Speakers

Julia Jose is a Computer Science Ph.D. candidate at New York University, advised by Rachel Greenstadt. Her research focuses on developing computational tools to detect propaganda across domains and languages. By identifying the characteristics of misleading content, she explores persuasive techniques in social media, parliamentary debates, and news articles.

Drawing on her expertise in AI and machine learning, she is currently also working at King Street Capital, supporting investment research. Previously, she served as a VC & ML Fellow at Atento Capital, a Tulsa-based early-stage venture capital firm, where she worked on investment evaluation, deal sourcing, and growth strategies while advancing machine learning initiatives across portfolio companies. Before beginning her doctoral studies, she was a Data Scientist at Atos, where she developed AI-driven applications and implemented MLOps solutions.

Julia holds a master’s degree in Computer Science from Arizona State University and a bachelor’s degree in Electronics and Communication Engineering from the National Institute of Technology Delhi. At ASU, she collaborated with the Behavioral Research Lab to implement technological tools for analyzing behavioral patterns and served as a Graduate Teaching Assistant for courses such as Principles of International Business and Negotiation at the W. P. Carey School of Business.

Earlier in her career, she worked as a Research and Development Intern at the Qatar Computing Research Institute, rotating through the Arabic Language Technologies, Social Computing, and Visualization departments.