The SDSC is envisioned as a platform on which industry consortium members can engage public research performers with the objectives of partnership on innovative data science projects. It will train and synergise manpower in data science, collate accurate and valuable data for research and innovation purposes, create solutions to support companies and help to achieve Singapore’s goal of becoming a Smart Nation. Click on the projects below to find out more about our completed and ongoing data science projects!
DATA SCIENCE PROJECTS
Corporate IT Solutions and NUS to Develop and Design a Dynamic Recommender System for Exhibition Industry
LumiHealth and A*STAR Collaborate to Better Serve Citizens’ Health and Wellness Needs through the LumiHealth Programme
Mercurics and SMU Applying Data Science of Collected Sensor Data to Identify Barrier-free Access Paths for Wheelchair Users
SKH, SMU and NUS Collaborate to Study Sensor-obtained Data for Early Detection of Cognitive Decline
SDSC Develops a Deep Learning and Computer Vision-based Method to Monitor Social Distancing in Real Time
SKH and SMU Uses Smart Sensors to Test Seniors’ Cognitive Functions
UOB and NUS to Collaborate on Company Profiling Project
Certis, NUS and SDSC to Detect Anomalous Behaviour in Access Log Using Machine Learning and AI Techniques
EZ-Link and IDS Jointly Developing Data Analytics Applications for Fraud Detection and Customer Persona Development
Jurong Port and NUS to Develop the Next Generation Multipurpose Port
SMU and NTUC Health Co-operative Ltd (NHCL) Jointly Develop Smart Tech Attendance and Home Visit Recording System
MEIYUME and NUS Jointly Develop a Smart Beauty Trend Engine for Beauty Product Trend Analysis
K&S and IORA Update Manufacturing Operations to Achieve the Visions Broadly Defined in Industry 4.0
GSK and NUS to Drive Better Efficiencies Using Predictive Modeling
National Gallery and IDS to Develop Intelligent GalleryBot Using NLP
UOB and NUS Leverage Data Analytics to Understand Consumers’ Needs
Surbana Jurong and IDS Apply AI Techniques to Categorize Residents’ Textual Feedback
Trampolene and SMU Apply Data Science to Identify Barrier-Free Routes for Wheelchair Users
DSTA and IDS Collaborate to Design the Next Generation of Intelligent Risk Management System