Optimal design of composite structures

A composite material is a macro-level combination of two or more material whose properties can be tuned based on the macro-scale distribution of the material. D.I. Self-Composite Alloys Inc., are working on developing a new generation of materials. Their preliminary findings have shown that it is possible to create metals with improved mechanical properties by just tuning the manufacturing process. They are interested in a design optimization tool for composites.

Accelerated development of a recombinant protein vaccine against COVID-19 by integrating the SARS-CoV-2 S-protein antigen with a new delivery system

The objective of this proposal is to develop a new candidate recombinant protein vaccine for the new coronavirus disease 2019 (COVID-19) based on a novel protein delivery and adjuvant technology, iPDT. If successful, this research will advance another COVID-19 vaccine candidate(s) to the pipeline toward clinical use. The causative agent of COVID-19 is SARS coronavirus (CoV)-2. The spike (S) protein of CoV protrudes from and covers the surface of virus particles and interacts with host cell to initiate infection.

Data analysis and image processing for livestock identification

OneCup provides cattle management solutions to the livestock industry. Our AI is called BETSY - Bovine Expert Tracking and Surveillance. Using artificial intelligence, we put a rancher's skillset into a device the size of a small book. With several types of cameras, BETSY can ID and track cattle activity 24x7. For example, she can track an animal's growth over a season, or determine if an animal is suffering from a disease or lameness. When BETSY finds something that requires human intervention, she texts or emails a human immediately.

360 Live ID for Livestock

OneCup provides cattle management solutions to the livestock industry. Our AI is called BETSY - Bovine Expert Tracking and Surveillance. Using artificial intelligence, we put a rancher's skillset into a device the size of a small book. With several types of cameras, BETSY can ID and track cattle activity 24x7. For example, she can track an animal's growth over a season, or determine if an animal is suffering from a disease or lameness. When BETSY finds something that requires human intervention, she texts or emails a human immediately.

Intelligent Systems Data Ingestion and Analytics

This project will support the development of comprehensive, multidisciplinary Smart Building, Smart Transportation, and Smart City management systems in order to improve energy performance, operations cost, safety and reliability for large infrastructures in the private and public sector.
The research problem to be addressed is to develop effective methods to ingest and analyze massive amounts of streaming data from large numbers of WiFi-connected IoT devices monitoring buildings, vehicles, and transportation corridors within a Smart Campus or Smart City.

Exploration of attitudes, motivations and behavioural patterns of social media users in relation to winter backcountry recreation and its effect on avalanche safety behaviour

Social media has substantially changed the information landscape for winter backcountry recreation (e.g., backcountry skiers and snowboarders, mountain snowmobile riders and snowshoers), which has created both opportunities and challenges for avalanche safety. The Avalanche Research Program at Simon Fraser University and Avalanche Canada are conducting a study to examine how recreationists seek, share and introduce social media related information to their avalanche risk management process.

Visual Analytics Methods to Support Sensemaking under Ambiguity in Avalanche Forecasting

Analysis of complex systems involves much more than what is evident in data alone. Background knowledge and experience are used to inform interpretation. Often this results in ambiguity, a state where multiple potential interpretations must be considered and evaluated. When analysis is shared these challenges are compounded by the complexity of communication. Ambiguity is common in avalanche forecasting.

Embedding Project

The Embedding Project is a public-benefit research project that relies on strong social science research methods to bring together a global network of business sustainability change agents and harness their collective knowledge to develop rigorous and practical guidance that benefits everyone. This internship will offer an MBA student the opportunity to gain experience in both practice and research, while learning from leaders in the field.

Investigating Machine-Learning-Based Mocap Data Augmentation for Live Performance

This project is a collaboration between researchers from the Simon Fraser University and industry partners, Lifelike & Believable Animation Design and Animatrik Film Design. Its goal is to research and develop machine learning techniques for capturing and analyzing movement data in real-time to support the world’s first immersive in-game 3D simulcast of a live, real-time motion-capture circus performance, featuring death-defying physical performances and stunning, cinematic quality visuals.

Understanding 3D Spatial-Data from Health, Trade and Customer Service VR Training Simulator

The proposed research is a collaboration between Virtro and SFU’s iVizLab to collaboratively work on ways to understand the processes involved in analyzing and visualizing 3D spatial data. iVizLab’s research focuses on AI based computational models, in this case a data visualization tool that help users analyze 3D spatial data. In creating this user interface, the iVizLab will help teachers find insights and make sense of the errors their students do in a VR training simulator to provide personalized feedback to each student.

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