Homa Hosseinmardi

Homa Hosseinmardi is an Assistant Professor at the University of California, Los Angeles (UCLA). She holds a Ph.D. in Computer Science from the University of Colorado Boulder. Her research focuses on computational social science, leveraging machine learning, natural language processing, and causal inference to study sociotechnical systems, radicalization dynamics, and platform governance. She collaborates across disciplines with sociologists, economists, and psychologists.

Her work examines topics such as media bias, algorithmic effects on content consumption, and cyberbullying prevention. Notable contributions include causal analyses of YouTube’s recommender systems and studies on partisan news diets. She actively participates in conferences and workshops, presenting at venues like the Political and Information Networks Workshop and the Conference on Harmful Online Communication.

Key themes in her research include auditing digital platforms, quantifying shared reality in media, and predicting human behavior through tensor embeddings. She has published in top journals like Proceedings of the National Academy of Sciences and Science Advances.

Academic and professional highlights include joining UCLA in 2024, speaking at the DataX+IDRE Symposium, and leading interdisciplinary projects on algorithmic impact and social media governance.