Dr. Yulin Hswen is an Assistant Professor in the Department of Epidemiology and Biostatistics and the Bakar Computational Health Institute at the University of California, San Francisco. (HSWEN.UCSF.EDU) Dr. Hswen earned her Doctorate from the Harvard T.H. Chan School of Public Health, specializing in computational epidemiology. Dr Hswen is also the youngest female Associate Editor at JAMA and JAMA network, a top medical journal in the world, where I lead the AI division of JAMA+ AI where I oversee and curate AI articles and am a host of the JAMA+ AI conversations where I speak to leading AI experts to dissemination research to a broader audience.   

Her research investigates how information spreads, influences behavior, and shapes public health outcomes. Her research integrates artificial intelligence (AI), machine learning, and social media analytics to analyze how narratives—both true and misleading—gain traction in digital spaces, influence population-wide perceptions, and impact real-world decisions. By leveraging vast datasets from online platforms, she examines the mechanisms through which ideas, trends, and information propagate, through social contagion, and how they shape both political and health-related discourse. 

Dr. Hswen’s work is particularly focused on understanding the role social media as a vector for social engineering in shaping societal viewpoints. Social Engineering plays a critical role in directing collective thought by subtly manipulating emotions, beliefs, and behaviors through targeted messaging, curated digital environments, and algorithmic reinforcement.

In her research, Dr. Hswen employs generative AI and natural language processing (NLP) tools to analyze how digital content is produced, shared, and interpreted. She uses AI models that can detect patterns in discourse, measure emotional undertones in communication, and evaluate the extent to which AI-generated narratives align with or diverge from human perception. A key aspect of her work involves comparing AI’s ability to interpret complex emotional cues—such as happiness, sadness, anger, and disgust—with traditional human assessments. Through this approach, she explores the limitations of AI in capturing the nuances of human emotion and the ethical concerns surrounding AI-driven communication, particularly in healthcare settings.

Beyond emotion analysis, Dr. Hswen investigates how cognitive complacency—the over-reliance on AI for decision-making—affects problem-solving, creativity, and critical thinking in public health and political contexts. She examines whether AI’s predictive capabilities inadvertently discourage human-driven innovation and whether automation can reinforce misinformation by amplifying dominant narratives without questioning their validity. To address these concerns, her research integrates human-in-the-loop methodologies, where human oversight is incorporated into AI processes to enhance accuracy, mitigate errors, and ensure ethical considerations in automated decision-making.

Dr. Hswen also applies these methodologies to public health surveillance, analyzing how AI can be optimized to detect emerging health threats, track illicit behaviors, and understand patterns of misinformation in online discourse. Her work on underground black markets, such as illicit drug sales, explores how AI can be used to monitor discussions, detect shifts in public attitudes, and assess the potential health risks associated with unregulated substances. By studying how digital platforms serve as both facilitators and regulators of public narratives, she highlights the intersections between AI, social influence, and public health policy.

Through her interdisciplinary approach, Dr. Hswen’s research challenges the assumption that AI-driven insights are inherently objective and instead emphasizes the need for critical evaluation of how AI systems shape knowledge, perception, and decision-making. Her work underscores the importance of ensuring that AI tools enhance rather than replace human reasoning, fostering a more informed and balanced approach to addressing complex social and public health challenges.

Dr. Hswen has served as Deputy Editor of the Harvard Public Health Review and is on the editorial boards of Nature Scientific Reports and Humanities and Social Sciences Communications. She has been a Kennedy Fellow at Harvard University, a Chateaubriand STEM Fellow, and a researcher supported by the Embassy of France and the French National Research Agency. Before joining UCSF, she was a Visiting Assistant Professor at Aix-Marseille School of Economics (AMSE), where she applied behavioral economics to optimize public health intervention strategies.

Dr. Hswen’s expertise in AI-driven health analytics, digital epidemiology, and behavioral modeling has positioned her as a leader in computational epidemiology. Her research continues to drive the advancement of innovative AI applications in medicine and public health, optimizing data-driven approaches for disease prevention, risk assessment, and health promotion.

Personal interests: Collectionneur de montres, 18th-19th century French and Italian Art, and Crystal.
Activities: Strategic surprises, extraordinary excursions, finessing forums, wandering walks, Drawn-out dinners, and lingering laydowns
Previous life: Actress - Commercial, Movies, Television https://www.imdb.com/name/nm1840526/
Languages: English (Written: British), French (Fluent), Punjabi
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