A human protein “interleukin-2” plays a key role in immunity. The target of this project is to modify this protein, triggering more immune cells in body, and hence enhancing body defense. At first, the intern will produce normal interleukin-2 in bacteria. The protein will then be mixed with the immune cells. Increase in cell amount indicates the protein is functional. Afterwards, the intern will modify the interleukin-2 at different positions, followed by combining these modifications randomly to create a library of various interleukin-2. They will be tested by using immune cells.

As the underlying networks transition into 5G and 6G infrastructure, the optimal task performance across different WIoT devices with different energy consumption and computing power require coordination at both the software and hardware levels to maximize accessibility and minimize latency to support emerging applications. The proposed research will explore the various parameter space to determine how federated learning should be optimally executed in real-time, in the edge and cloud, to maximize user experience supported by upcoming 6G networks.

Curate Mobile operates a demand site platform (DSP), which is an advertising platform responsible for bidding in real time ad placements from various publishers. This process is a blind auction, happening over 50,000 times a second, and during this bidding process we have less then 100ms to determine which of our clients should bid for this ad placement, how much it might be worth to them, and what price we believe we can win this auction for.

Pressure ulcers are a major health concern around the world, affecting individuals living with spinal cord injury (SCI) in particular. Pressure ulcers occur when the blood supply to the skin and underlying tissue is compromised, leading to cell death and potentially fatal infections. In this project, we are developing a soft, flexible and stretchable pressure sensing sheet for pressure ulcer prevention. The device is designed for wheelchair use, where it covers the entire seating area over the cushion.

Preterm birth (PTB) is the leading cause of death in twin pregnancies. A variety of parameters, such as cervical length, maternal medical history, demographics, and obstetric characteristics all have been shown to affect the risk of PTB. However, the relationship is not obvious. Early prediction of PTB in these pregnancies can assist physicians in identifying those patients who may benefit from preventive interventions and closer monitoring. This project aims to use machine learning to create an algorithm that predicts which twin pregnancy is at a risk of PTB.

Detecting the presence of bacteria at a low concentration during a wound healing process can eliminate catastrophic results such as chronic infection and amputation. The available diagnostic techniques with high sensitivity require high-tech equipment and are expensive. Moreover, to monitor the wound with these kits/technologies, wound dressing removal is needed, which causes the second trauma. In order to overcome these shortcomings, we are fabricating Nanosheet™ Biosensor.

Poor physical recovery, especially in remote rehabilitation, is the problem that will be addressed in this project.This project is Phase I of development of Fun-exercise module. Fun-exercise system uses gamification to boost patients’ adherence to their prescribed home-exercises. To achieve this goal, Fun-exercise will use mentally stimulating and customizable games paired with a set of wearable sensors to provide feedback to ensure activities are being done correctly. In phase I, patient study and conceptual design of the Fun-exercise module will be undertaken.

Wearable medical devices (SWDs) are emerging as powerful patient monitoring and data collections tools. These smart, multiplexed devices allow us to quantify dynamic biological signals in real time through highly sensitive and miniaturized biosensors. SWDs can enable monitoring at risk patients at home, diagnosing early disease progression, and reducing healthcare expenditures by means of prediction and prevention of disease.

The proposed research project focuses on multi-sensor such as heart rate, body temperature, oxygen saturation level, and inertial sensor data-based sleep stage classification, and tremor detection in real-time for preventive health devices. The goal of the proposed research is to build robust and energy-efficient machine learning and deep learning-based approaches that extract and analyze the significant information from the multisensor data coming from wrist-based health devices to help Parkinson's patients with tremors and an individual with sleep quality tracking.

Luna Nanotech is in the process of developing an automated portable device for diagnosis of infectious pathogens. As part of his PhD project the intern has participated in the development of a rapid multiplex benchtop serological test for Covid-19. In this project the intern will work with Luna Nanotech scientists and engineers to adapt this benchtop serological test to be used in the diagnostic device to allow rapid automated detection of Covid-19 specific antibodies.