About Me

In my research, I use communication science to study the real-world impact of bias, whether algorithmic or human. I combine theoretically grounded conceptual frameworks with state-of-the-art computational methods and rigorous experimental designs. Together, these approaches allow me to examine how communication reveals how biases are recreated and amplified.

As a junior lecturer, I tackled teaching both theoretical and methodological topics, and, in all instances, my approach rested on helping students see research as a skill that can help them reflect on our world more thoughtfully. Through this approach, I was able to inspire curiosity and self-efficacy in my students, allowing them to discover their own path.

Interests
  • Algorithmic and Human Bias
  • Communication and Online Communities
  • Computational Social Science and Machine Learning
Education
  • Ph.D. in Communication Science, 2026

    University of Amsterdam

  • M.Sc. Communication Science (Research, cum laude), 2020

    University of Amsterdam

  • B.A. Mass Communication (Hons, cum laude), 2017

    SEGi University & Plymouth Marjon University

Experience

 
 
 
 
 
Postdoctoral Researcher, Communication Science
Jun 2026 – Present Amsterdam, Netherlands
  • Postdoc on Bias Revisited: Replicating Information Bias Theories in Three European Media Systems (NWO Replication Studies), replicating Lord, Ross & Lepper (1979), Gunther & Schmitt (2004), and Taber & Lodge (2006) across European media systems.
  • Responsible for study design, preregistration, data collection, analysis, and open reporting.
  • Team: dr. Martin Tanis (PI), dr. Ellen Droog, dr. Mariken van der Velden, dr. Ivar Vermeulen, and prof. dr. Tilo Hartmann.
 
 
 
 
 
Ph.D. Researcher in Communication, Organizations and Society (COS)
Sep 2020 – Aug 2025 Amsterdam, Netherlands
  • Dissertation: Hiring in the digital society: Content and consequences of gender and age stereotypes in job advertisements
  • Investigate how gender- and age-based framing in job advertising shapes candidate sourcing and selection.
  • Combine computational content analysis, experiments, and cross-national datasets to study bias in algorithmically-aided hiring.
 
 
 
 
 
Junior Lecturer, Communication Science
Sep 2021 – May 2022 Amsterdam, Netherlands
  • Designed tutorials and assessments for courses on computational communication science, corporate communication, and research methods.
  • Mentored undergraduate cohorts on data-driven inquiry, academic writing, and reflection.
 
 
 
 
 
Research Intern in Political Communication
May 2019 – Jan 2020 Amsterdam, Netherlands
  • Conducted collaborative projects on news audiences and political communication under the supervision of dr. Mark Boukes and prof. dr. Theo Araujo.
  • Supported data collection, analysis, and reporting across cross-platform social media studies.

Publications

Quickly filter by topic, collaborator, or publication type on the publications page.
2026. Bias in AI-Aided Candidate Selection: Investigating the Influence of AI Recommendations and Gender Stereotypical Frames on Candidate Selection and Hiring Decision-Making. Manuscript in preparation. .

2026. Bias in Automated Job Advertisement Delivery: The Effect of Stereotypical Gender and Age Framing Across European Countries. Manuscript in preparation. .

2024. Bias in Candidate Sourcing Communication: Investigating Stereotypical Gender- and Age-Related Frames in Online Job Advertisements at the Sectoral Level. Public Relations Review, 50(3) . Available at: https://www.sciencedirect.com/science/article/pii/S0363811124000353

PDF DOI

2021. Comparing User-Content Interactivity and Audience Diversity Across News and Satire: Differences in Online Engagement Between Satire, Regular News and Partisan News. Journal of Information Technology & Politics, 19(1), 98–117 . Available at: https://www.tandfonline.com/doi/full/10.1080/19331681.2021.1927928

PDF DOI

Conferences and Talks