I build reliable, human-centered AI systems that transform complex information into useful experiences. My work focuses on applied machine learning, accessible technology, adaptive interfaces, and well-tested software.
I am seeking AI/ML engineering opportunities where I can combine intelligent features with thoughtful product design, safety guardrails, evaluation, and strong software-engineering practices.
An AI-powered tactile interface designed to translate digital information into accessible haptic experiences for deafblind users. Built with Swift, a deterministic state-machine architecture, dependency injection, semantic compression concepts, and more than 310 tests.
A Streamlit application that integrates AI guidance into an interactive number game. It uses structured outputs, response validation, safety checks, deterministic fallbacks, evaluation tooling, and persistent statistics to provide reliable AI assistance.
An adaptive Java trivia application that adjusts question difficulty according to player performance. It uses min-heaps, max-heaps, priority queues, and terminal and graphical interfaces to create a personalized learning experience.
A CUDA and C++ project that compares CPU and GPU performance for vector addition, measures execution time and speedup, and verifies result correctness.
My personal portfolio featuring selected projects and additional information about my work.
- AI/ML: Applied AI systems, output validation, evaluation, guardrails, and deterministic fallbacks
- Languages: Python, Java, Swift, C++, and JavaScript
- Engineering: Automated testing, data structures, algorithms, state machines, and accessible product development
- Tools and platforms: Streamlit, CUDA, Git, GitHub, and Xcode
- Build production-minded AI applications with measurable reliability
- Explore accessible and multimodal human-computer interaction
- Strengthen my ML engineering, evaluation, and deployment skills
- Collaborate on projects with meaningful social and technical impact