Sitemap

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

* 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](https://www.sciencedirect.com/science/article/pii/S1532046421001672)]

* 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](https://epjds.epj.org/articles/epjdata/abs/2022/01/13688_2022_Article_366/13688_2022_Article_366.html)]

* 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](https://www.sciencedirect.com/science/article/pii/S0198971523000303)]

* 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](http://saad-abrar.github.io/files/easm_2023.pdf)]

* Abrar, S.M.*</b>, 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](https://dl.acm.org/doi/pdf/10.1145/3588001.3609374)]

* 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](https://arxiv.org/pdf/2407.10304)]

* 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](https://infodemiology.jmir.org/2023/1/e43703)]

* 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](https://dl.acm.org/doi/pdf/10.1145/3616380)]

* 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](https://dl.acm.org/doi/abs/10.1145/3764924.3770890)]

* 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](https://aclanthology.org/2025.findings-emnlp.1266/)]

* 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](https://www.tandfonline.com/doi/full/10.1080/13645579.2025.2571689?scroll=top&needAccess=true)]

* 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](https://doi.org/10.1371/journal.pone.0319383)]

* 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](https://zcliu.org/papers/VLM_ProcessVis_Vizwiz25.pdf)]

* 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) [[PDF]()]

*

*

*

*

*

*