Software Engineer | UI/UX Designer | Frontend Developer
I build digital experiences from idea to product. I work across software engineering, product development, and UX, turning problems into useful, thoughtful solutions. Whether I’m designing an interface, developing an application, or exploring an AI-driven solution, I care about both how something works and how people experience it.
Leading product architecture and frontend development for an AI-powered lung auscultation platform helping physicians detect respiratory disease faster
Baguio City, Philippines.
Supported client delivery across web apps, documentation, and QA for a remote team.
A study app that instantly turns your notes and PDFs into quizzes and flashcards, featuring a virtual pet that levels up as you keep up your daily study streaks.
Lung auscultation remains highly subjective, with pulmonologists averaging only 36.5% correct detection rates. This study proposes a dual-channel CNN-LSTM architecture with a constrained MFCC-Chroma gated fusion mechanism for multi-class respiratory sound classification. HINGA V1, the first localized Filipino lung sound dataset, was collected from 51 patients across four Baguio City institutions and combined with the ICBHI 2017 benchmark. The model achieved a macro F1 of 0.4056 across six disease classes on unseen data, with the fusion mechanism consistently favoring MFCC-derived temporal features, supporting a viable path toward a clinically relevant auscultation tool for the Philippine healthcare setting.
Auscultation-based lung disease detection remains subjective and inconsistent. This study proposes two complementary approaches: a dual-channel CNN-LSTM using MFCC-Chroma fusion, and a Random Forest model incorporating patient demographic data, both evaluated on the ICBHI 2017 dataset. The CNN-LSTM models reached up to 80% accuracy, while demographic features also proved valuable for classification, offering competitive performance in accuracy, robustness, and class-wise fairness compared to prior work in the field.
This study develops a Finite State Accepter that validates Philippine vehicle and motorcycle plate numbers against the LTO's current formats (LLL DDDD, L DDD LL, DDD LLL). A consolidated automaton was built and implemented as a program, then tested against 100 valid and 50 invalid plate numbers. All valid plates were correctly accepted and all invalid plates correctly rejected, demonstrating the framework's reliability for automated plate validation.