Experience

Cisco AppDynamics

Lead foundational and evaluative research that informs user-centered development of new apps and their ecosystem in Cisco Observability Platform, which empowers users to monitor, secure, and optimize their cloud-native applications and infrastructure.
Spearheaded research that defined user experience in new product areas, such as data security posture management (DSPM) and the first developer platform that enables users and partners to build their own solutions for full-stack observability.
Employ and triangulate multiple methods effectively (e.g., concept testing, interviews, surveys, usability testing, etc.) to address business-critical research questions and uncover the motivations, pain points, and goals of potential and existing users in highly technical roles, such as SRE, DevOps, Security, etc.
Partner with stakeholders in Product, Design, and Engineering to continuously prioritize research needs and share findings to enable data-driven decisions throughout the product development lifecycle.
Democratize user research by providing consultations about research methods and best practices and coaching junior designers and PMs through the process of gathering and synthesizing unbiased feedback from internal users or key customers.

Led research that provided user-centric insights about developing key components of Cisco Cloud Observability—a flexible data platform and ML/AI-based alerting features.
Conducted evaluative research that guided designers, PMs, and engineers in migrating existing features to a reimagined UI that supports more intuitive workflows.
Facilitated conversations between PMs and customers in Product Advisory Councils and delivered findings that shaped product roadmaps and strategies for building and launching Cisco Cloud Observability.

Proposed a new categorical system for webinars on GoToStage (video hosting website) to improve alignment between users’ mental models and machine learning models for increased user engagement.
Developed new categories for GoToStage webinars by conducting multi-stage content analyses of textual and visual information in existing webinars.
Conducted interviews about building trust with users of multiple video conferencing software (GoToMeeting, Webex & Zoom) to make recommendations for design enhancements in GoToMeeting.

Conducted survey research that identified factors that lead people to rely on mental shortcuts to make privacy-related decisions in social media (Facebook, Instagram, Snapchat, and Twitter), and then generated ideas for designing privacy tools that could help users make safer and more informed decisions.
Led iterative focus group interviews to gain insights about how and why people use mental shortcuts to make decisions about sharing information in social media.

Provided human-centered insights in a cross-functional team of computer scientists and HCI researchers to develop a tool that protects social media users from hashtag-related inference algorithms.
Made design recommendations based on findings from experiments that aimed to understand privacy threats by a technology that enables extended trending topics analysis (e.g., predicting users’ personal characteristics based on hashtags they use).
- The findings were presented at the 21st ACM Conference on Computer-Supported Cooperative Work and Social Computing.

Coordinated usability testing of an Android app SecurePost before its launch on Google Play Store by recruiting and managing survey responses from approximately 60 participants.
Assisted in data synthesis and report writing on cross-cultural research in Zambia, Turkey, and Mongolia that identified users’ need for SecurePost.

Communicated quantitative research methods to a diverse audience effectively and received recognition with an award and multiple nominations for similar awards.
- Edwin Schoell Award for Excellence in Graduate Teaching, June 2020
Taught descriptive and inferential statistics by using R and SPSS.

Analyzed survey data (collected by GfK) from a nationally representative sample of Facebook users to understand their privacy risk perceptions and information sharing behaviors.
Proposed ideas for developing new privacy tools that could support SNS users’ decisions.
- The findings were published in the Journal of Communication.

Conducted in-depth interviews (N = 30) to understand people’s privacy perceptions and the way they share information on social media using different devices (mobile vs. non-mobile) in different physical locations.
- The findings were published in Social Media + Society.
Assisted with data collection for a lab study that assessed when people would use search engines (Google & Bing) and/or social media (Facebook & Twitter) for their information needs.
Coded open-ended responses about how people seek information online and identified design implications for search engines.
Transcribed and coded interviews about people’s web search processes to find answers to specific health questions.