Undergraduate Project Showcase
CS Project Showcase
Welcome to the School of Computing Science's project showcase. Learn more about the innovative projects that our students are working on to tackle real-world problems. Explore the projects from our undergraduate students below.
Project Title: Impact of Multi-Robot Presence and Anthropomorphism on Human Cognition and Emotion
Team: Jiadi (Tian) Luo
Instructor: Lawrence Kim
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This work investigates how a group of robots and its anthropomorphism affects users' cognitive capability and emotion. We find that increasing the number of non-anthropomorphic robots generally leads to slower performance, but coordinated patterned motions can lower the completion time compared to random movements. An anthropomorphic robot induces an increased level of feelings of being judged compared to a non-anthropomorphic robot.
Project Title: Co-Designing Programmable Fidgeting Experience with Swarm Robots for Adults with ADHD
Team: Samira Pulatova
Instructor: Lawrence Kim
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Recognizing the uniqueness of individual fidgeting tendencies, especially for those with ADHD, we use small tabletop robots to provide a customizable fidgeting interaction experience and conduct co-design sessions with 16 adults diagnosed with ADHD to explore how they envision their fidgeting interactions being changed with these programmable robots. We examine core elements defining a successful fidgeting interaction with robots, assess the significance of customizability in these interactions and any common trends among participants, and investigate additional advantages that interactions with robots may offer.
Students apply HCI concepts to real-world scenarios while exploring advanced and specialized topics such as emerging interaction paradigms, human-AI interaction, ubiquitous computing, the social impact of HCI, and inclusive design.
Project Title: Fitness AI
Instructor: Parmit Chilana
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Entering the world of working out can be veryoverwhelming to beginers, making them lessmotivated to start their health journey. Withthis website, we aim to simplify the process ofcreating a routine so that beginers can easilycreate their own routine.
Project Title: CalendarGPT
Team: Aneet Kaur, Lara Carvalho Lemos, Emma Yang, Belinda Zhu
Instructor: Parmit Chilana
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This project plans to enhance ChatGPT, a leading generative AI tool, by integrating an AI-powered calendar and scheduler tailored specifically for post-secondary students. Our application will help students efficiently organize their schedules, deadlines, and daily tasks, offering AI-generated suggestions and manual customization options.
Project Title: ChatCompare: Generative-AI Chat Bot Comparison
Team: Matteo Bombelli, Ryan Hargrave, Miles Grant, Weiqi Wang
Instructor: Parmit Chilana
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This project aims to enhance the efficacy and usability of large language models (LLMs) for professionals working in the workplace and research environments. Despite the abundance of generative AI chatbots available today, there remains a significant gap: users lack an effective method to compare the performance and responses of different LLMs simultaneously.
Project Title: LeetBuddy. AI-based Technical Interview Preparation Tool
Team: Yaaska Pandit, Trevor Cho, Nicholas Medland, Ryan Phan
Instructor: Parmit Chilana
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Current technical interview tools lackpersonalized guidance.AI often provides direct answers, limitingthe learning process.Switching between AI chat and problem-solving websites is cumbersome. LeetBuddy offers native AI hint generation and interactive chat during problem-solving. It provides analysis of time/space complexity, style, and actionable suggestions.
Project Title: MathHelper - The AI Math Helper
Instructor: Parmit Chilana
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The goal of MathHelper is to assist math students in getting math help by offering an efficient method of inputting complex math equations to an AI, offering detailed explanations of solutions and generating personalized practice questions to enhance theri understnading of the topic.
Project Title: My Trip AI - Simplifying Travel Planning for Young Budget-Concious Travelers.
Team: Celvia Tjahjadi, Katya Kubyshkin, Shana Chan, Lacey Swamy
Instructor: Parmit Chilana
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Travellers, especially young budget-concious ones, face challenges in organizing their trips, including managing bookings, budgeting and tracking expenses accross multiple platforms. existing solutions are often convoluted and lack ease of use.
My trip AI is a mobile-friendly website that centralizes bookings, tracks expenses and provides AI-powered sugesstions based on user preferences, focusing on simplicity and efficiency.
Project Title: Movie Recommendations That Don't Suck: Precise, Feedback-Driven Media Suggestions with Gemini
Team: Alexander Cannuli, Anderson Lee, Mason Liang, Misha Zoubarev
Instructor: Parmt Chilana
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Users of movie streaming services often feel dissatisfied with in-app recommendations, finding them poorly aligned with their interests and limited in categorization.
Our app addresses these issues by integrating AI to deliver precise, transparent, and personalized movie suggestions. Users can sync their streaming accounts, allowing the app to analyze watch history and preferences to generate tailored recommendations.
The app offers two interfaces: a generative AI chatbot for quick, focused suggestions and a simple filter-and-browse option for broader exploration
Project Title: Draw-E - Draw Now. Draw Better.
Instructor: Parmit Chilana
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What is the current problem with DALL-E?
- Lack of control, customization, and understanding of the AI
- Unintuitive, resulting in a large gulf of execution
Why Improve DALL-E’s UI?
- AI assisted image creation decreases skill barriers
- Image creation becomes more accessible
- Increase productivity
Project Title: Thread - AI-Powered Fashion Assistant
Team: Asmita Srivastava, Bianca Diamaano, Gahee Kim, Kaylee Ryu
Instructor: Parmit Chilana
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Thread, an AI-powered fashion assistant app, simplifies outfit styling for beginners. Upload images of your clothing, and effortlessly create personalized outfits by selecting items from your wardrobe.
Project Title: TerminAI
Team: Dixon Snider, Yifei Jia, Nam Nguyen, Jedidiah Akinola
Instructor: Parmit Chilana
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What's the problem with standard Terminals?
- Terminals/CLI's can be intimidating for beginers.
- Advanced users get frustrated having to constantly retype or look up long and complicated commands
Our Solution
- AI-integrated terminal that simplifies the command-line experience by offering natural language input, clear command explanations, and a customizable interface tailored to user needs.
Project Title: AI TUTOR : A Browser Extension for Solving Coding Problems.
Team: Nolan Whittaker, Steve Duong,Tony Huang, Ryan Marwaha
Instructor: Parmit Chilana
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Based on personal experience, using AI for LeetCode problems often hinders learning since it provides direct solutions without supporting the learning process. To address this, the AI coding tutor was designed to guide users through structured learning rather than simply giving answers. Early concepts included using AI to generate visuals, provide tiered hints, recommend resources, and offer partial or full solutions. These ideas were refined through four project stages: ideation, interviews and sketches, medium-fidelity prototype, and high-fidelity prototype.
Project Title: GitGPT - Mobile Coding Assistant with GitHub Contextual Integration
Team: Yecheng Wng, Tianxi Huang, Yvan Zhang, Albert Zhang
Instructor: Parmit Chilana
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Project Title: H2OhYeah!
Team: Jasmine Lin, Josie Tran, Yewon Park, Edmund Lee, Jin Song
Instructor: Lawrence Kim
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This project introduces an idea to pair an app with a water bottle to automatically track water consumption and promote a healthier lifestyle through water consumption.
Project Title: Mental Health App Design for University Students
Team: Nayeong Lee, Khant Te Kyi, The Vinh Hong, Jake McFarland, Albert Chao-an Liu
Instructor: Lawrence Kim
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Mental Health App Design for University Students introduces an app to help improve the mental health of university students through the facilitation of social interactions, such as study groups, discussion forums, and therapy sessions.
Project Title: AskSFU: The AI-Powered University Chatbot
Team: Manish Madishetty and Gowtam Garapati
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Ask91ÅÝܽ an AI-powered chatbot developed to help students at 91ÅÝܽ quickly and accurately find information related to courses, clubs, admissions, and campus services. Students often face difficulties navigating the SFU website to locate key details about academic programs, club activities, and university resources. AskSFU addresses this challenge by consolidating relevant content from official SFU webpages into a centralized knowledge base.
Using Retrieval-Augmented Generation (RAG) and OpenAI’s language models, the chatbot retrieves and generates accurate, natural-language answers to student queries. It includes features like 24/7 personalized assistance, citation of source links for transparency, and fallbacks to GPT responses when no match is found. The tool is designed to reduce repetitive inquiries to advisors, improve access to course information, and enhance student engagement across SFU’s online services.
This service runs on OpenAI API tokens and will stop functioning once the available credits are used up
Working link:
