David Hason Rudd

David Hason Rudd is a PhD research engineer, subject coordinator and lecturer at the faculty of engineering and information technology (FEIT) at the University of Technology Sydney (UTS). His expertise, experience, and collaborative spirit make him an invaluable asset to the global research and data science community. He also collaborates with the data science & machine intelligence lab (dsmi.tech) and has done several industrial research projects. In addition to his research at UTS, he serves as the lead data scientist at BayesianConsulting.com.au in Sydney, where he has consulted for clients in the banking, telecommunications, and investment industries.

His research interests include data analytics, smart sensing & technology 4.0, machine learning signal processing, organizational member engagement, financial X-Ray and causal analysis of customer churn. His commitment to advancing the field of data science is evident in his extensive publication history, which covers a wide range of topics in machine learning, artificial intelligence, and data analytics in highly recognized journals and conference proceedings. Besides, he is a PC member at multiple international conferences. He is a CA lecturer, tutor, and supervisor for subjects including 42050 SAS Predictive Business Analytics, 41030 Engineering Capstone Supervisor, 41029 Engineering Research Preparation, and 41004 AI/Analytics Capstone Project.
In the industrial section, he is a qualified professional engineer awarded by Engineers Australia (m. #8385590), Industrial Engineers Australia (GradIIEA #4473294), and a Registered building practitioner - electrical design (medium rise Lic. # 0-10-530-01580). He has over 17 years of multidisciplinary engineering experience, spanning four countries and fields including electrical, telecommunications, engineering management, and data analytics. This diversified perspective not only allows him to establish rapport with students from various academic areas and assist them accordingly, but he is also known for his strong analytical skills, problem-solving abilities, and dedication to advancing the field of data science.

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