Singapore Machine Learning & Data Science Summit – Recap

This post is authored by Tamarai G V, Senior Product Marketing Manager at Microsoft.

Singapore has started to embrace the many benefits of digital transformation, and data plays a central role in this process. From using non-traditional indicators such as electricity consumption and public transportation to monitor the economy to helping the government improve the lives of ordinary citizens, machine learning and data science are being put to use to solve real world problems.

As part of Singapore’s digital efforts, and to nurture a vibrant ML and data science community, the inaugural Machine Learning and Data Science Summit in Asia was held in Singapore on Dec 9th, 2016, at the beautiful University Town in the National University of Singapore (NUS).

The event was jointly organized by the Government Technology Agency of Singapore (GovTech); Residential College 4, NUS; and Microsoft; and attended by hundreds of data scientists, developers, students and faculty. The full day summit had an exciting agenda, with keynotes, breakout sessions and hands-on labs helping attendees learn how to tap the power of Cortana Intelligence, Microsoft R Server and SQL Server R Services to build intelligent applications. There were sessions on building intelligent bots, demystifying deep learning, understanding how the Team Data Science Process can help jump-start successful data science teams and many more.


The summit kicked off with keynote sessions by Jessica Tan, Managing Director for Microsoft Singapore, Chan Cheow Hoe, Government CIO at GovTech, and Professor Lakshminarayanan of NUS. Jessica highlighted the new possibilities of digital transformation and the need to approach data sciences as a team sport.


Chan Cheow Hoe spoke about the use of Data Science in the Public Sector, and how a data-driven approach has solved real world problems in Singapore, such as the recent Circle Line incidents. He also shared how data science can be harnessed to derive deep insights from data to inform policy changes and reviews, and to improve operations and service delivery through applications and data visualisation.


Finally, Professor Lakshminarayanan (from Residential College 4, NUS) welcomed the attendees to University Town, and shared the work that college is doing on systems thinking and design, and how it is relevant to the data science community.


Hongyi Li, Product & Engineering lead at GovTech, presented on how the organisation is working on using data for the public good and how open data can help citizens understand and use data through the data.gov.sg portal. He also shared how the team wants to help government agencies establish a common data sharing infrastructure and make it accessible to use for decision making.


Other sessions that followed included topics on adopting a system thinking towards data science by Wee Hyong Tok and Jenson Goh (from NUS); Matt Winkler and Jennifer Marsman who shared how one can bring intelligence into applications using Cognitive Services and Cortana Intelligence Suite; and Anusua Trivedi who demystified deep learning and shared the exciting applications that can be built in this area.

A key highlight of the event was the Hackathon, led by Hang Zhang, where participants from across academia and industry pitted their skills against the best in ML and data science. Hackathon participants tackled the problem of predicting the number of fatalities in traffic accidents in which drunk drivers had an impact on the outcome. Using the Cortana Intelligence Competition Platform, participants came up with many creative ways of building and improving on their solutions, and worked away to get on the leaderboard.


The Summit concluded with a closing address by Vijay Narayanan, Director of Data Sciences at Microsoft, and an awards ceremony recognizing the hackathon winners.


It was great to see the winners being offered internship opportunities by different organizations at the conclusion of the event!

We look forward to the next Data Science Summit in 2017.

Tamarai