Funding program
The Applied AI Institute offers an annual funding program meant to advance its strategic directions and accelerate interdisciplinary research on AI at Concordia University.
Open Call
AI2 Call for Proposals: Collaborations with Industry
The Applied AI Institute is accepting applications to its annual funding program meant to accelerate AI adoption across sectors. The program funds new or on-going applied AI research projects in collaboration with industry or non-profit partners. Successful projects will have the potential to receive ongoing funding until May 2027.
Fund Details
Successful projects will have the potential to receive ongoing funding until the end of the project (May 2027). We encourage innovative proposals that address real-world challenges and are based in Quebec.
Eligible expenses:
- Salaries and benefits for part-time or full-time research professionals, including research assistants and research associates.
- Note: however, MSc or PhD bursaries or funding awards are not eligible. Salaries for post-docs are also not eligible.
Funding Structure:
- Industry projects
- 50% funded by this program.
- 50% will be funded by a private partner via cash contribution, plus University overhead fees.
- Note: the industry partners’ contributions cannot come from provincial grants.
- Non-profit collaborations
- Up 100% funded by the program.
- Contingent on fund availability.
How to Apply
To apply, please complete this form. In the form, you will need to provide the following information:
- Names and CVs of research team
- Project description
- Description of alignment with the AI2 guiding principles
- Institutional partner details
- Letter of support or confirmation of funding from institutional partner
- Budget
- Confirmation of eligibility
If you have any questions about your eligibility, or the application process, please email the AI2 Institute.
Evaluation Criteria
We encourage innovative proposals based in Quebec that address real-world challenges. Applications will be ranked by the Operating Committee using the following criteria:
Encourages AI Adoption
Describe how the proposed research program will encourage the private sector or non-profit organizations to adopt artificial intelligence and the potential impact on the broader community.
Feasibility
Highlight past research accomplishments and capacity to undertake the proposed program of research.
Fit with AI2 guiding principles
Describe how the research program meaningfully responds to public interest, demonstrating a commitment to principles of equity and justice. Additionally, explain how you have addressed barriers that could prevent participation from underrepresented groups.
As well, describe how your team advances interdisciplinary collaboration, inviting members from at least two faculties (e.g. Arts and Science, Management, Engineering).
Previous Calls
Funding Programs
We have offered the following funding programs:
Matching Funding
- Approximately $25k was made available, up to $5K per call, for applied artificial intelligence research projects.
- We encouraged early career researchers to apply and will prioritize funding projects evenly across the four faculty.
- Successful applicants committed to public engagement through a workshop, seminar, poster session, or other kind of event.
Working Group Funding
- Approximately $45k was made available, up to $10k per call for inter-cluster and cluster-based working groups centered around a theme related to applied AI. Our members proposed AI&SynthBio, AI&Health, but we were open to a variety of art, life-science, or other variations our members proposed.
- We provided up to $5k of funding for each working group. In addition, we will provide $1k honorariums each for 3-5 graduate students who will participate in the projects of the working group.
- Successful applicants committed to public engagement through a workshop, seminar, poster session, or other kind of event.
2022 AI Auditing Seed Funding
- Seed Projects (approximately $25k was available) meant to accelerate research into the assessment, development, and auditing of AI systems including, but not limited to, identifying and auditing high-risk AI systems.