I'm a Software Engineer and researcher specializing in iOS development and on-device machine learning. I love
building production mobile apps and exploring how ML can run efficiently on resource-constrained devices.
- π² 4+ years of experience in iOS development, specializing in Swift, SwiftUI, and UIKit to build apps used by millions.
- π§ Researching on-device ML deployment - published on arXiv and currently exploring Core ML patterns for production apps.
- π M.S. in Computer Science from California State University, Fullerton.
- π©βπ« Previously taught iOS Mobile Application Development to 100+ students at CSUF.
- π¬ Passionate about bridging the gap between ML research and practical mobile deployment.
- π€ Open to collaborating on iOS, Swift, and ML research projects.
- π Pronouns: She/her.
- π LLM-Enhanced Log Anomaly Detection: A Comprehensive Benchmark - arXiv:2604.12218
- π» Benchmark Code & Experiments
- βοΈ Can LLMs Replace Traditional Methods for Log Anomaly Detection? - Medium
- Languages: Swift, Python, SwiftUI, UIKit
- ML/AI: Core ML, PyTorch, scikit-learn, Transformers
- Patterns: MVVM, TDD, Clean Architecture
- Tools: Xcode, Git, CI/CD, XCTest
- βοΈ Email: disha81100@gmail.com
- πΌ LinkedIn: https://www.linkedin.com/in/diisha-patel/
- π¬ Google Scholar: https://scholar.google.com
- π¦ Twitter: https://x.com/diishapatel
