Human-AI collaborative resume screening tool wins 2023 capstone design award

Fifteen management engineering capstone design projects were recently showcased at the 2023 Management Engineering Capstone Design Symposium. Students identified and tackled emerging problems in a range of domains and industries including healthcare, social services, human resources, lifestyle, and education. Their innovative and impactful solutions offer critical process improvements and decision support tools to serve individual and institutional stakeholders.

Project Calamansi by Justine Archer, Francois Barnard, Arden Song, Christiana Wu and Charles Yu was honored with the top prize in the cohort. In addition, Calamansi also won the Konrad Capstone Design Award

Below is a spotlight on project Calamansi originally published by the Faculty of Engineering. 

Explain your project in one sentence 

Calamansi is a user-collaborative machine learning-based application that works with recruiters to mitigate the pain of leafing through numerous job applications in their hiring processes by saving time and maintaining quality. 

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

Working together with friends before heading in different directions! And seeing Calamansi come to fruition. 

What are the biggest challenges you've faced during the project? 

Finding and collecting data (like old resumes) to actually train and test our machine learning model was initially a bit of a challenge, but we’ve managed to get a bunch through our network! 

How does your project improve human lives and/ or our planet's health? 

Calamansi will greatly improve the job recruiting process from the employer’s standpoint. Recruiters will save hours of time looking through resumes by collaborating with Calamansi. 

For background, Calamansi leverages Continuous Active Learning (CAL), which is a machine learning paradigm where users continuously provide their input to update and refine a given model in real time. So, not only will significant time and effort be reduced for users, but they will be able to understand and work with the system to come to their decisions (i.e., collaborative artificial intelligence!). 

What's next for your team members (ie: working full-time, looking for a job, starting a business, etc). 

• Francois: hopefully internship in summer, then Masters at University of Waterloo focusing on NLP and QA systems (like our project) 
• Arden: a master’s at the University of Waterloo, hopefully researching board games 
• Christy: also travelling to southeast Asia, then looking for a job in data science 
• Charles: Travelling to Japan and around the world before starting a software engineering job in NYC in September 
• Justine: taking a trip to southeast Asia, then looking for a job in product management