Kaushal Ramesh
Software Development Engineer
About Me
I'm a Computer Science student at UC Santa Cruz with a perfect 4.0 GPA, passionate about software development and machine learning. With experience at Amazon, Imago.AI, and Cisco, I've developed strong skills in both frontend and backend development, as well as machine learning applications.
Education
University of California, Santa Cruz
Bachelor of Science in Computer Science
Expected June 2025 | GPA: 4.0/4.0
Skills
My Projects
Portfolio Website
A modern, interactive portfolio website with 3D animations and smooth transitions.
- Implemented 3D particle animations using Three.js for an engaging user experience
- Created responsive and accessible design with glassmorphism effects
- Built with modern React practices and smooth animations using Framer Motion
Splitmate
A web application for managing shared expenses and group finances.
- Designed and implemented a web application utilizing React.js for a dynamic user experience and Node.js for robust backend functionality
- Utilized Kanban methodology to accelerate project planning and development times by 30%
Analytics Engine
A comprehensive data analysis and machine learning platform.
- Analyzed 50,000+ data points, tackling incomplete and corrupted data by applying RegEx matching and One Hot Encoding
- Created various machine learning models, making use of K-Nearest Neighbor and Decision Tree algorithms to predict future trends with up to 99% accuracy
- Authored a 16-page report on strategic applications, employing intricate Matplotlib visualizations
Experience
Software Development Engineering Intern
Worked on automating ticket intake system and improving backend performance.
- • Developed CRUD APIs using Java to automate the ticket intake system, reducing developer TTR by over 85%
- • Utilized DynamoDB, Lambda, CloudFront, and API Gateway to redesign the backend system, achieving $50,000+ cost reduction
- • Conducted system improvements, decreasing network RTT by 20% and bandwidth consumption by 15%
- • Enhanced DynamoDB table performance via indexing and query refactoring, leading to 90ms reduction in data retrieval times
Machine Learning Engineering Intern
Focused on improving ML models for Mycotoxin classification and detection.
- • Used TensorFlow and PyTorch to develop and train KNN and CNN models, increasing accuracy by 25%
- • Performed data enhancement with 1,000+ new microbial samples, resulting in 68% increase in model accuracy
- • Conducted training camps for investors and clients, improving brand image by 40%
STEM Shadow Program
Developed data processing and visualization solutions.
- • Leveraged NumPy and InfluxDB API for data transformation, achieving 92% reduction in processing time
- • Built a responsive dashboard supporting 500+ data points with 9,000 records per second throughput
Get in Touch
Feel free to reach out for collaborations or just a friendly hello