Scaling research into systems that drive product decisions and business impact.
Focused on ResearchOps, AI-enabled workflows, and embedding research into product strategy across complex enterprise environments.
AI changes the nature of the product. The experience is defined less by features alone and more by how the system behaves within a workflow.
The shift is no longer just about what AI can do. It is about how people interact with it, when the system should recommend, when it should ask for input, and how it should explain its reasoning in ways that build trust and improve outcomes.
UX Research creates value when it scales beyond individual studies into systems that inform product decisions.
My approach focuses on building research programs, integrating AI into workflows, and designing systems that increase the reach and impact of research.
Led a centralized research program across 9–15 product teams, scaling discovery and synthesizing insights into a unified product direction.
"Large-scale usability testing conducted during OpenText World, enabling rapid feedback collection across multiple product teams."
Implemented AI-assisted workflows that reduced synthesis time by 40% while improving consistency across qualitative research.
"AI-assisted qualitative analysis, highlighting themes and accelerating insight generation from research sessions."
Designed a ResearchOps platform to centralize participants, projects, and artifacts—improving visibility and coordination across research activities.
"Centralized ResearchOps platform supporting participant management, project tracking, and cross-team research visibility at scale."
"Leadership is not just about managing projects; it's about operationalizing empathy and intelligence to make better bets on the future."
With over a decade of experience in UX leadership, I focus on the intersection of human behavior and business strategy. My approach is rooted in the belief that research should be a continuous operational engine, not a series of one-off projects.
I specialize in building ResearchOps systems that empower researchers to do their best work and product teams to make decisions with confidence. Currently, I am deeply involved in how generative AI can augment the research lifecycle—from accelerating transcription and tagging to uncovering deep semantic patterns in global datasets.
Systemizing discovery processes to ensure user insights drive every stage of the PDLC, from visioning to shipment.
Developing ethical and efficient AI workflows for research synthesis, sentiment analysis, and predictive modeling.
Partnering on AI experience strategy, product design, and systems for complex enterprise workflows.