Publications

* Wu, J., Abrar, S. M., Awasthi, N., & Frias-Martinez, V. (2023). Auditing the fairness of place-based crime prediction models implemented with deep learning approaches. Computers, Environment and Urban Systems, 102, 101967. [PDF]

* Abrar, S. M., Zinat, K. T., Awasthi, N., & Frias-Martinez, V. COVID-19's Unequal Toll: An assessment of small business impact disparities with respect to ethnorace in metropolitan areas in the US using mobility data. Equitable Accessibility and Sustainable Mobility Workshop 2023. [PDF]

* Abrar, S.M. *, Awasthi, N. *, Smolyak, D. *, & Frias-Martinez, V. Systematic analysis of the effectiveness of adding human mobility data to COVID-19 case prediction linear models. ACM Compass 2023. [PDF]

* Sigalo, N., Awasthi, N., Abrar, S. M., & Frias-Martinez, V. (2023). Using COVID-19 vaccine attitudes on Twitter to improve vaccine uptake forecast models in the United States: infodemiology study of Tweets. JMIR infodemiology, 3(1), e43703. [PDF]

* Abrar, S.M., Awasthi, N., Smolyak, D., & Frias-Martinez, V. (2023). Analysis of performance improvements and bias associated with the use of human mobility data in COVID-19 case prediction models. ACM Journal on Computing and Sustainable Societies, 1(2), 1-36. [PDF]

* Wu, J., Abrar, S.M., Awasthi, N., Frias-Martinez, E. & Frias-Martinez, V. (2022). Enhancing short-term crime prediction with human mobility flows and deep learning architectures. EPJ Data Science, 11(1), p.53. [PDF]

* Moon, C., Jin, C., Dong, X., Abrar, S., Zheng, W., Chirkova, R. Y., & Tropsha, A. (2021). Learning Drug-Disease-Target Embedding (DDTE) from knowledge graphs to inform drug repurposing hypotheses. Journal of biomedical informatics, 119, 103838. [PDF]