Grants and Contributions
About this information
In June 2016, as part of the Open Government Action Plan, the Treasury Board of Canada Secretariat (TBS) committed to increasing the transparency and usefulness of grants and contribution data and subsequently launched the Guidelines on the Reporting of Grants and Contributions Awards, effective April 1, 2018.
The rules and principles governing government grants and contributions are outlined in the Treasury Board Policy on Transfer Payments. Transfer payments are transfers of money, goods, services or assets made from an appropriation to individuals, organizations or other levels of government, without the federal government directly receiving goods or services in return, but which may require the recipient to provide a report or other information subsequent to receiving payment. These expenditures are reported in the Public Accounts of Canada. The major types of transfer payments are grants, contributions and \'other transfer payments\'.
Included in this category, but not to be reported under proactive disclosure of awards, are (1) transfers to other levels of government such as Equalization payments as well as Canada Health and Social Transfer payments. (2) Grants and contributions reallocated or otherwise redistributed by the recipient to third parties; and (3) information that would normally be withheld under the Access to Information Act and the Privacy Act.
$463,216.67
Mar 30, 2020
International (non-government)
Understanding non-involvement in terrorism: why most radicals never become terrorists
21053
The purpose of this contribution will provide insights into non-involvement in terrorism. The research will seek to ask why most people who radicalize never actually become terrorists. What distinguishes this ‘control group’ from those who do cross this threshold, and understanding these differences can help policymakers and practitioners more effectively prevent and respond to terrorism.
$150,000.00
Mar 26, 2020
For-profit organization
400057173
400057173
Marketing strategy: The project aims to support the growth of an innovative start-up company through the implementation of a commercialization strategy for an R&D-based product using artificial intelligence, in this case a Chatbot.
$200,000.00
Mar 26, 2020
Academia
Smart agri-food supply chain digital twinning
947416
The goal is to investigate intelligent management of supply chain digital twinning with application to the Global Agri-Food Value Chain (GAVC) that improves food quality and safety.
$237,600.00
Mar 25, 2020
Academia
AI for simulation and design of nanocatalytic materials
947408
This project aims to harness the power of modern Artificial Intelligence to build on the success of DFT and ferret out optimal design parameters.
$156,750.00
Mar 25, 2020
Academia
AI for drug design – development and testing of ai methods and molecule parameterization
947434
The emerging of massive biochemical and high-throughput genomic data acquisition techniques and the rise of advanced artificial intelligence paradigms provide an unprecedented opportunity for automatic design of new drugs with much faster pace and much lower cost, igniting hopes to discovery drugs for diseases where no medicines have been found yet.
$260,000.00
Mar 25, 2020
Academia
Wildlife health and plastics – surveillance, health intelligence and knowledge mobilization
$158,400.00
Mar 25, 2020
Academia
AI FOR SIMULATION AND DESIGN OF NANOCATALYTIC MATERIALS
947408
This project aims to harness the power of modern Artificial Intelligence to build on the success of DFT and ferret out optimal design parameters.
$200,000.00
Mar 25, 2020
Academia
Smart Agri-Food Supply Chain Digital Twinning
947416
The goal is to investigate intelligent management of supply chain digital twinning with application to the Global Agri-Food Value Chain (GAVC) that improves food quality and safety.
$126,500.00
Mar 25, 2020
Academia
AI FOR DRUG DESIGN – DEVELOPMENT AND TESTING OF AI METHODS AND MOLECULE PARAMETERIZATION
947434
The emerging of massive biochemical and high-throughput genomic data acquisition techniques and the rise of advanced artificial intelligence paradigms provide an unprecedented opportunity for automatic design of new drugs with much faster pace and much lower cost, igniting hopes to discovery drugs for diseases where no medicines have been found yet.
$310,200.00
Mar 24, 2020
Academia
Intelligent design through graph generation with deep generative models and reinforcement learning
947409
The objective of this project is to develop general machine learning techniques for graph generation, with the end application of smart design including new material discovery, advanced circuit design, and novel drug invention, amongst many others. Research will focus on deep generative models and reinforcement learning for the generation of graphs with optimized properties. The representation power of graph will be leveraged to sufficiently encode the key compositional behaviours and their interplays of the target domain, and treat developing a novel design as a new graph structure generation process with various composition constraints. The decomposition in the former can be attained through deep generative models with disentangled latent variables, and the composition search space in the latter can be effectively explored by deep enforcement learning.