Systems & Networking Research Projects
Multimodal AI × Sensors for Healthcare
Jingxian Wang’s lab develops multimodal AI with IoT sensors for healthcare applications. We explore non-invasive, everyday health diagnostics through intelligent sensing and AI. By integrating wireless, multimodal sensors with signal processing and machine learning, we build practical systems for early disease detection. Our approach emphasizes low-cost, continuous monitoring suitable for real-world deployment and daily use. This work is partially funded by Microsoft’s Accelerate Foundation Models Research Program.
- Mobile Computing & Sensing
AI for Space Networks; and Space Networks for AI
Jingxian Wang’s lab explores the intersection of AI with networks and systems in space. As mega-constellations (e.g., Starlink) scale rapidly, there’s surging demand for groundbreaking solutions that keep pace with exploding traffic and emerging services in low-Earth orbit. A recent example is SATE from the lab, published at ACM SIGCOMM 2025—an AI-accelerated traffic-engineering system that learns to produce near-optimal solutions in milliseconds for thousand-satellite constellations, delivering orders-of-magnitude speedups over classical solvers and higher throughput.
- Computer Networks
Enhancing Legal Document Services with Accessible and Private LLM Technology
This research focuses on developing a local, privacy-preserving Large Language Model (LLM) for legal document services. By eliminating reliance on external servers, the proposed solution enhances user privacy, efficiency, and reliability. The study addresses challenges related to memory and computational constraints through optimisations, aiming to provide accessible and secure document processing.
Operating System Support for Large Memory Systems
This project tackles performance limitations in large server systems with extensive memory. It proposes OS-level solutions to optimize memory access for both traditional Non-Uniform Memory Access (NUMA) systems and emerging disaggregated memory architectures. The goal is to improve performance, power efficiency, and cost-effectiveness for data centers.
Towards a Testbed for Innovative Inter-Networking Research
This project aims to achieve performance-guaranteed stream processing using a serverless paradigm. By designing Stream as a Service (SaaS) abstractions and APIs, users can specify computational logic and performance goals for their stream jobs, advancing serverless technology for real-time analytics with a broader impact.
Tackling Energy-Efficient Reception Challenge for Next Billion IoT Devices
The proposal addresses the energy challenge in IoT by designing energy-efficient receivers with tunnel diodes and LiFi or visible light communication, to enable sustainable, battery-free IoT devices.
Research Programme in Assuring Hardware Security by Design in Systems on Chip (SOCure)
NUS-NCS Joint Laboratory
NCS Pte. Ltd. (NCS) and the National University of Singapore (NUS) have established a joint research lab that is hosted in NUS to conduct research, develop capabilities and innovative digital solutions to protect individuals, businesses and public agencies in Singapore from a wide range of cyber threats. The joint lab is governed by a Management Committee comprising members from NUS and NCS.
Record & Replay: Framework for Network-wide Monitoring and Debugging
- Computer Networks, Programmable Networks
In-Network Acceleration for Latency Sensitive Applications for Future Communication Systems
- Computer Networks, Wireless Networks