Grants and Contributions

This is a multifunction team project involving Sales, Ops, Purchasing and Finance, sponsored by the CEO.

The synthesis of motion data presents a significant opportunity to address key scientific gaps in the study of human activities and interactions, particularly in the context of developing assistive agents to support older adults aging in place. One of the primary challenges in this domain is the scarcity of comprehensive and diverse datasets that accurately capture the intricacies of daily activities and interactions within home environments. Existing datasets often lack the granularity, realism, and size necessary to train AI models effectively, hindering the development and deployment of assistive technologies tailored to the specific needs of older adults. Furthermore, the synthesis of motion data allows augmenting existing datasets or generating entirely new datasets that encompass a broader range of activities and scenarios, thereby enabling more robust and generalizable AI models. By bridging this data gap through AI-driven synthesis, new opportunities can be unlocked for studying human behavior, understanding social dynamics, and ultimately designing more personalized and effective assistive agents to support older adults in maintaining their independence and quality of life while aging in place

The Firm seeks to hire and train a Graduate into its software development team. This project will include training on multiple systems and software the firm employs, quality assurance testing, and general product development.

As part of the Japan Corporate Co-Innovation Program, the project “GoGame” will focus on software development of AI technology to transform game footage analysis for the Japanese gaming market.

Plastic pollution is a worldwide problem. As plastic pollution is expected to grow, the amount of plastic in the environment is also expected to grow. Plastic pieces found in the environment are categorized depending on their size: microplastics (MP) (1-5000 µm) and nanoplastics (NP) (1-1000 nm). Both micro and nanoplastics can have deleterious effects when ingested by organisms in the environment. Observed effects varies from food dilution, oxidative stress and lower reproductive success. Additionally, more and more research is done on organisms microbiome. Once ingested, microplastics are mainly accumulating in the gastro-intestinal tract before being egested with feces and only a small portion will reach other organs. In the case of nanoplastics, due to their small sizes, they can cross biological barriers and can be distributed within all organs. As the gastro-intestinal tract is where both micro and nanoplastic transit through, these particles can have potential effects on the gastro-intestinal tract itself but also on the microbiome inhabitating it. Additionally, some research found that nanoplastics can disrupt the brain-intestine-microbiota axis, and call for this endpoint to be studied when assessing the environmental risk of micro and nanoplastics. To study the effects of micro and nanoplastics on gut microbiota, we propose to use adult zebrafish (Danio rerio) as a model species.

The Civonus AI Facilitator Co-Pilot project will implement AI solutions to carry out some of the tasks of the Facilitator, and scope out the data requirements for machine learning to automate the facilitator role, and thereby reduce the cost of the service for clients.

This is an R&D project to test hypotheses and experiment with new mechanisms to design a repeatable and scalable business process and to develop IP in business methods.

Accelerating YoGPS GPS Tracking solution’s growth and leveraging marketing tactics to create brand awareness, credibility thereby generating leads and improving revenue.

This project will enhance the OneVest trading platform. The portfolio optimizer, already in use, efficiently processes portfolios in minutes and reduces trades, minimizes tax burdens, and boosts investment efficiency. This project will integrate multi-currency management and separately managed accounts into the platform and improve performance.

A major challenge to photonic graph states is to work out an efficient algorithm for its generation. In this project, researchers will develop algorithms for such an optimization.