This program requires your motivation, time commitment and openness to collaborate. Once your team is accepted, you’ll be given access to required resources and receive weekly mentorship from the professor.
Tentative Plan: In the beginning of the program, all teams will work in parallel to solve a common problem using their unique approach. This technique will encourage out-of-the box ideas and bring diversity through multiple approaches. Every week, your peers might evaluate you and your team’s progress and performance. The approach receiving highest score gets discussed with the professor during the weekly meeting, and everyone is expected to take next steps or improve their approach based on these discussions. This set up will create a challenging environment for all participants, without over taxing professor's time. Every week, you also get a chance to evaluate us through a quick survey, on how we’re doing and you can make suggestions or leave anonymous comments.
Through these about 10 weeks, you’ll experience academic research process of brainstorming, prototyping, iterative development, results generation and evaluation. Depending on time constraints, diversity in approaches, your skill sets, your progress and performance; we might merge, split, add, remove or re-arrange your teams or team members to optimize this new research process in our controlled environment. Therefore, it is important that you should be willing to collaborate with new people and also be open to compliment your skill sets where its needed most. It is possible that the team you begin working with might change during the course of the program.
At the end of this program, we will submit a research paper at a top-tier conference. The paper will be based on results produced by you, and you get to be an author on the paper on the basis of your contribution. In computer science, professors go last in the author list, therefore, one of you has a chance to be the first author!
-Parallel prototyping leads to better design results, more divergence, and increased self-efficacy. Steven P. Dow, et. al. ACM Trans. Comput.-Hum. Interact 2010. [pdf]
-The Polymath Project: Lessons From a Successful Online Collaboration in Mathematics. Justin Cranshaw, et. al. CHI 2011. [pdf]
-Massively Distributed Authorship of Academic Papers. Bill Tomlinson, et. al. CHI 2012. [pdf]
-Pair Research: Matching People for Collaboration, Learning, and Productivity. Rob Miller, et. al. CSCW 2014. [pdf]