AI-driven Predictive Models and Consumer Insight for Trade Optimization Improvement

The proposed project is to develop AI strategies to provide precision marketing through consumer segmentation and recommender systems, as well as to promote events that shall meet various business goals for retailers and Unilever. Successful outcomes will feed into an On-Demand AI Engine aimed at improving consumer engagement and pricing strategy in the consumer packaged goods sector.

Edge-Cloud Video Streaming Pipeline for Video Action Recognition

Streaming Cameras have become ubiquitous in the urban and industrial landscape. This research project aims to improve the AI-based action recognition capability of consumer-class home camera streams, which often have limited bandwidth and degraded video quality. The project proposes to develop a network-aware, video-action recognition AI pipeline that pushes key operations of traditional action recognition pipelines to the edge and uses this in concert with a cloud-based infrastructure to provide high-precision recognition capability.

Functionalization of tunicate-derived- cellulose nanocrystal additive manufacturing of their bio-derived polymer nanocomposites

Tunistrong Technologies, a sustainable biotech company utilizes invasive marine species of tunicates to produce value-added products such as cellulose nanocrystals (T-CNCs) and is the only known commercial producer of T-CNC. T-CNCs are more sustainable and greener as it is synthesized from invasive animal rather than plants. It is beneficial to demonstrate the application of T-CNCs in the green additive manufacturing (AM) space.

Physicomechanical and rheological analysis of PHB and PHBV for packaging application

Polyhydroxyalkanoates (PHAs) are bio-based, biodegradable polymers that have the most potential to replace conventional polymers used in food packaging. To this end, PHAs must be designed to achieve low cost and better performance, such as tunable mechanical properties, crystallinity, surface features, amphiphilicity, and degradation rate.

Wearable Digital Technology for Continuous Monitoring of Vital Signs

SFU will be collaborating with partners of a supercluster on the Continuous Connected Patient Care (CCPC) Platform, which is being developed to provide safe, responsive, and high-quality outpatient care at home. We will be working directly with our partner, Medtronic Canada. SFU’s will focus on the research, development, and testing of medical grade wearable sensor systems for untethered and continuous monitoring of vital patient parameters including SpO2, pulse rate, respiration rate, activity, and blood pressure.

A Nanomaterial-Integrated Paper Microfluidic Device for Detecting and Predicting Myocardial Infarctions

Cardiovascular disease kills 17.9 million people globally each year. 85% of these deaths were caused by either a myocardial infarction (heart attack) or stroke. Current tests for predicting heart attacks provide rapid results when presented with a blood sample, but these samples must be preprocessed using time-consuming methods. This project will develop a paper-based platform to detect heart attack markers in blood without external preprocessing. This will be accomplished by integrating a blood processing device into the testing platform.

Computer Vision for Autonomous Spacecraft Docking

Current spacecraft docking systems are expensive, large, and require a high-power draw due to the sensors used such as Radar or Lidar. A vision-based spacecraft docking system is proposed to enable the use of lightweight, inexpensive, and less power-intensive optical sensors when compared to Lidar and Radar, and vastly improve upon existing systems. This project seeks to research and implement a combination of classical techniques and modern artificial intelligence methods to overcome the harsh lighting conditions of the space environment which reduces the reliability of vision-based systems.

Identifying optimal growth conditions for cell-cultured fat

This research project will investigate the optimal environment for creating cultivated fat (real animal fat grown in a
lab, without harming any animals). Cultivated fat will be a key ingredient to help alternative protein sources achieve
the taste, texture, and aroma, and nutritional value of conventional meat; however, cultivated meat/fat companies
face challenges in driving down production prices.

Oxygenation for muscle stem cell growth and differentiation

The project's partner, MyPalate Inc., produces real meat without raising whole animals and
facilitates a new era of protein consumption.. Using a parallel, gas-controlled bioreactor
system, the project aims to understand how process parameters influence oxygenation status
during muscle cell proliferation and differentiation. Specifically, we aim to investigate how the
dissolved oxygen, impeller agitation speed, gas flow rates, and gas composition can be tuned
to optimize cultured pork production in stirred-tank bioreactors.

Renewable Diesel fuel from Fischer–Tropsch synthesis

Greenfield Global has been developing a process that aims to convert renewable materials to produce sustainable jet fuel (SAF). In addition to SAF, it is possible to produce other fuels such as diesel. Greenfield Global has been awarded a federal government grant which aims at developing a novel process for the production of renewable diesel from agricultural wastes. A key process step in this project is Fischer-Tropsch (FT) synthesis and upgrading to drop-in fuels particularly renewable diesel.