Yang Xing, PhD

Senior UX Researcher & Product Strategist

I study how people perceive and interact with the world, then apply those insights to build better products.

UX Research

At Kardder, I led mixed-methods research across successive product iterations, culminating in a social discovery platform designed to connect people within their communities through shared experiences in real time. The selected work presented here highlights research that helped identify emerging user needs and shape product strategy across onboarding, user profiles, discovery, and events through experimentation and post-launch measurement.

Removing Forced Decisions Increased Engagement

2.6× more profile views • 2.1× more sessions • +22% chat conversion • +18% profile visits/session

An A/B test followed by 120-day telemetry validation showed that free browsing increased exploration and chat conversion while preserving connection-request activity.

METHODS | Interviews · A/B Testing · Bootstrap CIs · Post-Rollout Behavioral Analysis

Removing Forced Decisions Increased Engagement

2.6× more profile views • 2.1× more sessions • +22% chat conversion • +18% profile visits/session

An A/B test followed by 120-day telemetry validation showed that free browsing increased exploration and chat conversion while preserving connection-request activity.

METHODS | Interviews · A/B Testing · Bootstrap CIs · Post-Rollout Behavioral Analysis

Removing Forced Decisions Increased Engagement

2.6× more profile views • 2.1× more sessions • +22% chat conversion • +18% profile visits/session

An A/B test followed by 120-day telemetry validation showed that free browsing increased exploration and chat conversion while preserving connection-request activity.

METHODS | Interviews · A/B Testing · Bootstrap CIs · Post-Rollout Behavioral Analysis

Prioritizing Profile Features Using MaxDiff Tradeoff Modeling

16+ weeks of development saved • 115 participants • 1,035 best-worst evaluations • 12 profile attributes modeled

A controlled MaxDiff study quantified a stable feature hierarchy, showing that foundational identity signals consistently outperformed rich media profile features.

METHODS | MaxDiff Experiment · Survey Design · Chi-Square Validation · Bootstrap Analysis

Prioritizing Profile Features Using MaxDiff Tradeoff Modeling

16+ weeks of development saved • 115 participants • 1,035 best-worst evaluations • 12 profile attributes modeled

A controlled MaxDiff study quantified a stable feature hierarchy, showing that foundational identity signals consistently outperformed rich media profile features.

METHODS | MaxDiff Experiment · Survey Design · Chi-Square Validation · Bootstrap Analysis

Prioritizing Profile Features Using MaxDiff Tradeoff Modeling

16+ weeks of development saved • 115 participants • 1,035 best-worst evaluations • 12 profile attributes modeled

A controlled MaxDiff study quantified a stable feature hierarchy, showing that foundational identity signals consistently outperformed rich media profile features.

METHODS | MaxDiff Experiment · Survey Design · Chi-Square Validation · Bootstrap Analysis

Bringing Discovery Into the Home Experience

+44% sessions reaching profiles • +45% connection acceptance • 30-day post-launch evaluation

Log-level behavioral analysis revealed that the home feed was suppressing profile exploration, resulting in a redesign that improved discovery and connection outcomes.

METHODS | Usability Testing · Log Analysis · Two-Proportion Z-Tests · Behavioral Metrics

Bringing Discovery Into the Home Experience

+44% sessions reaching profiles • +45% connection acceptance • 30-day post-launch evaluation

Log-level behavioral analysis revealed that the home feed was suppressing profile exploration, resulting in a redesign that improved discovery and connection outcomes.

METHODS | Usability Testing · Log Analysis · Two-Proportion Z-Tests · Behavioral Metrics

Bringing Discovery Into the Home Experience

+44% sessions reaching profiles • +45% connection acceptance • 30-day post-launch evaluation

Log-level behavioral analysis revealed that the home feed was suppressing profile exploration, resulting in a redesign that improved discovery and connection outcomes.

METHODS | Usability Testing · Log Analysis · Two-Proportion Z-Tests · Behavioral Metrics

Reducing Onboarding Friction Through Progressive Profile Completion

~70% faster onboarding (~11 min → ~3 min) • 50+ hours of field research

Usability testing showed that users were asked for too much before experiencing value, leading to a faster onboarding flow with progressive profile completion.

METHODS | Field Research · Think-Aloud Usability Testing · Observational Validation · Behavioral Analysis

Reducing Onboarding Friction Through Progressive Profile Completion

~70% faster onboarding (~11 min → ~3 min) • 50+ hours of field research

Usability testing showed that users were asked for too much before experiencing value, leading to a faster onboarding flow with progressive profile completion.

METHODS | Field Research · Think-Aloud Usability Testing · Observational Validation · Behavioral Analysis

Reducing Onboarding Friction Through Progressive Profile Completion

~70% faster onboarding (~11 min → ~3 min) • 50+ hours of field research

Usability testing showed that users were asked for too much before experiencing value, leading to a faster onboarding flow with progressive profile completion.

METHODS | Field Research · Think-Aloud Usability Testing · Observational Validation · Behavioral Analysis

I study how people perceive and interact with the world, then apply those insights to build better products.

Product Strategy & UX Design

Across Sun Scooter and Kardder, I led product strategy and design across consumer apps, connected physical systems, and operational tools. My work translated user needs, behavioral evidence, and technical constraints into product requirements, prototypes, and shipped experiences.

Sun Scooter: Designing a Full-Stack Micromobility System for Riders, Operators, and Cities

Designed rider and operations systems across mobile, IoT hardware, and backend services, using telemetry and real-world validation to diagnose failures and improve system performance.

2016-2020

ROLE | Head of Product

Sun Scooter: Designing a Full-Stack Micromobility System for Riders, Operators, and Cities

Designed rider and operations systems across mobile, IoT hardware, and backend services, using telemetry and real-world validation to diagnose failures and improve system performance.

2016-2020

ROLE | Head of Product

Sun Scooter: Designing a Full-Stack Micromobility System for Riders, Operators, and Cities

Designed rider and operations systems across mobile, IoT hardware, and backend services, using telemetry and real-world validation to diagnose failures and improve system performance.

2016-2020

ROLE | Head of Product

Kardder: Building a Research-Driven Platform for Real-World Social Coordination

Drove product strategy across onboarding, discovery, and social interaction systems using experimentation and behavioral analysis.

2020 - 2026

ROLE | Senior UX Researcher & Product Strategist

Kardder: Building a Research-Driven Platform for Real-World Social Coordination

Drove product strategy across onboarding, discovery, and social interaction systems using experimentation and behavioral analysis.

2020 - 2026

ROLE | Senior UX Researcher & Product Strategist

Kardder: Building a Research-Driven Platform for Real-World Social Coordination

Drove product strategy across onboarding, discovery, and social interaction systems using experimentation and behavioral analysis.

2020 - 2026

ROLE | Senior UX Researcher & Product Strategist

Vision Science

My doctoral research at UCLA examined how the visual system transforms ambiguous two-dimensional (2D) motion signals into three-dimensional (3D) percepts. I used psychophysical experiments, computer-generated visual stimuli, and quantitative modeling to investigate stereokinetic depth and the relationship between perceptual experience and behavioral measurement.

Predicting the Perceived Depth of a Stereokinetic Cone

A rotating ellipse with an eccentric dot produces the perception of a 3D cone. Changing the dot’s position systematically altered its perceived depth, and a quantitative model predicted these shifts from the stimulus geometry.

METHODS | MATLAB · Psychophysics Toolbox · Psychophysics · Repeated-Measures ANOVA · Multilevel Regression

Predicting the Perceived Depth of a Stereokinetic Cone

A rotating ellipse with an eccentric dot produces the perception of a 3D cone. Changing the dot’s position systematically altered its perceived depth, and a quantitative model predicted these shifts from the stimulus geometry.

METHODS | MATLAB · Psychophysics Toolbox · Psychophysics · Repeated-Measures ANOVA · Multilevel Regression

Predicting the Perceived Depth of a Stereokinetic Cone

A rotating ellipse with an eccentric dot produces the perception of a 3D cone. Changing the dot’s position systematically altered its perceived depth, and a quantitative model predicted these shifts from the stimulus geometry.

METHODS | MATLAB · Psychophysics Toolbox · Psychophysics · Repeated-Measures ANOVA · Multilevel Regression

Quantifying Stereokinetic Depth Across Measurement Methods

Two rotating, non-concentric circles produce the perception of a 3D cylinder extending in depth. Four methods for measuring the same percept produced systematically different depth estimates, revealing that perceived depth depends partly on how it is measured.

METHODS | MATLAB · Psychophysics Toolbox · Psychophysics · Multimethod Measurement · Reliability Analysis

Quantifying Stereokinetic Depth Across Measurement Methods

Two rotating, non-concentric circles produce the perception of a 3D cylinder extending in depth. Four methods for measuring the same percept produced systematically different depth estimates, revealing that perceived depth depends partly on how it is measured.

METHODS | MATLAB · Psychophysics Toolbox · Psychophysics · Multimethod Measurement · Reliability Analysis

Quantifying Stereokinetic Depth Across Measurement Methods

Two rotating, non-concentric circles produce the perception of a 3D cylinder extending in depth. Four methods for measuring the same percept produced systematically different depth estimates, revealing that perceived depth depends partly on how it is measured.

METHODS | MATLAB · Psychophysics Toolbox · Psychophysics · Multimethod Measurement · Reliability Analysis

Publications

Xing, Y., & Liu, Z. (2026). Quantifying stereokinetic depth: Divergence across methods despite robust within-subject precision. Vision Research, 244, 108817.

Xing, Y., & Liu, Z. (2026). Quantifying stereokinetic depth: Divergence across methods despite robust within-subject precision. Vision Research, 244, 108817.

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Yu, A., Zhang, R., Silva, A. E., Xing, Y., Thompson, B., & Liu, Z. (2022). Motion opponency at the middle temporal cortex: Preserved motion information and the effect of perceptual learning. European Journal of Neuroscience, 56(12), 6215-6226.

Yu, A., Zhang, R., Silva, A. E., Xing, Y., Thompson, B., & Liu, Z. (2022). Motion opponency at the middle temporal cortex: Preserved motion information and the effect of perceptual learning. European Journal of Neuroscience, 56(12), 6215-6226.

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Xing, Y., & Liu, Z. (2018). A preference for minimal deformation constrains the perceived depth of a stereokinetic stimulus. Vision Research, 153, 53-59.

Xing, Y., & Liu, Z. (2018). A preference for minimal deformation constrains the perceived depth of a stereokinetic stimulus. Vision Research, 153, 53-59.

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Erlikhman, G., Xing, Y., & Kellman, P. J. (2014). Non-rigid illusory contours and global shape transformations defined by spatiotemporal boundary formation. Frontiers in Human Neuroscience, 8, 978.

Erlikhman, G., Xing, Y., & Kellman, P. J. (2014). Non-rigid illusory contours and global shape transformations defined by spatiotemporal boundary formation. Frontiers in Human Neuroscience, 8, 978.

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Education

PhD, Cognitive Psychology — UCLA
2024

MA, Cognitive Psychology — UCLA
2017

BA, Psychology — UCLA
2013

About

I am a UX researcher and product strategist with a PhD in Cognitive Psychology from UCLA. My work explores how people perceive, behave, and make decisions under uncertainty, translating behavioral research into products that are intuitive, measurable, and grounded in evidence.


Across startups, connected hardware, and academic research, I have combined qualitative research, controlled experimentation, behavioral analytics, and computational modeling to understand user behavior and guide product strategy. Whether redesigning social discovery systems, improving fleet operations, or modeling visual perception, my work begins with understanding behavior and ends with clear, testable product decisions.


I enjoy working on complex systems where behavior emerges from the interaction between people, technology, and context. My goal is to transform ambiguity into structure by identifying meaningful patterns, evaluating competing ideas, and translating research into products that are both useful and scalable.

Connect

Feel free to reach out for collaboration, opportunities, or just to chat.


Email: yangxing92@gmail.com

LinkedIn: www.linkedin.com/in/mac-xing888