Sam Wang’s Project Portfolio
About Me
Welcome! I’m Sam Wang, a Junior studying Informatics and Mathematics at the University of Washington. I am currently working on a project called DOGPAWS, a social media web-app aimed at uniting the UW student body and its professors for both academics and professional networking opportunities.
I am very interested in backend development and data science and am currently seeking internship opportunities in software for Summer 2021.
My GitHub.
Projects
DOGPAWS | Data Team Lead
DOGPAWS is a social media project that began in April, 2020. Our vision is to better connect UW students (Huskies) with each other, and with the abundant resources that UW has to offer.
As the Data Team Lead, I manage and direct a team of 10 people to work on tasks such as designing ERDs, creating and setting up databases, and writing stored procedures to automate various backend processes. I also used Tedious to communicate between MS SQL Server and our Node.js server.
We are currently working on features to connect students with each other based on classes, interests, or hobbies; find roommates; and create a collaborative platform to improve efficiencies in studying and communication.
Project GitHub
HuskyMaps
HuskyMaps is an interactive map of the Greater Seattle Area that allows the user to find the shortest path from one location to another. Set your start and end location by double-clicking anywhere on the map. If you click on a building or somewhere that’s not physically accessible, HuskyMaps will automatically snap your location to the nearest road, so the path returned will always be valid.
Implementation details: autocomplete (case-sensitive) implemented with dual-instance binary search, A* algorithm to find the shortest path, k-d trees for nearest-neighbor search for finding the nearest road where a user clicked on the map. GitHub.
Hingeify
Hingeify is a web-app that allows the user to input their own data from the Hinge dating app and dynamically produces data analysis and visualizations in a digestible manner. It displays a summary of statistics such as their likes sent, likes received, and matches with others since their Hinge account was created. Moreover, it creates interactive data visualizations that provide further insight about their own Hinge habits. For example, the time of day when they’re the most active and receiving the most matches.
There are instructions on the website on how to download your personal data as an existing Hinge user.
