Waterloo SearchWorks

Team waterloo search works

March 23, 2022

As part of our FYDP/Capstone 2022 spotlights, we’re excited to introduce team 10 from Management Engineering: Amy Tai, Peter Bondi, Christina Lee, Bradley Hallett, and Seher Sarin and their project “Waterloo SearchWorks”! 

Can you explain your project in one sentence? 

Our project improves the search experience for Waterloo’s co-op job platform by developing a more advanced search engine that helps students find the most relevant jobs more efficiently and effectively. 

What has been the best part of your project so far? 

The best part of our project so far has been being able to integrate concepts from our diverse courses to design and validate our product and hearing immense positive feedback during our user interviews. Throughout this project, our team leveraged knowledge from our algorithms and data structures (MSCI 240), human-computer interaction (MSCI 343), database systems (MSCI 346), information systems analysis and design (MSCI 444), machine learning (MSCI 446), search engines (MSCI 541), and natural language processing (MSCI 598) courses to write concise code with appropriate unit tests, design a user-friendly system interface, and implement a workable prototype that effectively processes text queries. It was a ton of work but we wanted to work on a project that would positively impact students and we are so happy to know that it will! 

What is the biggest challenge you’ve faced during your project? 

The biggest challenge we’ve faced so far with the project is the data and integration restrictions with WaterlooWorks due to university policies regarding research and data access. However, we were able to closely collaborate with Waterloo Cooperative Education to ensure that our end design is feasible and can be integrated in the future. 

What’s next for your team members once you’re finished? 

Some of our members will be working full time as project managers, product managers, or data scientists in the fintech/insurance, AI, and technology space with other members pursuing thesis-based graduate programs in optimization, computer vision, and medical imaging.