01

Visa Installments

Buy-now-pay-later, reimagined inside the card you already carry. No new app, no new lender, no new checkout.

Visa Director of Product Payments & Fintech Commercialization Global Scale

The Opportunity

Buy-now-pay-later exploded, but it fragmented the checkout. Every merchant bolted on a different third-party lender, every consumer juggled a new app and a new credit decision, and issuers watched balances walk off their own cards. The insight: the installment plan didn't need a new player. It needed to live inside the Visa card the consumer already had, usable across millions of merchants with nothing new to download or apply for.

What I Led

Led commercialization for Visa Installments, the productized installment capability that turns an existing Visa card into a flexible-payment instrument at checkout. Owned how the product reached the market: the merchant and issuer adoption motion, the customer experience standards, and the brand and integration guidelines partners build against worldwide.

How I Built It

Defined the end-to-end customer experience across every entry point, from product-listing awareness to card-on-file and guest checkout to point-of-sale, so installments feel native to the merchant's own flow rather than a bolt-on Authored the brand and experience standards (Visa Installments Brand Standards, Jan 2026) that issuers, acquirers, and merchants implement against, keeping the experience consistent and compliant at global scale Drove the commercialization motion across the two-sided market, aligning issuer enablement with merchant integration so supply and demand activated together Balanced regulatory disclosure, eligibility messaging, and conversion, surfacing installment availability early in the journey without cluttering the path to purchase

Outcome

A standardized installment experience embeddable across the Visa network, giving consumers flexible payments inside a card they already trust and giving issuers a way to keep installment balances on their own books. The eCom card-on-file flow shown here is the reference experience partners build to.

View the Visa Installments brand standards

02

Redesigning Amazon Rufus

AI that recommends without reasoning doesn't build confidence. It transfers the work.

Georgia Tech MS AI HCI Research AI Trust Design Conversational UX

The Problem

Amazon Rufus returns a shortlist. It doesn't explain the shortlist. Users can't determine whether results are ranked by reviews, by margin, or by algorithm, so the AI creates a new decision to make rather than eliminating one. The failure isn't the technology. It's a product design choice to omit reasoning, and it's costing Rufus the trust that would make it actually useful.

What I Led

Led the full research and design lifecycle end-to-end. Defined the research hypothesis, set the design strategy across three competing prototype directions, synthesized two rounds of evaluation into a final high-fidelity solution, and delivered documentation at publication quality.

How I Built It

Structured needfinding: user surveys on shopping behavior plus a rigorous heuristic evaluation of the live Rufus interface against Nielsen's 10 usability principles Framed three distinct design hypotheses (transparency in output, constraint-setting before results, guided comparison after results) and built a low-fi prototype for each Ran structured evaluations with 18 participants to isolate which intervention had the highest impact on perceived trust and decision confidence Synthesized across all three into a single high-fidelity design: transparent recommendation cards with visible ranking criteria, a lightweight pre-search intake form, and an optional guided decision flow for high-consideration purchases

Outcome

A high-fidelity prototype that makes AI reasoning visible at the point of recommendation, reducing the trust gap that drives abandonment and turning Rufus from a list-generator into a genuine decision-support tool.

Read the full report

03

Redesigning Amazon Alexa's Smart Home Interface

A list of devices doesn't tell you where they live. A floor plan does.

Georgia Tech MS AI HCI Research Spatial UX IoT Design Team Project

The Problem

Amazon Alexa's app organizes smart devices as a flat list of text labels. But users think in rooms and physical spaces, not spreadsheet rows. 52% of surveyed users rated the app poor at reflecting their home's layout, and only 19% found it easy to locate a specific device. The interface forces a mental translation between the digital and physical that shouldn't exist.

What I Led

Set the design direction and research strategy for the team. Defined the spatial redesign thesis, shaped the methodology across needfinding, surveys, and heuristic evaluation, and directed how findings translated into the final prototype. The team executed against that direction.

How I Built It

Needfinding across three methods: a 25-person survey, 5 semi-structured interviews, and a heuristic evaluation of the live Alexa iOS app against Nielsen's 10 + 3 spatial principles Three competing design alternatives: an interactive floor plan view, a diagnostic signal hub with WiFi heatmap, and a hybrid room-list interface Evaluated by 9 participants (Prototype 1 scored M=4.44 vs M=3.62 and M=3.50 for the others), leading to a clear direction for the high-fidelity build Final prototype: spatial floor plan as the primary UI, device status overlaid directly on the map, drag-to-move icons, routine previewing on the floor plan, and a signal heatmap for connectivity diagnostics

Outcome

Final evaluation with 24 participants: Q1 (ease of finding devices without text labels) scored M=4.67 with every participant rating 4 or 5. t(23)=16.97, p<0.001. A spatial-first interface eliminates the naming burden that makes today's smart home apps frustrating to maintain.

04

Ambria

ICU nurses shouldn't have to manually measure what machines can monitor continuously.

Penn Medicine Co-Founder + Product Lead Medical Device 0 to 1

The Problem

Urine output is one of the most critical signals in an ICU, a leading indicator of shock, kidney failure, and fluid imbalance. Yet in most hospitals, nurses still measure it manually, every hour, for every catheterized patient. The process is inaccurate, biohazardous, and occupies time that should be spent on higher-acuity care. Physicians make decisions on data they know is unreliable. The gap between what's clinically needed and what the workflow delivers is enormous.

What I Led

Founded and led the product from clinical insight to commercialization. Set the strategic vision, identified the opportunity inside Penn Medicine's MICU, and drove every decision across research, design, and the business case for Penn Medicine's innovation pipeline — from bedside observation through IP transfer.

How I Built It

Embedded in Penn Medicine MICU wards to observe the workflow firsthand. The problem was far more systemic than initially framed by clinical staff Interviewed nurses, intensivists, and hospital administrators to map pain across the full care team, not just the bedside Identified that the core failure was the measurement-disposal loop: inaccurate data entry, biohazard exposure, and EHR fragmentation all stemmed from the same broken process Designed an integrated device with automated continuous measurement, spill-free disposal, one-touch bag removal, direct EMR connectivity, and configurable clinical alarms Created go-to-market strategy and business case anchored to hard savings per ICU deployment

Outcome

80% reduction in urine disposal time. $98,100 in annual savings per ICU. All IP transferred to University of Pennsylvania. Ambria is currently in refinement at Penn Medicine Innovation Center on the FDA approval pathway.

05

Duolyfe

The productivity market solved for doing more. Nobody solved for stopping.

Founder Consumer App 0 to 1 Behavioral Design

The Problem

COVID didn't just move work home. It eliminated every environmental cue that told people to stop working. The commute, the colleague leaving, the physical context switch: gone. 100,000+ productivity apps existed to help people work more efficiently. None existed to help them stop. The market had built entirely in one direction, and the behavioral gap it left behind was real and measurable.

What I Led

Founded Duolyfe and defined the product direction from zero. Set the behavioral model that became the core of the product thesis, made every strategic call from initial hypothesis to working prototype, and directed a two-engineer team toward MVP.

How I Built It

15 user interviews and 100+ surveys, not to validate the problem (which was obvious) but to understand the mechanism: why don't people stop even when they want to? Core insight: it wasn't a time problem or a willpower problem. It was a motivation vacuum: people lacked an intrinsic reason to invest in their personal time Reframed the design challenge: don't block work, create pull toward life. The solution needed to generate its own motivation, not borrow from willpower 5 design iterations from paper prototypes to high-fidelity Figma, testing engagement models across habit tracking, social accountability, and companion mechanics Applied RICE framework to scope MVP: prioritized the Buddy mechanic above all others as the highest-engagement, lowest-complexity path to the core behavior change

Outcome

Shipped a virtual companion, the "Buddy", whose wellbeing mirrors the user's own self-care. Take a walk, your buddy thrives. Skip dinner, it shows. Built extrinsic accountability that creates intrinsic habit change. MVP in development for Play Store launch.

Chapter Two

Before AI Came Into My Life

A decade of hardware, industrial design, and 0-to-1 startups. Back when I was building things you could hold.

06

Keriton

NICU nurses were hand-labelling breast milk bottles. We automated the entire flow.

Product Designer Medical Device Hardware NICU

The Problem

In NICUs, nurses manually track pumped breast milk inventory, recipes, and feeding order across dozens of patients. The process is slow, error-prone, and happens in a setting where mistakes have real consequences for the most vulnerable patients in the hospital.

What I Built

A fully automated hardware system that tracks bottle inventory, recipes, and feeding order at the bedside, replacing the manual labelling workflow with a single device integrated into the nurse's existing routine.

Outcome

13,520 nurse hours saved per year. $432K in annual hospital savings per facility. A clean reduction in cognitive load on the team caring for the smallest patients in the hospital.

07

Nouvair

Range hoods catch 30% of smoke. Nouvair catches 80%, at a tenth of the energy.

Product Design Lead 0 to 1 Consumer Hardware Sustainability

The Problem

Most range hoods are mounted too far from the stove to actually work. They capture under 30% of cooking smoke and pollutants while drawing 300 to 1,800 watts of power. Decades of bad placement priced as a feature.

What I Built

A portable cooking hood that sits closer to the source, captures 80%+ of smoke and pollutants, runs at less than a tenth of the energy draw, and routes air through a 4-layer filtration system for odor and particulate removal.

Outcome

The world's most effective, energy-efficient, quiet, and affordable kitchen exhaust hood. Productized end-to-end from form factor through manufacturing-ready design.

08

rePod

72% of workers want a nap at work. 9% have access. rePod bridges the gap.

Product Designer 0 to 1 Workplace Consumer Hardware

The Problem

Post-lunch fatigue is universal, well-documented, and silently expensive. 51% of workplace productivity loss is attributed to fatigue, yet only 9% of offices offer any form of rest space. The default fix is caffeine and apologies.

What I Built

The world's first self-service resting pod for shared office spaces. A private, bookable nap unit that fits standard floor plans and operates without staff intervention, designed to slot into existing office leases.

Outcome

A productized solution for an unmet workplace need. Targets the 51% productivity loss with a single piece of furniture-grade hardware.

09

Everwaters

Clean drinking water using a seed that already grows where it's needed most.

Product Designer Social Impact Kenya Market Sustainable Design

The Problem

Affordable clean water remains out of reach in much of the world. Conventional purifiers depend on either grid infrastructure or replaceable cartridges, neither of which works in resource-constrained communities.

What I Built

A water purifier for the Kenyan market built around Moringa Oleifera, a naturally occurring plant seed with proven purification properties. Designed the full package end-to-end, from die-line to manufacturing.

Outcome

A purifier that runs on locally sourced inputs, removing the supply chain dependency that makes traditional water tech inaccessible to the people who need it most.