Technology  ·  August 24, 2020

Staff Favorite Projects from CodeDay Labs 2020!

Erika Lamothe, Marketing Manager

Students created hundreds of amazing projects during our summer internship program! While all the projects taught students new languages, techniques, and skills in the tech industry (frontend and backend development, api implementation, and language processing to name a few), there were projects that really stood out to us. 


Yanilda Peralta Ramos, Alyona Karmazin, and Charles Sy mentored by Eric Hui:

This project was inspired to medicate the over-exposure of depressing news and daily life stresses with laughter. Who doesn’t love a good dad joke? This web application looks simple on the surface, but so much has gone into making this a functional and user-friendly app that it really struck our team (aside from the incredibly amusing dad jokes)! They implemented joke sentiment, a star rating system, how many users rated a joke, filter system, and search tools!

Let’s talk tech: This team used AWS to host and run their static website as well as using Github for source control and Terraform to provision the infrastructure. For the frontend CI/CD, they used AWS CodePipeline, and for the backend, they used the Serverless framework! Throughout this project, the students learned how to optimize Lambda functions to minimize runtime, use Serverless technology, and how DynamoDB differs from a relational database.

We must close with a dad joke: “Why don’t eggs tell jokes? They’d crack each other up.”

There is so much more included that we can’t write it all here, so why not watch their full tech talk on how it all came together: 


Edward Haas, Erica Chong, and Jovan Petrovic mentored by Aditi Kabra:

This website was made to help people find related seminal papers when researching new technical subjects! It is often hard for people to go beyond a starting point when it comes to researching topics; finding that next point in research is incredibly difficult. The process of looking at an abstract to the intro to citations is a tedious one. Citations are flooded with 20 sources to navigate through, and not all of the sources are relevant to the specific topic you’re researching! So with this headache of a process in mind, the team developed a way to visualize and showcase articles that are relevant to topics users are researching.

Let’s talk tech: This team used Node.js with Scholarly for scraping, Node.js with Electron for Desktop applications (Windows and Linux), HTML, CSS, and JavaScript for the frontend with Graphviz for the graph visualizations. The students learned so much about GitHub, working on a cloud based environment, and testing code.

This project was incredibly complex with so many layers and data involved, you should watch the tech talk: 


Amy Ghotra, Smilte Valasinaite, and Zarrin Ali mentored by Tim Van Cleave:

Photographers have an incredibly difficult time getting their work out to the world with so much competition! There are thousands upon thousands of photographers itching for a chance to be discovered – but there isn’t a set community for them to connect with each other, showcase their portfolios, and provide critique or receive it. That’s where Krino comes in! This web application allows users to upload their photos with descriptions of the tech they used and camera settings as well as engage with other photographer portfolios.

Let’s talk tech: This team used React for the frontend/UI and for the backend the Django Rest Framework as well as the Pusher Channels API for the real-time comments. For the external cloud storage to upload images (and create beautiful profiles), they used Amazon S3 simple storage service. The students learned how to collaborate remotely using Slack, agile development, how to organize and test code, and segmentation of project tasks. The strong teamwork resulted in a great finished product that really shows how passionate they were about their project. 

This project definitely captured our attention (see what I did there?) which makes this tech talk absolutely worth a watch: 


May Fulop, James Kerrane, and Jonathan Abraham mentored by Saharsh Yeruva:

altML is a chrome extension that uses machine learning to generate image captions for websites that don’t have them (that alt text we all forget about!). This project was created with disabled people in mind who have vision impairment or blindness and have to have screen-readers vocalize content when browsing the web. When alt attributes or alt text is missing from a photo, the screen readers simply just say “image”, which is not helpful in the slightest! AltML takes images with these missing attributes and generates them in real time.

Let’s talk tech: This team used many technologies including Python, Numpy, TensorFlow, Keras, nltk, PIL, Matplotlib, and tqdm. They created an apache web server on a virtual machine instance using Google Cloud’s compute engine. There is also a php script that would run the model, generate a caption, and then send the https response. There are multiple options for generating the alt text, and this was just one of them! The students learned about how to use the Google Cloud platform and the variety of tools that are readily available to them. They also learned about how to better communicate as a team and setting realistic goals and deadlines to see the project to completion. 

This extension is open-source and anyone can fine-tune it or work on it! Check out the tech talk: 

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