Work

I returned to NextEra Energy's HumanITy team as a second-year intern to lead user research for the redesign of an internal sales platform. The platform helps NextEra sales representatives show Commercial & Industrial (C&I) customers where they stand in the energy market and make better-informed purchasing decisions. Once launched, it will be used by thousands of customers across the U.S.

This was a real stakeholder project bridging Cybersecurity, Sales, and IT. I ran 18+ user interviews and usability tests with NextEra sales reps to understand how they worked today, mapped user journeys and process maps to find workflow pain points and opportunities, and audited 4+ screens with heuristic evaluation. To cut the time that evaluation took, I interviewed 8+ UX designers and engineered an AI heuristic evaluation agent that scores a screen in 14 seconds versus 6 hours manually, giving designers a fast baseline so they spend less time on rote scoring. I earned a Six Sigma Yellow Belt for streamlining that process through AI-driven scoring and process improvement.

During my human-centered design internship I worked on HumanITy, NextEra Energy's in-house UX and experience architecture team, partnering with cybersecurity to improve how employees handle phishing emails that slip past the company firewall. NextEra blocks roughly 330 million phishing emails a year; this app covers what gets through.

I redesigned a company-wide app that quarantines suspicious emails and surfaces key details about their content, so employees can preview a message safely, decide whether to request a release through IT support, and track that request's status. Because the previous version carried unnecessary features and weak flows, my focus was refining the experience, building on the earlier designer's research within a tight timeline. Some specifics stay confidential, but the approach and skills are open for discussion.

Lasso Loop builds smart appliances that clean, process, and sort recyclable materials at home, creating a closed-loop system where items are collected pure and ready to reuse. The product needed a clearer way to show recycling metrics without overwhelming people with data.

I designed the metrics in an approachable, digestible way, translating data into real-world comparisons like recycled weight in familiar terms, and simplifying appliance status into actionable insights such as percentage changes and fullness levels for glass, plastics, and metals. Impact-driven messaging highlights the environmental outcome, so people understand their contribution and stay motivated to keep recycling.

Mia is an AI-powered schedule-building interface for University of Michigan students that simplifies class scheduling. It integrates UMich course requirements (major, minor, and expected graduation date) and uses them to recommend which classes to take and how they map to a student's academic goals.

The project was completed during a fast-paced 24-hour design jam focused on creating, designing, and marketing a unique AI platform, from concept and interface through positioning.

At Michigan, "did you find housing yet?" is a question that reliably causes anxiety. Ann Arbor housing is scarce, expensive, and often in poor condition, and accessibility or location needs add another layer. After going through it myself, I ran a semester-long independent study asking: how do out-of-state students without access to a car navigate finding on-campus housing?

I recruited five participants through screener surveys and informed consent, UMich students from out of state, without a vehicle, who had searched for Ann Arbor housing. Each 50–60 minute interview used photo elicitation, with seven images (heavy snowfall, crowded buses, tiny apartments, luxury units) to prompt deeper reflection. I then synthesized the interviews into an affinity map, a persona, and a journey map of the search from start to finish.