AI/DS Discipline Courses

Date: 20/8/2017
Venue: Melbourne Convention and Exhibition Centre (Meeting room 103, MCEC)
Time: 8:00AM – 5:30PM

 20 Aug: AI/Data science Discipline Course (Meeting room 103, MCEC)
Time Talk Speaker
08:00-08:25 Registration
08:25-08:30 Opening Prof Longbing Cao
08:30-09:30 Managing the Internet of Things: Challenges, Activities, and Future Directions

Michael Sheng – ARC Future Fellow
Professor, Head of Department of Computing
Macquarie University, Australia

09:30-10:30 Computer vision meets machine learning

Dacheng Tao – ARC Laureate Fellow 
Professor of Computer Science, School of Information Technologies
University of Sydney, Australia

10:30-11:00 Morning Tea
11:00-12:00 Advances in machine learning

Qiang Yang – IEEE/AAAI Fellow 
Head of Department of Computer Science and Engineering
Hong Kong University of Science and Technology

12:00-13:00 Mathematical modeling & bitcoin blockchain

Peter Taylor – Australian Laureate Fellow 
Director, ARC Centre of Excellence for Mathematics and Statistics of Complex Systems
The University of Melbourne, Australia

13:00-14:00 Lunch Break
14:00-15:00 Advances in big graph/data processing

Xuemin Lin – IEEE Fellow
School of Computer Science and Engineering
The University of New South Wales

15:00-16:00 Ethics in artificial intelligence

Toby Walsh – Scientia Professor of AI
Group Leader, Data61
Professor, University of New South Wales, Australia

16:00-16:30 Afternoon Tea
16:30-17:30 Knowledge discovery & social analytics

Joao Gama – ACM Distinguish Speaker (2016-2019) 
Associate Professor, Laboratory of Artificial Intelligence and Decision Support
University of Porto Porto, Portugal

Who Should Participate:

  • HDR students
  • Early-career researchers in data science and AI
  • Early-career professionals in data science and AI
  • Researchers and developers
  • Data scientists
  • Data engineers
  • Executives and policy-makers


  • Seven carefully selected interdisciplinary discipline lectures on AI/DS latest advancements, and future scientific directions
  • Major topics: Data science, big data, mathematical modelling, artificial intelligence, machine learning, deep learning, data mining, computer vision, Internet/Web of Things, and AI ethics
  • Lecturers are all world-leading active professors in respective areas
  • Global perspectives about AI/DS disciplinary directions
  • The very frontiers and grand challenges of Artificial Intelligence 2.0
  • The very frontiers and grand challenges of Data Science
  • The first AI/DS discipline course series in the Oceania region

Tentative Program/Topics:

  • Trends and directions in data science
  • Advances and directions in artificial intelligence
  • Advances and directions in big data technologies
  • Advances and directions in mathematical modeling
  • Advances and directions in deep learning
  • Advances and directions in machine learning
  • Advances and directions in data mining
  • Advances and directions in computer vision
  • Advances and directions in Internet/Web of Things
  • Advances and directions in AI/data science ethics
Find more
Big Data Summit 2017