finding and matching, and machine learning algorithms and applications.

I have recently developed an NLP based technological trajectory for patent examination process in IP Australia during 2018 - 2020. As a computer scientist, I completed my PhD (Monash University, 2011) and was a core member of Swinburne’s Data Science Research Institute at Swinburne during 2018 - 2020. My research outcomes have been demonstrated by publications in Information Systems journal, WIREs data mining and knowledge discovery, JMIR public health and surveillance, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Cybernetics. Some representative conference papers A/A* include AAAI, ECAI, ISWC, CIKM, K-CAP, and ACL.

I have also experience teaching bachelors and master courses in the capacity of a lecturer and tutor in Faculty of IT at Monash University during 2014 - 2018. My teachings were focused on the areas of data science such as natural language processing, machine learning, and data mining and big data processing.

Education

• PhD. Faculty of Information Technology (2011)
  • Monash University
  • Thesis: USIMSCAR: A Retrieval Strategy for Case-based Reasoning using a Combination of Similarity and Association Knowledge
• MS. Computer Science and Engineering, Department of Computer Science (1998)
  • Pusan National University
  • Thesis: Character Grouping Technique Using 3-D Neighbourhood Graphs in Raster Map

Recent Funding

• 2022: Chief Investigator
  • An AI governance framework for garbage truck-mounted machine vision systems; A new research project in ARC Centre of Exellence for Automated Decision-Making and Society (ADM+S)
• 2021: Chief Investigator
  • Research and Development of a Solution for Question/Answer Generation and Assessment from Video using Natural Language Processing; VidVersity
• 2020: Chief Investigator
  • Development of Proof-of-Concept AI-based solution for SoA (Statement of Advice) Assessment; Fourth Line
• 2018: Chief Investigator
  • Development of a deep-learning based solution for detecting corrosion in industrial assets using images captured from drones; Funded by Robonomics AI

Work Experience

• Senior Research Fellow
  • Centre of Excellence for Automated Decision Making and Society (ADM+S), Swinburne University (2020 - Present)
• Senior Research Fellow
  • Data Science Research Institute, Swinburne University of Technology (2018 - 2020)
• Research Fellow
  • Faculty of Information Technology (FIT), Monash University (2011 - 2018)
• Senior Researcher (2006 - 2007)
  • Institute for Graphic Interfaces (IGI), Korea
• Researcher
  • Electronics and Telecommunications Research Institute (ETRI), Korea (2004 - 2006)