IMPS 2026 Research Competition FAQ
Who is eligible to participate?
To be eligible to compete, each team member must be a full-time graduate student or have graduated no earlier than January 31, 2026. Each team is limited to up to four (4) members, consisting of a single team lead and up to three (3) additional members.
What if I do not have a team. Can I still participate?
Yes, individual submissions will be accepted.
Do I have to register for IMPS 2026 to participate?
If you are submitting as an individual, you must register for IMPS 2026 and agree to present. If you are submitting as a team, at least one of your team members must register for IMPS 2026 and agree to present. The team lead does not have to be the person registered for IMPS.
When do I (or one of my team members) need to register for IMPS 2026?
You must register for the conference by May 4.
How is the winning team selected?
Teams’ initial project submissions are due on June 19, 2026 at 11:59pm PST. A panel of judges will select a group of three finalist teams who will present their work during the IMPS 2026 conference. At the conference, the judges will select a winning team based on their proposal and presentation.
What does the winning team get?
The winning team receives a certificate and a cash prize of $2000.
What are examples of proposal topics?
Below are a couple of links to examples of published studies about high-dimensional data analysis in social and behavioural research. Note that this list is not exhaustive nor is it meant to define the breadth of projects, but merely to serve as inspiration and provide background or a starting point if needed.
- Computational complexity and scalability issues
- https://link.springer.com/article/10.1007/s11336-021-09748-3
- https://doi.org/10.1177/0146621620931198
- https://bpspsychub.onlinelibrary.wiley.com/doi/10.1111/bmsp.12153
- Complex structured high-dimensional data
- https://www.cambridge.org/core/journals/psychometrika/article/latent-functional-parafac-for-modeling-multidimensional-longitudinal-data/97EB58664C3ED9878241E49B508CBB06
- https://www.cambridge.org/core/journals/psychometrika/article/multifaceted-neuroimaging-data-integration-via-analysis-of-subspaces/DF96CB30ABCAD057482692C43DCB3435
- https://pubmed.ncbi.nlm.nih.gov/28637279/
- https://pubmed.ncbi.nlm.nih.gov/31714107/