Research & Innovation
Using data science and research for innovative solutions to transform urban challenges into actionable insights.
"Data work is what we do."
Research Spotlight:
AI Report to NJ Governor
In 2024, IDRIS leadership contributed expertise to the report to the Governor on Artificial Intelligence.
This comprehensive report, developed by a state-appointed Task Force including IDRIS Executive Director Dr. Fay Cobb Payton and Associate Professor Gregory Porumbescu, examines the potential societal impacts of emerging AI technologies, particularly Generative AI (GenAI).
The report provides findings and recommendations aimed at ensuring New Jersey leverages AI responsibly and ethically to improve government services, enhance equity, foster innovation, and create economic opportunities for its residents. Key areas addressed include safety and privacy considerations, workforce training, Al equity and literacy, and strategies for making New Jersey a hub for AI innovation.
Regional Research Participation
NSF I-Corps Hub Northeast Region
IDRIS extends its research influence and commitment to innovation through active participation in significant regional initiatives.
IDRIS Executive Director Dr. Fay Cobb Payton served as an Research and Evaluation Lead for the NSF I-Corps Hub Northeast Region.
Dr. Fay Cobb Payton
Executive Director, Institute for Data, Research, and Innovation Science (IDRIS)
About the NSF I-Corps Hub Northeast Region
The NSF I-Corps Hub Northeast Region supports researchers in transforming scientific discoveries into market-ready products and services that benefit society.
It offers free events, mentorship, and accelerator programs through a collaborative network of universities to help innovators assess and advance the feasibility of their ideas.
Featured Research Publications & Conferences
Pengju Zhang Ph.D.
Associate Professor
Research Focus: Local Government Fiscal Health
- Zhang, Pengju, Jinah Yoo and Carolyn Abott. (working paper) The Bankruptcy of Special Districts in the United States: What, When, and Why?
- Zhang, Pengju, and David Guo. (2024). Navigating local fiscal sustainability: topics and challenges. Local Government Studies, 50(6), 1094–1104. https://doi.org/10.1080/03003930.2024.2408629
- Hayes, M. S., Rubin, J. S., and Zhang, Pengju. (2023). The state takeover of the Camden City District schools and students’ academic performance: A descriptive analysis. Journal of Urban Affairs, 47(4), 1348–1370. https://doi.org/10.1080/07352166.2023.2216886.
Anthony Mayo Ph.D.
Biomedical Informatics Co-Adjutant
Research Focus: Computational Models for Substance Use Disorder (SUDS)
- Mayo, Anthony, “Trends in Substance-Related Emergency Department Visits and Treatment Outcome in Individuals with Substance Use Disorder in the United States”, Global Learning through Global Health: Advancing Common Goals, Together, December 4, 2019, Office of Global Health & Brain Health Institute, Rutgers Robert Wood Johnson Medical School.
- Mayo, Anthony, “Trends in Substance-Related Emergency Department Visits and Treatment Outcome in Individuals with Substance Use Disorder in the United States”, Computational Models in Disease: Applications and Implications, May 9, 2019, Rutgers Robert Wood Johnson Medical School.
- Frank E, Tu XM, Anderson B, Reynolds CF 3rd, Karp JF, Mayo A, Ritenour A, Kupfer DJ. Effects of positive and negative life events on time to depression onset: an analysis of additivity and timing. Psychol Med. 1996 May;26(3):613-24. doi: 10.1017/s0033291700035686. PMID: 8733219.
- Stack JA, Paradis CF, Reynolds CF 3rd, Houck PR, Frank E, Anderson B, Mayo AL, Miller MD, Rifai AH, Perel JM, et al. Does recruitment method make a difference? Effects on protocol retention and treatment outcome in elderly depressed patients. Psychiatry Res. 1995 Jan 31;56(1):17-24. doi: 10.1016/0165-1781(94)02617-r. PMID: 7792338.
Kimele Persaud Ph.D.
Assistant Professor of Psychology and MC² Lab Director
Research Focus: Employing computational cognitive models to understand semantic and episodic memory processes across development.
- Macias, C., & Persaud, K. (2024). From silos to synergy: Integrating approaches to investigate the role of prior knowledge and expectations on episodic memory. Psychonomic Bulletin & Review, 31(6), 2390–2409. https://doi.org/10.3758/s13423-024-02505-4
- Persaud, K., & Hemmer, P. (2024). The influence of functional components of natural scenes on episodic memory. Scientific reports, 14(1), 1-11. DOI: 10.1038/s41598-024-81900-2
- Persaud, K., Macias, C., Hemmer, P., & Bonawitz, E. (2021). Evaluating recall error in preschoolers: Category expectations influence episodic memory for color. Cognitive psychology, 124, 101357. DOI: 10.1016/j.cogpsych.2020.101357