Funded Research Projects

The C+M Center supports pioneering research at the intersection of data science and social impact. Our research initiatives harness big data, artificial intelligence, and advanced analytics to address pressing social challenges and promote equity. Through collaborative projects, faculty-led studies, and doctoral research, we strive to develop innovative solutions that inform policy, enhance social services, and drive systemic change.

Jordan DeVylder headshot

Development of a Machine Learning Algorithm to Predict Outcomes among Young Adults with Psychotic Experiences

This project aims to employ machine learning methods to examine video and audio-recorded data and...
Rohini Pahwa headshot

An AI-driven approach for examining objective markers of social support to identify individuals at risk of PTSD after trauma

This study explores the impact of social support on PTSD risk among trauma survivors in...
Nicholas Lanzieri headshot

The Use of Virtual Simulations in Social Work Education

This study aims to develop and pilot test a technology-based simulation template for social work...
Neil B. Guterman headshot

Analyzing the Language Environment Analysis (LENA) on Fathers’ and Infants’ Verbalizations”

This study examines the role of fathers in early childhood development, an area that has...
Michelle R. Munson headshot

Using ‘Big Data’ to Identify ‘Hotspots of Need’ and Key Drivers of Service Utilization in New York

This project will leverage the PSYCKES platform’s large integrated mental health and Medicaid claims database,...
Ernest Gonzales headshot

Predicting Cognitive Functioning in Later Life through Machine Learning: Implications for Equity Research

This study investigates cognitive impairment, which disproportionately affects minoritized groups in the U.S., despite nearly...
Victoria Stanhope headshot

Harnessing Natural Language Processing to Measure Person-Centered Care in Behavioral Health Settings

This study addresses the widespread issue of service disengagement in the mental health system by...
Doris F. Chang headshot

Macro-Contextual and Individual Predictors of Discrimination, Intergroup Attitudes, and Collective Action to Address Racial Inequality

This study examines how regional racial climate influences Asian Americans’ mental health, intergroup attitudes, and...

C+M Center Request for Proposals

The C+M Center sponsors an annual Pilot Grant Competition that provides funding for research projects that use data science and emerging technologies to address pressing social challenges. The competition is open to full-time faculty of NYU Silver who haven’t previously received a C+M Center grant. The program encourages proposals involving artificial intelligence, machine learning, predictive modeling, and other advanced data science techniques to tackle issues like health inequity, racial disparities, substance use, and child welfare. Strong applications should demonstrate potential for large-scale social impact, scientific advancement, and future funding opportunities.

 
 

For more information, contact the C+M Center (silver.cmscenter@nyu.edu).

Publications

Explore our latest research publications, software, and policy submissions in response to government and pariamentary calls for evidence

Rodwin, A. H., Layman, D., Finnerty, M., Patel, S. Y., Jeong, J., Chen, Q., & Munson, M. R.(2025). Prevalence and Geographic Variation of Serious Mental Illness Among Young Adults Enrolled in Medicaid in New York State. Journal of Adolescent Health, Volume 77. https://doi.org/10.1016/j.jadohealth.2025.01.010
Nicholson Jr, H. L., Yoo, N., Okazaki, S., Chang, D. F., & Craig, M. A.(2025). Inter-minority Relations: Factors Shaping Cognitive and Affective Intergroup Attitudes between Asian and Black Americans. Social Problems, spae075. https://doi.org/10.1093/socpro/spae075
Stanhope, V., Yoo, N., Matthews, E., Baslock, D., & Hu, Y.(2024). The Impact of Collaborative Documentation on Person-Centered Care: Textual Analysis of Clinical Notes. JMIR Med Inform, 12:e52678. https://doi.org/10.2196/52678
Yoo, N., Nicholson, H., Chang, D.F., Okazaki, S., & Craig, M.(2023). Mapping Anti-Asian Xenophobia: State-Level Variation in Implicit and Explicit Bias against Asian Americans across the United States. Socius: Sociological Research for a Dynamic World, Volume 9. https://doi.org/10.1177/23780231231196517
Yoo, N., Matthews, L., Stanhope, V., & Baslock, D.(2023). Impact of Collaborative Documentation on Completeness and Length of Clinical Notes in Behavioral Health Settings. Psychiatric Services, 75(2):186-190. https://doi.org/10.1176/appi.ps.20230118
Chang, D.F., Yoo, N., Lee, C., Prasai, A., & Okazaki, S.(2023). From racial awakening to collective action: Asian Americans' pathways to activism and benevolent support during COVID-19. Cultural Diversity and Ethnic Minority Psychology, 29(4):503-515. https://doi.org/10.1037/cdp0000617
Okazaki, S., Lee, C. S., Prasai, A., Chang, D. F., & Yoo, G.(2022). Disaggregating the data: Diversity of COVID-19 stressors, discrimination, and mental health among Asian American communities. Frontiers in Public Health, 10:956076. https://doi.org/10.3389/fpubh.2022.956076

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