Jeffrey Blevins, Journalism
Data Injustice: A Minority Report for Social Media and Our Digital Futures
Xuan Cao, Mathematical Sciences
Network-Guided Feature Selection for Disease Risk Stratification
Omics data, routinely collected in various clinical settings, are of a complex and network-structured nature. For example, quantitative molecular traits including gene expression, proteomics, or metabolomics often display a coordinated change along a pathway, where the impact of one single factor on the disease outcome may not be apparent. The method of network-based feature selection can incorporate various omics data and highlight unknown networks to improve the performance of feature selection and disease prediction by borrowing information from the underlying biological pathway. The overarching goal of this project is to develop general statistical frameworks for network-based feature selection and formulate network-guided risk scores for disease risk stratification.
Anita Dhillon, School of Public and International Affairs
Cross-System Collaborations and Its Effect on Service Provision for Dual-System Youth
Jennifer Glaser, English
Jews, Disability, and Post-Holocaust America
Delaney Harness, School of Communication, Film, and Media Studies
Tracing Transparency: The Role of Technology in Governance, Human Rights, and Accountability in Carbon Markets
Sharell Luckett, English
The Luckett Paradigm - A New Methodology
Aditi Machado, English
The End, Contd.
Eduardo Martinez, Philosophy
Belief-formation and Communication Under Polarization
Kelly Merrill, School of Communication, Film, and Media Studies
Responses to Supportive Messages: Assessing Differences Between AI Chatbots and Humans as Sources of Support
Oneya Okuwobi, Sociology
Disabling Perceptions: How College Students’ Perceptions of Ableism Affect Their Educational Career
Lim Sookkyung, Mathematical Sciences
Mathematical Modeling of Bacterial Swimming and Swarming