Kuksenok CV (Dec 2015)

Education

  • 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.

2

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

2

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

2


  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.