Kuksenok CV (Dec 2015)


  • In progress: PhD1 in Computer Science and Engineering at the University of Washington, Seattle, WA. Advised by James Fogarty (UW CSE), Cecilia Aragon (UW HCDE).

  • 2014: Master of Science2 in CSE at UW. Advised by James Fogarty and Luke Zettlemoyer.

  • 2010: Bachelor of Arts3 in Computer Science; Applied Mathematics at Oberlin College, Oberlin, OH.


Topic: Adoption and Adaptation of Programming Practices in Oceanography
Advised by Cecilia Aragon (UW HCDE), James Fogarty (UW CSE)


Topic: Capturing How People Fix Errors Made by Machine Translation
Advised by James Fogarty (UW CSE), Srini Bangalore (AT&T)


  1. Doctoral research topic:
    Adoption and Adaptation of Data Science in Oceanography

  2. Master’s research topic:
    Interactive Machine Translation

  3. Undergraduate research topic:
    Online Resources in Chronic Illness Management
    Conducted at Carnegie Mellon University Human-Computer Interaction Institute, advised by Jennifer Mankoff

Current Research

  • Adoption and Adaptation of Data Science in Oceanography (Qualitative Research; Ethnography)

  • Social Media and Multilingualism Online in Ukraine’s Maidan Movements (Qualitative Research; Human-Centered Data Science)

  • Critique and meta-analysis of qualitative research of social media data (Analytic Synthesis of Scholarly Literature)

Research Skills

  • Quantitative1 data exploration and analysis (crowdsourcing, relational db design, SQL, R, visualization, Tableau)

  • Qualitative data gathering and analysis (interviews, survey design, grounded theory development, visualization)

  • User-centered design; Value-Sentitive Design (design exercises, participatory design, synthesizing existing research)

  • Natural language processing (python, toolkits); Machine learning (weka, java, python)

  1. My research toolkit combines qualitative and quantitative methods with automation and design in a way that allows me to offer (1) a unique perspective, which (2) builds on existing understanding of how humans use technology and (3) leads to actionable design and development recommendations.

Work Experience

  • Jan 2014 - Mar 2014: User Researcher at Amazon.com Shared Shopping Experience research, mixed methods. Conducted interviews to understand user values regarding social content on Amazon.com; performed qualitative analysis, followed by unsupervised learning, over user-generated content.

  • Summer 2013: Software Engineering Intern at Google Seattle DoubleClick Search. Built internal tool (Java) to experiment with novel attribution modeling methods.

  • Summer 2012: Software Engineering Intern at Facebook Seattle Platform Integrity. Built internal tool (PHP, XHP) for quickly creating spam classifiers, using semi-supervised clustering and visualization techniques to identify useful features.

  • Summer 2011: Research Intern at AT&T Labs Speech Team Built interactive machine translation web applicationfor crowdsourcing translation data using iterative, human-centered design.

Peer-Reviewed Publications

5. K. Kuksenok, M. Brooks, Q. Wang, C. P. Lee. Challenges and Opportunities for Technology in Foreign Language Classrooms. CHI 2013. Best Paper Honorable Mention (top 5%)

4. K. Kuksenok, J. Mankoff, M. Brooks. Accessible Online Content Creation by End Users. CHI 2013.

3. M. Brooks, K. Kuksenok, M. K. Torkildson, D. Perry, J. J. Robinson, T. J. Scott, O. Anicello, A. Zukowski, P. Harris, C. Aragon. Statistical Affect Detection in Collaborative Chat. CSCW 2013.

2. T. J. Scott, K. Kuksenok, M. Brooks, C. Aragon. Adapting Grounded Theory to Construct A Taxonomy of Affect in Collaborative Online Chat. SIGDOC 2012.

1. J. Mankoff, K. Kuksenok, S. Kiesler, J. Rode, K. Waldman. Competing Online Viewpoints and Models of Chronic Illness. CHI 2011.