Saiph Savage

About

Saiph Savage is an Assistant Professor and the Director of the Civic A.I. Lab at Northeastern University. Her research focuses on machine learning, data mining, and life sciences, with particular emphasis on health and civic applications. She is a member of the Faculty Leadership Committee and contributes to the AI + Health and AI + Life Sciences focus areas. Her work involves developing AI solutions that address societal challenges, leveraging her expertise in data-driven methods to improve health outcomes and civic engagement.

Research topics

• Computer Science
• Economics
• Business
• Labour economics

Selected publications

• A Culturally-Aware AI Tool for Crowdworkers: Leveraging Chronemics to Support Diverse Work Styles

  Proceedings of the ACM on Human-Computer Interaction · 2024-11-07 · 6 citations

  articleOpen accessSenior author

  Crowdsourcing markets are expanding worldwide, but often feature standardized interfaces that ignore the cultural diversity of their workers, negatively impacting their well-being and productivity. To transform these workplace dynamics, this paper proposes creating culturally-aware workplace tools, specifically designed to adapt to the cultural dimensions of monochronic and polychronic work styles. We illustrate this approach with "CultureFit," a tool that we engineered based on extensive resear…

  PublisherOA PDFDOI

• New Frontiers of Human-centered Explainable AI (HCXAI): Participatory Civic AI, Benchmarking LLMs, XAI Hallucinations, and Responsible AI Audits

  2025-04-23 · 4 citations

  article
  PublisherDOI

• Playing to Pay: Interplay of Monetization and Retention Strategies in Korean Mobile Gaming

  ArXiv.org · 2025-04-14 · 1 citations

  preprintOpen accessSenior author

  Mobile gaming's global growth has introduced evolving monetization strategies, such as in app purchases and ads, designed to boost revenue while maintaining player engagement. However, there is limited understanding of the scope and frequency of these strategies, particularly in mature markets like South Korea. To address this research gap, this study examines the monetization strategies used in the top 40 most popular Korean mobile games through direct gameplay observations and targeted video a…

  PublisherOA PDFDOI

• Grand Challenges for the Convergence of Computational and Citizen Science Research

  SSRN Electronic Journal · 2026-01-01

  preprintOpen access
  PublisherDOI

• AI-Mediated Hiring and the Job Search of Blind and Low-Vision Individuals

  arXiv (Cornell University) · 2026-01-17

  preprintOpen accessSenior author

  Blind and low-vision (BLV) individuals face high unemployment rates. The job search is becoming harder as more employers use AI-driven systems to screen resumes before a human ever sees them. Such AI systems could inadvertently further disadvantage BLV job seekers, introducing additional barriers to an already difficult process. We lack understanding of BLV job seekers' experiences in today's AI-driven hiring ecosystem. Without such understanding, we risk designing technologies that create new s…

  PublisherDOI

Frequent coauthors

• Claudia Flores-Saviaga

  28 shared

• Carlos Toxtli

  Clemson University

  23 shared

• Jeffrey P. Bigham

  Apple (United States)

  18 shared

• Dhanaraj Thakur

  16 shared

• Maria Alma Rodriguez

  16 shared

• Andrés Monroy‐Hernández

  Princeton University

  16 shared

• Michal Luria

  16 shared

• DeVan L. Hankerson

  16 shared

Labs

• The Institute for Experiential AIPI

Education

• Ph.D., Computer Science

  Northeastern University

  2010

• M.S., Computer Science

  Northeastern University

  2006

• B.S., Computer Science

  Northeastern University

  2004

Similar researchers at Northeastern University

• Daniel Kimh-85
• Ozlem Ergunh-32