Curriculum Vitae
Curriculum Vitae Link
Education
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PhD, University of Maryland, 2024
Major: Information Systems
Dissertation: "Spatiotemporal Forecasting and Casuality Methods for the Arctic Amplification"
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MS, University of Maryland, 2023
Major: Information Systems
Dissertation: Spatiotemporal Forecasting and Causality Methods for Arctic Amplification
Current Scheduled Teaching
INFO 5707.021 | Data Modeling for Information Professionals | Spring 2025 |
Syllabus
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INFO 6910.029 | Special Problems | Spring 2025 |
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Texas Education Code 51.974 (HB 2504) requires each institution of higher education to make available to the public, a syllabus for undergraduate lecture courses offered for credit by the institution.
Previous Scheduled Teaching
INFO 5707.022 | Data Modeling for Information Professionals | Fall 2024 |
Syllabus
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SPOT
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Texas Education Code 51.974 (HB 2504) requires each institution of higher education to make available to the public, a syllabus for undergraduate lecture courses offered for credit by the institution.
Published Intellectual Contributions
- Ali, S., Wang, J. (2024). Tutorial on Causal Inference with Spatiotemporal Data. Proceedings of the 1st ACM SIGSPATIAL International Workshop on Spatiotemporal Causal Analysis. 23-25. ACM. https://doi.org/10.1145/3681778.3698786
- Ali, S., Faruque, O., Wang, J. (2024). Estimating Direct and Indirect Causal Effects of Spatiotemporal Interventions in Presence of Spatial Interference. Joint European Conference on Machine Learning and Knowledge Discovery in Databases.. 213-230. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-70352-2_13
- Lapp, L., Ali, S., Wang, J. (2023). Integrating Fourier Transform and Residual Learning for Arctic Sea Ice Forecasting. 2023 International Conference on Machine Learning and Applications (ICMLA). 1753-1758. IEEE. https://doi.org/10.1109/icmla58977.2023.00266
- Ali, S., Faruque, O., Huang, Y., Gani, M.O., Subramanian, A., Schlegel, N., Wang, J. (2023). Quantifying Causes of Arctic Amplification via Deep Learning Based Time-Series Causal Inference. 2023 International Conference on Machine Learning and Applications (ICMLA). 689-696. IEEE. https://doi.org/10.1109/icmla58977.2023.00101
- Ali, S., Mostafa, S.A., Li, X., Khanjani, S., Wang, J., Foulds, J., Janeja, V. (2022). Benchmarking Probabilistic Machine Learning Models for Arctic Sea Ice Forecasting. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. 4654-4657. IEEE. https://doi.org/10.1109/igarss46834.2022.9883505
- Kim, E., Kruse, P., Lama, S., Bourne, J., Hu, M., Ali, S., Huang, Y., Wang, J. (2021). Multi-Task Deep Learning Based Spatiotemporal Arctic Sea Ice Forecasting. 2021 IEEE International Conference on Big Data (Big Data). 1847-1857. IEEE. https://doi.org/10.1109/bigdata52589.2021.9671491
- Huang, X., Ali, S., Wang, C., Ning, Z., Purushotham, S., Wang, J., Zhang, Z. (2020). Deep Domain Adaptation based Cloud Type Detection using Active and Passive Satellite Data. 2020 IEEE International Conference on Big Data (Big Data). 1330-1337. IEEE. https://doi.org/10.1109/bigdata50022.2020.9377756
- Bushuk, M., Ali, S., Bailey, D.A., Bao, Q., Batté, L., Bhatt, U.S., Blanchard-Wrigglesworth, E., Blockley, E., Cawley, G., Chi, J., Counillon, F., Coulombe, P.G., Cullather, R.I., Diebold, F.X., Dirkson, A., Exarchou, E., Göbel, M., Gregory, W., Guemas, V., Hamilton, L., He, B., Horvath, S., Ionita, M., Kay, J.E., Kim, E., Kimura, N., Kondrashov, D., Labe, Z.M., Lee, W., Lee, Y.J., Li, C., Li, X., Lin, Y., Liu, Y., Maslowski, W., Massonnet, F., Meier, W.N., Merryfield, W.J., Myint, H., Navarro, J.C., Petty, A., Qiao, F., Schröder, D., Schweiger, A., Shu, Q., Sigmond, M., Steele, M., Stroeve, J., Sun, N., Tietsche, S., Tsamados, M., Wang, K., Wang, J., Wang, W., Wang, Y., Wang, Y., Williams, J., Yang, Q., Yuan, X., Zhang, J., Zhang, Y. (2024). Predicting September Arctic Sea Ice: A Multimodel Seasonal Skill Comparison. Other. 105 (7) E1170-E1203. American Meteorological Society. https://doi.org/10.1175/bams-d-23-0163.1
Contracts, Grants and Sponsored Research
- Ali, S., "Causality-at-Scale for Polar Regions (CSPR)," sponsored by NSF HDR Institute of Harnessing Data in Polar Regions, Local, $13000 Funded. (2024 - 2026).
- Ali, S., "Scientific Machine Learning for Analyzing Air Quality of North Texas," sponsored by College of Information, University of North Texas, $4200 Funded. (2025 - 2025).