Grants and Contributions

This project entails the engineering design, customization, and integration of a rugged thermal enclosure to house the current Dragon Fire PCB design with increased abilities on electronics platform for the current (OI V01.0).

To enhance SuiteSpot SaaS platform for multi-family property operators which digitizes, automates and improves the efficiency of property maintenance processes with technology. This project would augment SuiteSpot's offering by enabling automatic scheduling of technical staff thus reducing management overhead and increasing the efficiency of the existing workforce.

Jurisage Group aims to solve a crucial pain point faced by lawyers’ legal research and writing workflows by helping them contextualize their research and write legal documents more efficiently with AI/ML-assisted tools. This includes tools for organizing legal research for citation purposes, collaborating with others on citations in documents, and maintaining consistent citations that are acceptable for court filings.

The Project aims at the discovery and optimization of Metal-Organic Frameworks (MOFs) for carbon capture, utilization, and storage (CCUS) applications, particularly focusing on ocean carbon capture and electrochemical CO2 conversion. Leveraging the advanced capabilities of Large Language Models (LLMs) and AI-driven laboratory automation, the Project aims to rapidly identify and synthesize promising MOF candidates, a task traditionally hindered by the vast chemical diversity and slow experimental processes. The Project objective is to develop an LLM/AI driven framework towards MOF discovery, and then apply this framework towards applications in bicarbonate (ocean capture) and electrochemical CO2 reduction. Alongside these performance metrics, the Project will prioritize properties desirable for CCUS applications, such as moisture stability, synthesizability, low-toxicity, and alignment with industry standards. A significant outcome will be establishing a pioneering ML-guided framework for material discovery, contributing a novel dataset to the scientific community, thereby enhancing research and development in CCUS technologies.

The Project aims at the discovery and optimization of Metal-Organic Frameworks (MOFs) for carbon capture, utilization, and storage (CCUS) applications, particularly focusing on ocean carbon capture and electrochemical CO2 conversion. Leveraging the advanced capabilities of Large Language Models (LLMs) and AI-driven laboratory automation, the Project aims to rapidly identify and synthesize promising MOF candidates, a task traditionally hindered by the vast chemical diversity and slow experimental processes. The Project objective is to develop an LLM/AI driven framework towards MOF discovery, and then apply this framework towards applications in bicarbonate (ocean capture) and electrochemical CO2 reduction. Alongside these performance metrics, the Project will prioritize properties desirable for CCUS applications, such as moisture stability, synthesizability, low-toxicity, and alignment with industry standards. A significant outcome will be establishing a pioneering ML-guided framework for material discovery, contributing a novel dataset to the scientific community, thereby enhancing research and development in CCUS technologies.

A Research assistant is responsible for supporting research projects and performing various tasks such as collecting and analyzing data. preparing research reports, and maintaining accurate records. The Research Assistant will work under the direction of the Lab Manager and other Managers and Directors as deemed appropriate including other research members. the Research Assistant will also be responsible for ensuring that all research activities are conducted according to established protocols, policies, and procedures as well as applicable laws and regulations.

This International Co-Innovation Action Program (ICAP) project will prepare the firm to enter into future international co-innovation work.

The JITAI project focuses on leveraging cutting-edge AI to improve mental health support through timely and personalized interventions. This initiative seeks to enhance user engagement and establish innovative standards in digital health, by providing adaptive support that responds to the immediate needs of individuals, aiming for a significant positive impact on overall mental wellness.

validation of new sensors and new materials that will allow XSENSOR to advance the capabilities of its industry leading capacitive sensor technology.

Sulpetro, a Canadian energy market research firm specializing in North American LPG-NGL statistical data, seeks to automate its data collection process across all states and provinces in North America. This project aims to enhance the efficiency, accuracy, and comprehensiveness of data collection, thereby significantly improving service offerings to the energy sector and allowing the business to grow and expand in the North American marketplace.