UX Researcher (Graduate Research Assistant) - University of Michigan–Dearborn - Dearborn, MI
(2024-09 - 2026-05)
Industry Partnered Projects
- Led end-to-end primary research across 4 studies (n=10–105) for Toyota Motors NA and Hyundai Mobis NA, selecting naturalistic, simulator, or remote study designs to match each team's research question and timeline, partnering directly with each company's product and engineering stakeholders throughout.
- Used naturalistic, no-probe think-aloud research to capture authentic driver reasoning in real time, then applied behavioral and sentiment analysis to convert that raw signal into 4 data-backed interface recommendations developed with Toyota's Collaborative Safety Research Center that shaped Toyota Motors NA's shift to integrated architecture
- Concept-tested in-vehicle conversational AI design variations using NLP-based analysis to identify 5 key drivers of driver alertness, directly informing Hyundai Mobis's go/no-go decision on which conversation design to advance.
- Built custom data collection interfaces for 2 studies in collaboration with Georgia Institute of Technology, standardizing LLM interaction to control variance across human-AI collaboration and moral decision-making research.
- Built a framework tracking how individual creative contribution shifts turn-by-turn in unscripted human-AI conversation, computing metrics via NLP-leveraged Python pipelines and validating 86% predictive accuracy (Decision Tree vs. expert ratings), pinpointing exactly when AI assistance shifts from supporting to replacing human input.
- Built a self-serve, customizable dashboard from a rapid literature review of 80+ papers, applying TAM frameworks to compare adoption and trust across IoT and AI-assisted product categories in assistive tech, letting management, researchers, and designers each explore the evidence and recommendations most relevant to them
- Flagged a key design risk in conversational AI, confidence inflation without better decisions, through analysis contributed to a 240-participant study, informing trust-calibration guidance for conversational AI design.
- Compiled 2 manuscripts under review (IJHCS, Computers in Human Behavior) and delivered 5 peer-reviewed conference presentations (HFES, IISE), fielding questions from expert research audiences at each.
Learning Experience & UX Coordinator - Pattison Food Group - Vancouver, Canada
(2022-11 - 2024-07)
- Led continuous discovery and accessibility-first UAT (WCAG, screen reader compatibility) for a digital learning platform used by 30,000+ learners across 11 retail banners, cutting retry rates by 82% and lifting voluntary completion to 87%.
- Diagnosed why diverse, frontline learners disengaged from onboarding content, unclear click targets, timed questions that weren't visible to screen readers, and imagery that excluded the diversity of the actual workforce, then redesigned content hierarchy and accessibility now adopted organization-wide.
- Built clickstream dashboards tracking drop-off points, pause-and-return behavior, and completion across mandatory and voluntary courses, including correlating cybersecurity training completion against real phishing-simulation click rates, to prioritize redesign of the lowest-performing content.
Product Development Associate (Consultant, Part-time) - Source Scan Agency - Gurugram, India
(2022-06 - 2024-07)
- Conducted customer discovery with agricultural end users, translating field-tested usability constraints into product requirements for a patent-pending canopy system, including a single-person installation target under 30 seconds.
- Authored end-user installation and operation manuals, translating technical product requirements into plain-language guidance for non-technical buyers.
- Represented research-backed product positioning to industry buyers, personally securing $30K+ in direct orders; the product line has since generated $300K+ in company sales to date.
