Industry Session at ADMA’17

Towards our objective of bridging the data science communities in academia and industry, SIGKDD Singapore and ADMA2017 jointly organized the Industry Session in the Advanced Data Mining and Applications 2017 conference (ADMA’17), which took place on Nov 6, 2017 in NTU Alumni House at Marina Square.

The session featured the following talks by five accomplished professionals at the forefront of data science developments in Singapore.

Data Mining-based Cost Optimisation for Electricity Retailers
by Dr Phua Chun Wei Clifton, Director of Analytics, NCS Group

Advancing Ensembles for Population Data Mining
by Dr Graham Williams, Director of Data Science Asia/Pacific, Microsoft

Personalised News and Video Recommendation System at LinkSure
by Dr Rubing Duan, Director of Big Data Department, LinkSure

Innovation Opportunities in the Logistics Industry
by Timothy Kooi, Innovation Leader, DHL’s Innovation Center

AI in Healthcare – Opportunities and Challenges from a Health System’s Perspective
by Sijia Wang, Team Lead from Health Insights Department, Integrated Health Information Systems (IHiS)

We thank all the speakers for the informative and insightful talks.


Dr Clifton Phua on Data Mining-based Cost Optimization for Electricity Retailers


Dr Graham Williams on Advancing Ensembles for Population Data Mining


Sijia Wang on AI in Healthcare


Inaugural Tutorial Attended by 120

The first KDD.SG tutorial jointly organized by SIGKDD Singapore and MAS was successfully held on September 14, 2017 at the MAS Theatrette.

We extend our special thanks to the tutorial speaker, Dr. Graham Williams, who delivered an informative hands-on session on machine learning with R.

The event could not have happened without the generous support by the MAS team, namely: Zhi Rong Chng, Su Fen Lee, and David Hardoon.

We are particularly grateful for the strong support from the community.  120 attendees came from various organizations in Singapore, including the universities (e.g., NUS, NTU, SMU), government agencies (e.g., MAS), as well as companies (e.g., KPMG, SingTel, UOB, PwC, DHL, DBS, SAS).

We look forward to organizing more events and activities towards building a stronger data science community in Singapore.


Dr. Graham Williams (Director of Data Science, Microsoft Asia, Singapore) delivered the tutorial on Machine Learning in R


Dr. Hady Lauw (Chair) introduced the Singapore ACM SIGKDD Chapter


Tutorial attendees in the MAS Theatrette


Inaugural KDD.SG Tutorial Jointly Organized with MAS

Download the flyer for this tutorial and share it with your friends!

Hands-On Machine Learning in R – Getting Started

September 14, 2017 | 6pm to 8.30pm | MAS Building

Graham Williams

Director of Data Science, Microsoft Asia, Singapore
Graham joined Microsoft recently after over 30 years as researcher, developer and educator in Artificial Intelligence, Machine Learning, Data Mining, Analytics and Data Science. He was previously lead Data Scientist for the Australian Government’s Center of Excellence in Data Analytics, Director of Data Science at the Australian Taxation Office, and Principal Research Scientist with CSIRO Australia. Over those 30 years he has also been an active contributor to the Open Source ecosystem with open source software projects across Emacs, Linux, Data Science, and R. Graham has authored many books, papers, Internet resources and software packages for data scientists. His latest book released in July 2017 introduces the Essentials of Data Science through a programming-by-example based approach to knowledge discovery in R. He maintains an extensive collection of R and Data Science resources on


Machine learning underlies much of today’s technological advances driving enterprises who are embracing data and information to become knowledge-driven organisations. R is a popular ecosystem for Knowledge Discovery, Machine Learning and Data Science. It has grown over the past 20 years from a specialist tool for a handful of statisticians to an estimated 4 million users today. It provides a platform for building and deploying machine learning based models.  This tutorial will introduce, with a hands-on focus, the R ecosystem for Machine Learning and Artificial Intelligence. We will understand some of the most widely used machine learning algorithms, including decision trees, and explore how we build models R. The concepts of ensembles will also be introduced as the state-of-the-art classification learner. The tutorial will focus on hands-on learning so that all attendees will gain the experience to then continue with building such models on their own. A particular focus is on the use of readily repeatable template scripts for our tasks.


Date/Time Thursday 14 September 2017, beginning with a light reception at 6pm

Venue MAS Theatrette, Level 16, Looking Glass, Level 11, MAS Building, 10 Shenton Way, Singapore 079117

RSVP on Provide the info for entry into the venue. Due to limited capacity, we will send you a confirmation email if your registration is accepted.  Attendance will be recorded.

Preparation Bring your own laptop with your own internet connectivity (or Wireless@SG available on-site) for use of the X2Go application which you should also install. If you have no network connectivity then be sure to install R and Rattle and related packages prior to the session.

Call for Tutorials Interested in conducting your own tutorial?  Also check out our Call for Tutorials!