The ability to quickly analyze and respond to newly arriving information is vital for ensuring that a city's systems remain efficient, sustainable, resilient, and secure. Our full-stack analytics team specializes in quickly analyzing complex data to meet this need. Our data often arrives at high velocity and volume from a variety of different sources, each with its different format and semantics, ranging from noisy numerical sensor readings to text, images, audio or video.
Our team collaborates with domain experts to create proofs of concept for solutions to real-world analytics problems. Each of our projects makes a research contribution in the application domain, and many also produce advances in the state of the art in data mining, machine learning, or the infrastructure that supports them. Our team members have expertise all along the analytics stack, from machine learning down to hardware acceleration.
CREATE Programme Project:
- Analytics for Detecting Power Grid Attacks, Professor Marianne Winslett and SUTD Professor David Yau
- Real-Time Analytics for Sports Video Streams, Professor Marianne Winslett (QNRF)
- Real Time Analysis of Soccer Video, Dr. Stefan Winkler and Dr. Tom Fu (SportSG)
- Unified Heterogeneous Resource Sharing Framework in HPC Clusters, Dr. Jiong He and Dr. Yao Chen (Alibaba Innovative Research)
- Data-Driven Modelling and Real Time Optimization for Diversified Chiller Plants, Dr. Zhenjie Zhang (BCA-NRF)
- Interpretable Transfer Learning over IoT Time Series for Predictive Maintenance, Prof. Marianne Winslett (SK Telecom)
- REVA: Real-time Elastic Video Analytics, Dr. Tom Fu (AWS SingAREN/AWS Cloud Credit for Research Program)
- Next-Generation Compilers and Architectures for Computation Acceleration with Energy Efficiency, Professor Deming Chen (A*STAR HSSP)
- Scalable, Real-time Analytics for Challenging Data, Professor Marianne Winslett (A*STAR HCCS)
- Enabling Medical Research with Differential Privacy, Professor Marianne Winslett (A*STAR SERC DVCaaS)