Goals:
- Build lab skills
- Explore specific research interests
- Set himself up as a competitive MD applicant
Frustrations:
- Can't efficiently find labs that are a good fit
- Significant time and effort is leading to no results
- Feels like he is falling behind his peers
Goals:
-Find motivated students with the correct skillset
- Speed up her doctoral research with more assistants
- Meet impending deadlines to keep full project scope
Frustrations:
- Past students lacked domain interests or relevant skills
- Must find new aids, or will need to pivot to scale down the research scope
0 Initial Scoping
College students face many problems, so we did some idea scoping to understand different problem areas, and figure out what problem space we wanted to focus on. Eventually, we realized we all had faced trouble looking for research opportunities, and had felt frustrated with UW's research database and the long and strenuous process to get involved with research at the UW.
01 Market Research
We did some market research, trying to understand current and previous solutions, including what works and what doesn't work. This research helped us to identify our main research questions, which set the context for our user research, ideation, and testing phase.
02 User Research
With our research questions in mind, we started to ideate, talk with actual users (both undergrads and graduate students), and user test our ideas, validating concepts and our key design values.
03 Product Development
With some ideas in mind, we started to scope out our features, working simultaneously on user testing Figma mockups and the front-end and back-end development. As we got more feedback, we fine-tuned our features, bringing us to our core product:
The biggest problem we found across existing solutions was a lack of standardization, relevance, and current-ness. Postings were outdated, some missing key information, and all over the place - PDFs, department websites, papers stuck to office bulletin boards. There was no good way to find research postings, and, on the research-lead side, no way to find relevant and well-fitting candidates for research positions and roles.
MatchLab solves this problem, by standardizing information across postings (requiring key, often-missing information such as if the position is paid or unpaid, time commitment per week, duration of position, and skills required); updating postings automatically when they fill or are removed; allowing students and research leads to save profile information (past experience, interests, major, domain knowledge information, etc); adding filters and tags to postings to make the search process easier and more efficient; and a match percentage, which takes into account key traits from the student side and research role, 'matching' students to a role.
Albert Lam - INFO + BUSINESS '23
Rishi Kavikondala - INFO '23
Thomas Gerber - INFO '22
Anika Mishra - INFO '22
