معرفی
Dr. Yulin Hswen is an Associate Professor in the Department of Epidemiology and Biostatistics at UCSF's School of Medicine, with a joint appointment in the Computational Precision Health Program at UC Berkeley. She holds a Doctorate in Social and Computational Epidemiology from Harvard University and completed postdoctoral training at Harvard Medical School. Her research integrates AI, machine learning, and social media analytics to study how information dissemination impacts public health outcomes, with focus areas including digital epidemiology, health equity, and social engineering.
Education includes:
- ScD in Social and Computational Epidemiology, Harvard University (2019)
- Post-Doctoral Fellowship in Computational Epidemiology, Harvard Medical School (2019)
- Visiting Assistant Professor in Behavioral Economics, Aix-Marseille School of Economics (2020)
Her research investigates how narratives—both factual and misleading—spread through digital spaces, influence population-wide perceptions, and impact health decisions. Key methodologies include generative AI and natural language processing to analyze emotional undertones in communication, detect patterns in discourse, and evaluate AI's role in public health surveillance. She maintains particular focus on cognitive complacency in AI-driven decision-making and ethical implications for healthcare.
Publications demonstrate strong emphasis on AI applications in medicine, including predictive modeling for neurodegenerative diseases, health equity frameworks, clinical trial optimization, and ethical AI deployment. Recent work explores large language models, multimodal hate speech detection, and cross-cultural health communication.
Awards and honors include:
- JAMA Associate Editor for AI & Medicine (2023)
- Two Robert Wood Johnson Foundation 'Most Innovative Manuscript' awards (2022)
- President Macron's Make Our Planet Great Again Fellowship (2019)
- Harvard Kennedy Fellowship (2018)
- CIHR Doctoral Research Award (2015)
Active research grants include NIH-funded projects on Alzheimer's early detection ($7M Syrmount Award), racial bias impacts on birth outcomes, and digital health solutions for COVID-19. She mentors faculty in research and career development through the UCSF Data Science Training Program (DaTABASE).
Additional roles include Associate Editor at JAMA, editorial board positions at Nature Scientific Reports, and previous visiting professorship at Aix-Marseille School of Economics. She maintains active media engagement with features in NY Times, Washington Post, and JAMA network publications.
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