This paper aims to improve the energy efficiency of LoRa by enabling LoRa nodes to operate in a downclocked ‘light sleep’ mode for packet reception.

This paper aims to improve the energy efficiency of LoRa by enabling LoRa nodes to operate in a downclocked ‘light sleep’ mode for packet reception.

This project presents a novel communication paradigm that enables parallel demodulation of colliding LoRa transmissions.

In this project, we propose a new power-saving strategy for screen-off Wi-Fi communications.

In this work, we design a simple yet effective error recovery code that uses XOR code to minimize delay and uses RSSI-hinted approach to detect in-packet corruptions without CRC.

This project proposes a novel sender impact metric which jointly exploits link quality and spatial link diversity to calculate the gain/cost ratio of the sender candidates.

We propose ReLog which consists of a programming language, a compiler, and a virtual machine to support reprogramming in wireless sensor networks.

This paper aims to improve the energy efficiency of LoRa by enabling LoRa nodes to operate in a downclocked ‘light sleep’ mode for packet reception.

This project presents MDLdroidLite, our latest on-device deep learning framework to support privacy-preserving personal mobile sensing applications.

Our first version of a novel decentralized mobile deep learning framework to enable resource-aware on-device collaborative learning for personal mobile sensing applications.

This paper aims to improve the energy efficiency of LoRa by enabling LoRa nodes to operate in a downclocked ‘light sleep’ mode for packet reception.

In this project, we present an indoor localization system using magnetometer on smartphone.

In this project, we present a novel infrastructure-free localization system to locate mobile users in a metro line.

We present FTrack a novel floor localization system leveraging on smartphone’s accelerometer only, and it does not require any prior knowledge of a building such as floor height.

This project presents an in-air writing gesture recognition system using a wrist-worn device.

In this project, we present a novel gesture input technique for off-the-shelf smartwatches.

In this project, we present the design of SpiderWalk on smartphones to detect transportation activity.

This project presents a system to detect human respiration using Wi-Fi devices.

In this work, we propose a system using low-cost RFID tags, which enables device-free, unobtrusive monitoring of elderly people by leveraging machine learning algorithms and the Internet of Things (IoT) technology.

This paper aims to improve the energy efficiency of LoRa by enabling LoRa nodes to operate in a downclocked ‘light sleep’ mode for packet reception.

This project aims to investigate the fundamental problem of recognizing activities of multiple users using wearable sensors in a home environment.

In this project, we develop a wearable system to recognize simple (i.e., sequential) and complex (i.e., interleaved and concurrent) activities in real life.

This project proposes the design of a smart neckband device for smoking detection.

In this project, we propose a novel computation framework to recognize gait patterns in patients with PD.

In this project, we use a large real-world dataset with on-street parking sensor data from Melbourne City Council and establish a formulation of the travelling officer problem with a probability-based model.

In this project, we aim to predict “serendipitous” social interactions.

In this project, we aim to predict “serendipitous” social interactions.

This project explores how to reduce the inter-server communications leveraging on Online Social Networks (OSNs).