About Me
DS at University of Michigan, ECE at Shanghai Jiao Tong University. Aspiring Software Engineer with a passion for creating user-friendly human-AI collaborative tools. Currently focusing on the intersection of HCI and AI, exploring how AI assistance benefits user experience in large-scale real-time systems.
I am a quick learner and I am always looking to expand my knowledge and skill set. I am a team player and I am excited to work with others to create amazing applications.
I am also a CAPYBARA lover and enjoy practicing Chinese calligraphy in my spare time.
My Journey
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Programming Languages
Python
95%
C++
90%
JavaScript
90%
TypeScript
85%
Dart
85%
C
50%
Java
50%
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Frontend
React JS
95%
Next JS
90%
TypeScript
90%
JavaScript
90%
HTML
90%
CSS
80%
Tailwind CSS
80%
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Tools
VS Code
95%
Git
90%
WordPress
70%
Figma
70%
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Backend
Django
95%
Flask
90%
Express JS
90%
Node JS
90%
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Database
MongoDB
80%
Firebase
80%
Supabase
80%
MySQL
70%
Redis
70%
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AI
Machine Learning
80%
NLP
50%
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Cloud
AWS
70%
GCP
70%
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My Projects
Snap❤️Meal
At the Google x MHacks AI hackathon, our team harnessed Google's advanced Gemini Vision and 1.5 Pro models to create Snap❤️Meal. This innovative app analyzes grocery snapshots to manage your pantry and generates recipes that optimize the use of ingredients, catering to your dietary preferences and reducing food waste. 📸🥗
🌟Developed with ReactJS, the app offers features designed to enhance your culinary experience:
1. Efficient Grocery Tracking🛒: Automatically logs your groceries from a simple photo.
2. Customized Meal Plans📒: Delivers recipes based on what you have, tailored to your taste and nutritional needs.
3. Sustainable Cooking Practices♻️: Focuses on minimizing waste and maximizing ingredient freshness when generating recipes.
Lipstick Expert
The Lipstick Recommendation Engine is a ReactJS web application designed to simplify the decision-making process for consumers in the rapidly expanding lipstick market. This project leverages data-driven insights from YouTube, utilizing a combination of metrics to recommend the top lipstick choices to users.
1. Data-Driven Insights: Our model identifies the ten most sought-after lipstick types by analyzing key metrics from highly viewed YouTube lipstick recommendation videos. Data is crawled Crawled using BeautifulSoup, Youtube API, and Sephora API.
2. Robust Scoring System: Our model considers factors such as the frequency of mentions, popularity metrics, and NLP sentiment analysis to determine product scores. Model is trained and optimized based on Kendall-tau distance using Python
Health Companion
The Health Companion is a mobile exercise app built with Flutter and Firebase
. The app idea comes from a common worry that we always find difficulty tracking our physical health and lacks motivation to keep to exercise plans we make. Also, lakcing health knowledge and exercise experience, it's easy to get lost.1. Exercise Community: Users can form exercise groups by adding people to their friend lists and start group chat. The chat system is realized using real-time interaction with backend and database.
2. Healthy and lasting goals: Gemini Pro API is embedded in the app to offer people convenience to acquire health information in time. Also, with AI support and advice from other experienced trainer, users can design exercise plans more tailored to themselves.
StoryGen
At the MHacks 16, our team built this education mobile app using React Native. StoryGen is an interactive learning app designed to help children improve their reading skills by allowing them to generate and engage with stories of their choice. Harnessing the power of ChatGPT and integration of NLP libraries, StoryGen enables children to create stories tailored to their reading level and interests, allowing them to learn at an accelerated rate.
1. Interactive Story Generation and Engaging learning experience: Children can input their reading level and keywords or topics of interest. The app generates stories sentence by sentence at a slow pace, providing ample time for children to read and comprehend.
2. Multifaceted Learning: Users can listen to the generated stories out loud, enhancing their auditory learning. Also NLP techniques are usedto visualize sentence structure: Nouns and verbs are highlighted to aid in understanding.
WebNote Bookmarklet
The Webnote Bookmarklet API utilized ReactJS, Flask and MongoDB to allow users to take notes directly on the webpages. The app idea comes from the disturbing learning experience online when we need to constantly copy and paste and store url's where notes come from.
1. Easier note-taking: Webnote Bookmarklet realized highlighting sentences on webpage by selecting information and click the highlighting bookmarklet, which is pretty convenient. This is achieved by careful HTML parsing and web crawling techniques
2. Easier review and directory organizing: Users can create folders in the app and put useful url links inside. Then when they need to review, they can click stored url and click the showing bookmarklet to view all the notes they've taken on the webpage before. All the data are stored in MongoDB
.SummerSara
SummerSara is built with Elm, a language for functional programming. Our team is devoted to creating a fascinating RPG game with multiple endings, incorporating puzzles and games. We hope the game can let players reevaluate their relationship with time and past. To end SummerSara, players need to ask themselves: what kind of life do I want to live? A long yet struggling life or a painless yet largely shortened lif.
🌟Game Highlights:
1. Build connections with NPCs through different dialogues.
2. Work out several puzzles and have fun with games embedded at different scenes to advance plot
3. Explore more game patterns after ending SummerSara.
4. Enjoy exquisite art-work: beautiful ending pages, scene images and so on.
Kunlin Ruan
Full Stack Developer
