Canada
Hey! I'm an iOS software engineer at Lyft. Here's a brief overview of my experiences to save you some time: Work experience: - iOS SWE @ Lyft (Applied AI team) - iOS Research Assistant @ UWaterloo (unsupervised topic modeling) - iOS SWE intern @ Lyft (look up 'Price Lock') - SDE intern @ Manulife (data engineering & automation) - iOS SWE @ Hafiz (NLP, signal processing, optimization) - SWE intern @ Magna (embedded systems) Extracurriculars: - AI Researcher @ WAT.ai (ML for diabetes management) - Co-Founder @ LaurierFlow (university site - 150,000+ visits) Top Projects: - Diabud iOS App (diabetes management app) - Diabud Apple Watch App (corresponding watchOS app) - ReceiptVault (HackTheGlobe 2023, digital receipt storage) - Chess with AI (my blood sweat and tears went into this one)
Overview: An unsupervised topic modeling pipeline for social media in Swift, supporting data collection, document encoding, dimensionality reduction, and clustering. The goal of this research is to provide a modular and efficient set of unsupervised topic modeling tools that work across MacOS and Linux. My work: - Optimized large-scale document encoding by integrating CoreML batch predictions via MLBatchProvider with concurrent processing, leveraging Apple’s Neural Engine to achieve a 14.4% reduction in total processing time
Partnership with Gluroo Causal Modeling and Time Series Representation Learning for Diabetes Management Overview: This project focuses on improving short-term prandial (meal-time) and postprandial blood glucose outcomes for people with type 1 diabetes, a complex disease that affects nearly 10 million people worldwide. We aim to leverage semi-supervised learning to identify unlabelled meals in time-series blood glucose data, develop meal-scoring functions, and explore causal machine-learning techniques. My work: - Implemented entropy-based agglomerative clustering (EAgglo) to detect multiple change points in time-series blood glucose data, enhancing the identification of meal-induced glucose fluctuations and improving segmentation accuracy
- Cofounded a university website for course and professor reviews, amassing over 70,000 visits - Engineered and maintained end-to-end authentication systems, including user registration, login, password resets, and security protocols - Implemented server-side authentication flows using OAuth code exchange within a Typescript and Next.js environment, leveraging Supabase for user session management and security - Developed responsive frontend modals and components using React for client-side dynamics, optimizing usability
Memberships & Loyalty - Built and owned the iOS Price Lock edit flow for the Memberships team, which resolved 55% of support tickets - Integrated a unidirectional data flow (TCA) in Swift for enhanced state management and effect handling - Increased test coverage by 17% through the use of XCTest, including unit tests, mock flows, and snapshot testing, while applying dependency injection to streamline testing processes - Developed IDL (Protocol Buffers) for the feature, reducing the payload by 20% and ensuring backward compatibility - Refactored a key area of the app to integrate map functionality, restructuring core architecture and routing