I stabilize system coherence—aligning intelligence with integrity across large, human-critical systems. When coherence holds, organizations move with more speed, safety, and strategic clarity. Then design thinking and human-centered design become the means, not the aim.
Human-centered design listens deeply, empathizes fully, and turns complexity into systems of trust, a foundational element of durable, profitable enterprise.
My approach begins with design thinking—listening first, defining the human need, and iteratively prototyping solutions that scale. It keeps the products I architect aligned with trust, mission, and measurable outcomes.
In my experience, organizations more often fail when connection breaks between people, process, and purpose than from a lack of talent or technology. My role is to rebuild that connection—to make intelligence human again. Trust, truth, and clarity aren't luxuries; they're among the most reliable routes to sustainable growth.
Design thinking isn't about decoration; it's about discovering truth in how systems actually function for people. Human-centered design begins where systems forget people. It listens, observes, and reframes until solutions mirror real human need. When that alignment happens, trust turns into velocity—decisions accelerate, silos soften, and technology starts to serve rather than dictate.
I treat every system—policy, platform, or product—as a living ecosystem of intelligence and intent. My work restores coherence between the two so actions, interfaces, and outputs consistently reinforce trust. Because shared truth is one of the fastest ways to accelerate decision-making, accuracy, alignment, and cohesion.
The examples below show how alignment between people, systems, and AI becomes measurable performance. Each project highlights a different layer of coherence—from data integrity to human clarity—demonstrating how design turns complexity into capability.
Enterprise Data Provenance Visibility & Human-in-the-Loop Oversight
Interface integration of NLP-generated query → source → answer visibility, and a human-centered RAG chat interface for postal operations, accountability dashboards, and audit-policy integration (enterprise, 2023–2025)
Goal: Deliver auditable, human-centered insight across finance and operations workflows—leveraging existing NLP and RAG capabilities to provide accountable, source-linked answers in real time.
Role: UX Architect for Data-Driven Systems—aligned the presentation of NLP-generated outputs with human workflow, established human-in-the-loop checkpoints, and prototyped a traceable, user-facing RAG chat workflow and interface in R Shiny.
Accomplished: Integrated dashboards and UI components to surface NLP-generated outputs within multi-source accounting workflows. Embedded user-facing oversight checkpoints, provenance visibility, and decision accountability that increased clarity and confidence for leadership.
- Human-Centered Systems
- AI-Integrated Design
- UX Architecture
- Design Thinking
- System Design
- Operational Flow & Quality
- Data Ethics & Governance
- Accessibility & Inclusion
- Trust Engineering
- Human Stewardship
If your data teams need visibility, auditability, and responsible AI oversight, let's build your next prototype.
Angular upgrade, performance, and UX hardening—reduced map interaction lag (p95) and improved build stability for mission-critical releases (2023).
Goal: Strengthen reliability and clarity in a mission-critical geospatial web application through framework upgrades and refined interaction patterns.
Role: Front-End Developer / UX Partner—upgraded Angular v14 → v16, improved responsiveness, reduced technical debt, and stabilized map controls for accurate, real-time use.
Accomplished: Achieved measurable UX and performance gains, faster builds, and clearer component structure—ensuring dependable operation under live mission conditions.
If your mission systems need to modernize legacy frameworks without sacrificing stability or user confidence, let's upgrade them together.
Human-Centered Design lead across enterprise workflows—produced service blueprints that clarified ownership, reduced escalations, and aligned policy with delivery (2021–2023).
Goal: Translate complex HR and policy workflows into accessible, scalable digital operations suitable for low-bandwidth and high-security environments.
Role: Human-centered design lead—conducted 75+ interviews, mapped service journeys, and aligned cross-functional teams to reconnect product intent with operational reality.
Accomplished: Delivered UX roadmaps and service blueprints that removed ambiguity between policy and execution—strengthening institutional trust and operational flow.
- Human-Centered Systems
- UX Architecture
- Design Thinking
- System Design
- Operational Flow & Quality
- Data Ethics & Governance
- Accessibility & Inclusion
- Trust Engineering
- Human Stewardship
If you need to bring policy, process, and people into a single auditable workflow, let's architect the transformation.
Modernized five financial applications through a unified Angular 9 component library—reducing duplication and enabling consistent, faster feature rollout (2017–2020).
Goal: Modernize and unify financial workflows by migrating legacy applications into a scalable Angular 9 platform—improving usability and delivery velocity across customer-facing systems.
Role: UX Architect & Front-End Systems Designer—integrated the design system directly into the Angular stack, aligning UX and engineering through live prototyping and behavior-based validation.
Accomplished: Designed, structured, and modularized the user-facing Angular component library for rapid deployment across five core applications (Loan, Line of Credit, Point of Sale, Title Loan, Collections). Reduced friction, increased completion rates, and enabled analytics for continuous improvement—demonstrating how coherent design systems translate usability into business velocity.
- Human-Centered Systems
- UX Architecture
- Design Thinking
- System Design
- Operational Flow & Quality
- Data Ethics & Governance
- Accessibility & Inclusion
- Trust Engineering
- Human Stewardship
If your platform needs a scalable design framework that accelerates delivery and strengthens trust, let's design your next-generation system.
Each case above points to the same pattern: when systems realign around people, clarity increases—and speed often follows. Trust is not sentiment; it is an operational advantage.
I design systems where intelligence, workflow, and human judgment reinforce each other—so decisions move cleanly, accountability is visible, and teams can act with confidence.
What follows is the operating model behind the results.
Each discipline reinforces the others. Together, they create systems where intent, action, and outcome stay aligned—so trust scales instead of eroding under complexity.
Designing policy, data, workflow, and interface ecosystems around real human constraints.
Industry Standard: Service design and systems thinking (IDEO, IBM Enterprise Design Thinking) emphasize empathy, mapping, and visibility.
My Implementation: These principles are embedded directly into workflows, interface structures, and the human-facing view of the data context so every decision path is visible and auditable.
Outcome: Decisions become easier to explain. Automation can be made safer. Escalation cycles shorten. Alignment becomes more repeatable.
Bringing model outputs into the flow of work with provenance, oversight gates, and fallback paths. Query → source → answer stays visible end-to-end.
Industry Standard: Explainable AI (XAI), the National Institute of Standards and Technology (NIST) AI Risk Management Framework, and Defense Advanced Research Projects Agency (DARPA) “third-wave” AI all emphasize visibility and accountability.
My Implementation: Human-in-the-loop checkpoints and visible data lineage are surfaced at the interface and workflow levels (using existing model outputs and data services) and in prototypes, so AI augments rather than obscures judgment.
Outcome: Confidence increases. Compliance risk drops. AI outputs become easier to explain, defend, and trust operationally.
The structural layer that aligns product intent, data meaning and structure, navigation, semantics, and accessibility—so teams can move fast without losing trust or context.
Industry Standard: Information Architecture and atomic design systems guide structure, hierarchy, and component consistency.
My Implementation: Design tokens, accessibility rules, and semantic components are implemented directly within the design-to-interface workflow (Angular, React) to keep design and engineering aligned.
Outcome: More predictable builds, reduced design drift, and a shared language across product, design, and engineering.
A disciplined loop of listening, framing, prototyping, and testing that turns ambiguity into buildable decisions.
Industry Standard: IDEO and Stanford d.school frameworks: Empathize → Define → Ideate → Prototype → Test.
My Implementation: I run the loop at enterprise scale—replacing static requirements with continuous, evidence-driven iteration.
Outcome: Faster discovery-to-delivery cycles and visibly higher adoption across users and leadership.
Mapping how technology, people, and process interact—so systems reinforce clarity rather than conflict.
Industry Standard: Systems theory (Meadows) and enterprise architecture frameworks such as The Open Group Architecture Framework (TOGAF).
My Implementation: I map human-centered feedback loops and dependencies early—anticipating downstream effects before interface, policy, or workflow changes occur.
Outcome: Coherence scales more reliably. Teams avoid fragmentation more often, rework drops, and core structures remain stable as complexity grows.
Reducing waste, variation, and ambiguity—so teams deliver faster with fewer defects.
Industry Standard: Lean removes non-value work; Six Sigma reduces variation through DMAIC (Define, Measure, Analyze, Improve, Control). Both emphasize measurable outcomes and repeatable improvement cycles.
My Implementation: I integrate these principles within UX architecture and system design: clear framing, baseline measurement, root-cause analysis, and user-validated countermeasures—reinforced by visible controls in the workflow.
In Practice:
- Define → Measure → Improve for RAG interface clarity & user-facing auditability
- Cycle time & p95 latency reduction in map UX
- Defect prevention through blueprint handoffs
- Design-system reuse to reduce waste
Outcome: Clearer accountability, fewer escalations, and faster decision loops. When flow is visible and variation is controlled, trust and velocity rise together.
Ensuring data is collected, stored, and applied in ways that respect privacy, equity, and intent.
Industry Standard: General Data Protection Regulation (GDPR), NIST Privacy Framework, and ISO/IEC 27001.
My Implementation: I translate policy into interface-level clarity—so ethical handling isn't hidden in documentation, but visible in how the system behaves.
Outcome: Compliance becomes natural to the workflow. Transparency increases. Trust strengthens.
Designing systems that support every cognitive and physical mode of interaction.
Industry Standard: Web Content Accessibility Guidelines (WCAG) 2.2, Section 508, and inclusive design heuristics.
My Implementation: Accessibility is designed into structure, flow, and contrast from the start—not audited in at the end.
Outcome: Wider usability, reduced legal exposure, and consistently higher trust and satisfaction across user groups.
The alignment of human judgment, visible safeguards, and operational clarity—so reliability is visible, not assumed.
Industry Standard: Rooted in safety-critical system design across aviation, defense, and regulated financial systems.
My Implementation: I treat trust as a measurable system property—shaping how transparency, feedback loops, and explainability appear in the interface and user-facing workflow.
Outcome: Stakeholders don't ask “Can we trust it?” — they ask “How fast can we scale it?”
Understanding systems deeply enough that people no longer have to be harmed by them in the normal course of work. So the organization can grow through alignment instead of fear.
Industry Standard: Emerging in adaptive workforce intelligence, talent ecosystems, AI-assisted internal mobility, and humane enterprise design—where companies shift from reactive reduction to proactive stewardship of human potential.
My Implementation: I surface where fear is quietly driving decisions and replace it with system clarity—mapping strengths, forecasting risk early, and designing structures where people can move, grow, and contribute without becoming collateral damage.
Outcome: Leaders stop treating layoffs as the only lever. The organization becomes capable of changing and scaling without breaking the people who keep it alive.