Maria Glenski is a Data Scientist in the Data Science and Analytics Group in the National Security Directorate. Her research focuses on computational social science approaches to model, characterize, and explain complex behavior in diverse online social environments and the impacts of biases in machine learning/artificial intelligence models, particularly for deception detection. Dr. Glenski’s research has been published in top tier venues including WWW, ACL, ACM TIST, and CSCW and interdisciplinary venues such as the Comparative Approaches to Disinformation workshop at Harvard University in 2019. She has co-organized a tutorial on measuring information spread within and across social platforms at the AAAI international conference on the web and social media (ICWSM) and contributed a chapter to the 2020 Springer book on Disinformation, Misinformation, and Fake News in Social Media – Emerging Research Challenges and Opportunities. She regularly serves on the program committee of several international conferences, including as an area chair for the Women in Machine Learning workshop, and has been recognized as an outstanding reviewer (ICWSM 2019).
Dr Glenski received her Ph.D. in Computer Science from the University of Notre Dame where she was an Arthur J Schmitt Leadership in Science and Engineering Fellow and a member of the Interdisciplinary Center for Network Science and Applications (iCeNSA). Her dissertation work focused on understanding and explaining how social media users engage with and propagate information from social news sources of varied credibility or deception.
Disciplines and Skills
- Artificial Intelligence
- Causal Analysis
- Data Science
- Deception Detection
- Deep Learning
- Machine Learning
- Network Science
- Social Media
- University of Notre Dame - Doctor of Philosophy, Computer Science
- University of Notre Dame - Master of Science, Computer Science & Engineering
- Saint Mary's Univ of MN - Bachelor of Arts, Mathematics