Hi there! My name is Dane Payba and I am a computer science student at UCLA with a strong foundation in machine learning, artificial intelligence, and web development.
I have valuable work experience through internships at companies such as Google, KBR Inc, and Daily Bruin, where I have had the opportunity to develop scheduling software, machine learning models, and web applications.
I have also received recognition for my work, placing first in the United States Congressional App Challenge and being named the Hawaii Society of Professional Engineers Scholar.
Please feel free to reach out if you would like to connect or learn more about my experiences, thanks!
Experienced through personal projects, workshops, internships and work experiences. Utilize Python programming and tools such as TensorFlow, Keras, Pandas, and Numpy. Worked with different types of neural networks throughout my career.
Background foundation through a software engineering internship at KBR in Summer 2021. Also competed in MIT BattleCode 2021 & 2022, placing 21/510 teams of students and developers worldwide.
Proficient in JavaScript, HTML, CSS, and frameworks such as React, Express, Django. Created multiple side projects along with main work as a software engineer for the Daily Bruin.
Incoming software engineering intern for Summer 2023.
- Developed C++ software for schedulers of 1,000,000+ daily tasks to retrieve checkpoint data between time periods.
- Improved debugging efficiency for critical issues and better-analyzing resource utilization patterns in machines.
- Implemented methods to obtain 6 specialized VM attributes using remote procedure calls and protobufs (JSON).
- Created visualizations using HTML / JS displaying event changes in virtual machines through backend data retrieval.
- Programmed and deployed a remodel for over 500 daily users of the Bruinwalk website using HTML, CSS, and JS.
- Enhanced usability for users by coding the functionality to dynamically change content from backend interfaces.
- Added filter searching for amenity-based apartment searching. Remodeled landing page with interface changes.
- Analyzed model performance and text classification results through confusion matrices, heatmaps, and ROC curves.
- Implemented a neural network, naive bayes, and regression model to classify PAWS files with 99.99% accuracy.
- Developed a web application to test counting skills from 1-100 on 29 kindergarteners using speech recognition.
- Minimized latency between tasks, cutting account retrieval down to 402 ms and input validation to 1100 ms.
Built a neural network to read 2 images of handwritten text and detect plagiarism if present using TensorFlow. Improved model to read single words to 98% accuracy, lines to 67% accuracy, and plagiarism to a 76% accuracy.
Produced a client-server video chat app in React JS where users can search for songs and follow on-screen lyrics. Processed songs within 900 ms and video connection latency of 1700 ms through WebRTC and Spotify Web APIs
Developed a Tangent Bug / A* pathfinding algorithm with a limited bytecode constraint for the MIT AI competition. Worked with 2 other developers over 2 months to place 21/510 teams of MIT students and developers worldwide.
Developed an app that allows photographers to show off their work and chat with potential clients. Allows customers to browse photos taken by real photographers with the ability to connect and set up photoshoots with them.
Text editor that integrates the use of various data structures and algorithms fundamentals in C++. Supports real-time spell checking, misspelled word suggestions, file operations, and keyboard shortcuts / hotkeys.
Developed a drag race system to track times of different positions on each lane and the winner of each race. Constructed using multiple Arduino’s and electronic circuitry. Precise to the nearest hundredth of a second.