Publications

Abrar, S. M., & Frias-Martinez, V. (2026). Fairness and Equity in AI for Societal Decision Making. In Encyclopedia of GIS (Eds. Shekhar, Xiong, Zhou, and Xie). (In Press)

Awasthi, N., Abrar, S., Smolyak, D., & Frias-Martinez, V. (2026). Fairness Correction in COVID-19 Predictive Models Using Demographic Optimization: Algorithm Development and Validation Study. Online Journal of Public Health Informatics, 18, e78235. https://doi.org/10.2196/78235 [PDF]

Jagtap, O., Awasthi, N., Jain, M., Abrar, S. M., & Frías-Martínez, V. (2025). Beyond Mode Detection: Reconstructing Detailed Transit Itineraries from Crowdsourced GPS Trajectories. In Proceedings of the 1st ACM SIGSPATIAL International Workshop on Spatial Intelligence for Smart and Connected Communities (pp. 35-38). [PDF]

Zinat, K. T.*, Abrar, S. M.*, Saha, S., Sakhamuri, S., Duppala, S., & Liu, Z. (2025). ProcVQA: Benchmarking the Effects of Structural Properties in Mined Process Visualizations on Vision–Language Model Performance. In Findings of the Association for Computational Linguistics: EMNLP 2025. (* equal contribution) [PDF]

Antoun, C., Frías-Martínez, V., Garove, A., Awasthi, N., & Abrar, S. M. (2025). Engaging underserved communities in smartphone-based research: comparing mailings, advertisements, and in-person recruitment strategies. International Journal of Social Research Methodology, 1-21. [PDF]

Abrar, S. M., Awasthi, N., Smolyak, D., Sigalo, N., & Martinez, V. F. (2025). Auditing the fairness of the US COVID-19 forecast hub case prediction models. PloS one, 20(4), e0319383. [PDF]

Zinat, K. T., Abrar, S. M., Duppala, S., Sakhamuri, S. N., & Liu, Z. (2025). Evaluating VLMs as Accessibility Bridges for Process Visualizations. CVPR 2025 Workshop on the VizWiz Grand Challenge. [PDF]

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.*, Park, S. & Vitak, J & Frias-Martinez, V. (2022). The BALTO Toolkit - A New Approach to Ethical and Sustainable Data Collection for Equitable Public Transit. [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]