Leveraging Multimodal Machine Learning for Accurate Risk Identification of Intimate Partner Violence

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Wednesday, October 15, 2025 | 1:00–2:00 p.m. ET
C+M Center Speaker Series | Online webinar

Leveraging Multimodal Machine Learning for Accurate Risk Identification of Intimate Partner Violence

Kimberly Villalobos Carballo, Assistant Professor at NYU’s Tandon School of Engineering, presented research on using multimodal machine learning to identify risk of intimate partner violence in clinical settings.

Her work combines hospital patient data and clinical notes to detect signs of risk before individuals seek help. The presentation addressed early identification as a step toward intervention in a public health problem that is often underreported.

Villalobos Carballo develops optimization and machine-learning methods for healthcare, with particular attention to small datasets, model robustness, and interpretability. Her research includes collaborations with Brigham and Women’s Hospital, Hartford HealthCare, and UMass Memorial Health.

Start Time

1:00 pm

October 15, 2025

Finish Time

2:00 pm

October 15, 2025