UX Research Portfolio

I'm a Ph.D. researcher in human-centered security and privacy who uses mixed methods to understand how people make decisions around security, privacy, and emerging technologies. Across my projects, I have planned and run studies, analyzed qualitative and quantitative evidence, synthesized fragmented research areas, and built tools that make rigorous data collection possible. I am especially interested in UX Research to help translate complex research questions into clear, decision-ready insights for product, design, and engineering teams.

Research Skills & Methods

Qualitative Research

  • Semi-structured interviews
  • User studies
  • Thematic analysis & qualitative coding
  • Participant recruiting & management
  • Research planning & moderation guides

Quantitative Analysis

  • Survey design & analysis
  • Descriptive & inferential statistics
  • Hypothesis & significance testing
  • Data analysis (Python, R, ElasticSearch, SQL)
  • Data visualization

Tools

  • Qualitative tools (MaxQDA, NVivo)
  • Survey platforms (Prolific, Qualtrics, SurveyJS)
  • Tool building (browser extensions, web crawlers, survey apps, transcription pipelines)

Research Synthesis

  • Systematic literature reviews
  • Gap analysis
  • Threat modeling
  • Translating findings into recommendations

Case Studies

These case studies are based on academic research projects I have worked on, or am currently working on, during my Ph.D. They are included here to show how my research training has helped me build skills that are useful in UX research: defining research questions, choosing appropriate methods, studying specialized users, analyzing qualitative and quantitative evidence, building research tools, and translating findings into clear recommendations.

QUALITATIVE · Trustworthy Data Collection

Building a Fraud-Resilient Survey Platform

Ongoing project: open-source survey platform for detecting and deterring traditional and AI-assisted survey fraud

I am developing an open-source survey platform that supports secure online data collection with built-in mechanisms for identifying low-quality, fraudulent, or AI-assisted responses. The platform will build on findings from prior studies and from a user study with researchers that I am currently designing. In that study, I plan to interview researchers about how fraudulent attempts affect their data collection process and ask them to evaluate and co-design survey application features. The project connects research operations with product thinking: translating evidence about fraud, researcher workflows, and participant experience into tooling that can help researchers collect more reliable data at scale.

Methods
Research operations Requirement translation Survey data quality Fraud mitigation
Tools
React Node.js SurveyJS MongoDB
Quantitative · Study Design

Online Consent Alignment

Ongoing project: understanding how users' privacy preferences align with historical cookie consent decisions

I have designed a mixed-methods privacy study that combines browser-based consent data, browsing behavior, and survey responses to compare what users say they want with the choices they have made in real browsing contexts. As part of this work, I am running a survey with 185 participants from the European Union to understand the causes of misalignment between users' privacy preferences and decisions, including the struggles they face when exercising agency and making informed consent choices. The project requires turning an ambiguous behavioral question into measurable constructs, building trustworthy data collection flows, analyzing messy behavioral and survey data, and communicating where consent experiences may fail to represent user preferences.

Methods
Survey design Behavioral data collection Browser-based instrumentation Descriptive & inferential statistics Data visualization
Tools
Python R React Browser extension
Qualitative · Usability Evaluation

Understanding How Researchers Use Privacy Tools

Paper: "An exploratory user study of disclosure-avoidance tools for scientific microdata (PETS 2027)"

I worked on an exploratory user study of how scientific researchers understand and use disclosure-avoidance tools for protecting microdata. The work centered on making expert workflows visible: how users interpret privacy protections, where tool concepts become confusing, and what support they need to make responsible data-sharing decisions. I contributed to the research process from study execution through qualitative analysis and the synthesis of design implications for specialized privacy tools.

Skills
Semi-structured interviews User studies Participant recruiting & management Thematic analysis Design implications
Tools
WhisperX & Pyannote NVivo Qualtrics
Research Synthesis · Literature Review

Mapping a Problem Space from the Ground Up

Paper: "SoK: Mapping Threats to Defenses in Online Survey Fraud (USENIX SOUPS 2026)"

I systematically reviewed and synthesized a large, fragmented body of prior work into a single structured framework, mapping known threats to the defenses that address them and exposing the gaps in between. This project strengthened the same synthesis and problem framing skills used in discovery research: turning scattered evidence into a decision-ready map, clarifying tradeoffs, and identifying where better tools and research practices are needed to support trustworthy online studies.

Methods
Systematic literature review Gap analysis Threat modeling Thematic synthesis
Tools
MaxQDA PRISMA
Quantitative · Measurement

Supporting a Measurement Study of an Ecosystem

Paper: "Mirror Mirror on the Wall, which APK Mirror Site is the Largest of Them All? (ACM IMC 2025)"

I supported a measurement study that quantified and compared competing APK mirror sites across a complex software ecosystem. My contributions focused on cleaning and analyzing large-scale platform data, creating visualizations, interpreting results, and helping write the paper. The project strengthened my ability to work with complex technical data and present evidence in a way that supports decisions about ecosystem risk, coverage, and reliability.

Methods
Data cleaning Data analysis Data visualization Comparative analysis Research writing
Tools
Python ElasticSearch SQL