Architecting the next generation of audio intelligence for AI-integrated wearables. I bridge the gap between high-fidelity hardware and real-time machine learning, focusing on the deployment of low-latency audio systems that power conversational AI and spatial awareness.

Key Contributions:

• Wearable AI Systems Architecture: Spearheaded the end-to-end prototyping of audio subsystems for smart wearables, successfully integrating classical Digital Signal Processing (DSP) with modern Machine Learning (ML) to optimize speech intelligibility and environmental sensing.

• Intelligent Signal Modeling: Developed advanced distortion modeling and acoustic compensation algorithms, utilizing PyTorch and HuggingFace to simulate and mitigate hardware constraints in miniaturized form factors.

• Strategic Technical Leadership: Define technical roadmaps and engineering standards for cross-functional teams; led the transition toward AI-augmented development workflows, significantly reducing R&D cycles for real-time audio evaluation tools.

• Generative AI & LLM Integration: Pioneered "AI-first" coding and system design workflows, leveraging a sophisticated stack including Llama, Claude, and Gemini via Ollama and Opencode to automate complex system simulations and firmware prototyping.

I was instrumental in enhancing the integration of audio device prototypes at Meta, driving innovation through tool design and collaboration.

• Developed internal tools that improved the efficiency of prototype integration processes.

• Worked with cross-platform engineers to establish advanced testing environments for audio technologies (psycho-acoustic metrics, such as: evaluation of speech quality and intelligibility).

• Leveraged various hardware technologies (transducers, digital interfaces, audio ICs, and DSPs) to explore cutting-edge metaverse technologies.

I architect and develop specialized mobile applications that bridge the gap between physical sensors and intelligent computing. By moving beyond simple data logging, I focus on bringing high-performance AI and real-time processing directly to the edge.

• akous: On-Device Machine Learning (Edge AI), Diffusion Models (DiT/VAE), Digital Signal Processing (DSP), Granular Synthesis, Swift Concurrency (async/await), UI/UX Design

• Itria (On-Device AI): A privacy-first LLM and Vision-Language Model (VLM) host for iOS. Built using Apple’s Metal GPU acceleration, Itria allows for local, offline inference of state-of-the-art models (Llama 3, Phi-3, Qwen-VL), enabling secure AI-driven research and document analysis without cloud dependency.

• MotionLink (Spatial Intelligence): A precision motion-tracking tool that transforms AirPods Pro into high-fidelity head-tracking systems. It utilizes core-motion data for 3D visualization and posture analysis, providing a low-latency bridge for AR/VR developers and biomechanics researchers.

• BLExAR (IoT Connectivity): A versatile Bluetooth Low Energy (BLE) integration app for the Arduino/nRF52 ecosystem. It serves as the primary data pipeline for thousands of engineers, enabling real-time sensor plotting, GPS-synchronized data logging, and raw serial communication for rapid hardware prototyping.

NOAA Fellow recipient conducting research focused on climate and human interaction in urban areas through utilization of field experiments and numerical models. Conceptualized and created high-level products for NOAA to expand understanding of extreme heat events in urban areas. Analyzed data to better understand how momentum, energy, and mass are transported in the urban boundary layer, with the intention of targeting and mitigating the negative effects of urban climate. Formulated image processing algorithms in real time for satellite data in cities. Managed research instruments such as sonic anemometers, gas analyzers, thermal cameras, and 3D printers.

Selected Contributions:

• Adopted machine learning to produce real-time visualizations of temperature maps.

• Managed all aspects of product development from research to product deployment.

• Patented novel device—GPS-Enabled Infrared Camera with Thermocouple for Real-Time Land Surface Temperature Calibration.

• Designated as lead author on research paper published in competitive academic journal to advance innovative research focused on urban air temperature modeling.

• Awarded Best Student of the Year 2020 for academic excellence

Instructed mechanical engineering students in laboratory setting, lecturing on topics such as fluid mechanics and heat transfer. Designed curriculum and created hands-on learning environment to merge theoretical and real-world application. Advised students on how to be successful and achieve goals. Stayed updated on innovations and changes within course field.

Selected Contributions:

• Awarded 2019 Graduate Teaching Assistant Award, Mechanical Engineering Department.