Developed and evaluated a wearable device that helps people connect in person using social-media-inspired visual signals.

• Prototyped the concept through paper sketches and Figma before building functional hardware end-to-end.
• Switched from BLE/WiFi to NFC to simplify setup, and used visual feedback to communicate system state at a glance.
• Designed and ran a two-part study (usability testing and an IRB-approved behavioral study), and analyzed results using nonparametric statistical methods, finding people were more willing to start conversations and felt a significantly stronger desire to reconnect with people they had met when using the device (p = .011).
• Refined the design across multiple iterations, cutting setup time by 83% and reaching 100% task completion in testing.

Developed an app-store-like platform for engineers and developers to browse, customize, and connect hardware devices through a browser-based interface for live control and data exchange with an embedded AI Assistant.

• Connected hardware (sensors, cameras, and microcontrollers) to a web interface for live control and data exchange using BLE, WebSocket, and serial communication.
• Designed and embedded an AI assistant directly into the platform using JavaScript, PyScript, and OpenAI's API.
• Designed the app store's architecture and visual design, defining consistency and APIs that could scale across a growing library.
• Iterated on the design through ongoing developer feedback and prototype testing in Figma and live browsers.

Designed and built a screen-free toy teaching kids computational thinking through play: a "magic mailbox" that kids interact with to customize their stuffed animal.

• Used signal strength (RSSI) to detect which stuffed animal was placed inside the box and automatically pair with it, replacing screen-based pairing selection.
• Built a multi-device system where several embedded boards communicated with each other in real time.
• Tested the toy with kids and used their behavior and feedback to refine how the interaction worked.

Completed medical device Human Factors Engineering projects spanning usability testing, UI requirements, and regulatory-compliant warning and alarm design.

• Completed a four-month anatomy and cadaver lab to ground design decisions in real clinical context.
• Conducted formative usability tests of a glucose meter, producing a full test protocol and design recommendations.
• Designed alarms and warnings for medical devices per IEC 60601-1-8 and ANSI Z535 standards.

Trained students on fabrication equipment and advised on manufacturability throughout the prototyping process.

• Trained students on mills, laser cutters, waterjet systems, and additive manufacturing equipment such as 3D printers.
• Advised on materials, tolerances, and fabrication methods to improve prototype manufacturability.
• Reviewed CAD models for design issues before fabrication, catching problems early in the process.

Conducted EEG and fNIRS research and developed MATLAB/R algorithms modeling hippocampal dopamine activity.

• Conducted EEG and fNIRS research on human subjects, including data collection, preprocessing, and analysis.
• Developed algorithms in MATLAB and R to model hippocampal dopamine activity based on experimental data.
• Collaborated with a multidisciplinary team to interpret results and refine research questions.

Designed experimental systems and simulation tools to study programmable polymer mechanics and self-assembling structures.

• Designed and fabricated experimental systems to study programmable polymer mechanics at macro scale.
• Developed Python-based 3D simulation tools to model self-assembling structures and analyze kinematics.