I am a Postdoctoral Scholar supported by an NIH T32 fellowship in AI/ML and Precision Nutrition. In this role, I develop and evaluate machine learning and deep learning models applied to large-scale population data, including NHANES and All of Us datasets, to identify Type 2 Diabetes risk predictors and study nutrition-related health outcomes. I also led a systematic review and meta-analysis examining the application of AI and ML in precision nutrition interventions, with a focus on biomarkers, hypertension, lipid profiles, anthropometrics, and behavior change (manuscript under peer review in the Journal of Nutrition). My training spans advanced AI/ML methods, precision nutrition science, and translational research, and I actively contribute to manuscript preparation, grant development, conference presentations, and student mentorship within a multidisciplinary team of nutrition scientists, clinicians, and data scientists.

Prior to this fellowship, I completed a postdoctoral appointment at the University of Washington's School of Nursing and Health Studies, where my work sat at the intersection of AI, behavioral health, and digital mental health. I applied NLP and LLM-based methods to analyze large-scale social media data, integrating semantic metrics, human perception data, and network analysis to evaluate how different AI response types influenced user experience and emotional outcomes in online mental health communities. I led a multidisciplinary team of graduate and undergraduate students spanning social work, nursing, public health, psychology, and education to conduct a systematic review of youth behavioral health literature and develop evidence-based policy recommendations for K-12 mental health services. I also led the development of a youth wellness curriculum and built an online resource hub featuring AI-enhanced interactive dashboards (Tableau, Power BI) to disseminate behavioral health strategies to practitioners and community stakeholders.

My work has been published in peer-reviewed journals including Psychiatry Research, Eating and Weight Disorders, PLOS ONE, and Psychological Reports, and has been featured in media outlets such as PsyPost for its public health relevance.