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Faculty
Mai Dahshan
Assistant Professor of Data Science
School of Data Science
Mai Dahshan is a data scientist and researcher specializing in intelligent user interfaces and their application to human-AI partnerships. She designs and develops visual analytical systems to explore and analyze high-dimensional single and multimodal data. Her work focuses on creating user-centered visual analytics tools that integrate and coordinate human and artificial intelligence in scientific and health care fields to quantify patterns, identify trends, and uncover relationships within the data. Her research also involves developing predictive models to forecast patterns and understand the evolution of phenomena. Additionally, she conducts research on integrating computational thinking and data science education in K-2 STEM subjects.
Dahshan received her Ph.D. in computer science from Virginia Tech, co-advised by Dr. Nicholas Polys and Dr. Chris North. Before that, she received her master's degree in computer science from the American University in Cairo and bachelor's degree in computer science from Suez Canal University. Before joining UVA in 2024, she served as an assistant professor at the University of North Florida, teaching data science courses and conducting research in visualization and computer education. Additionally, she worked as a research intern at Los Alamos National Lab in 2019.
Education
- Ph.D. in Computer Science, Virginia Tech
- M.S. in Computer Science, American University in Cairo, Egypt
- B.S. in Computer Science, Suez Canal University in Egypt
Selected Publications
Dahshan, M., Polys, N., House, L., North, C., Pollyea, R.M., Turton, T.L. and Rogers, D.H. (2024). Human–machine partnerships at the exascale: exploring simulation ensembles through image databases. Journal of Visualization, pp.1-19.
Dahshan, M., Polys, N.F., House, L., Youssef, K. and Pollyea, R.M. (2024(. Human-Machine Collaboration for the Visual Exploration and Analysis of High-Dimensional Spatial Simulation Ensembles. In VISIGRAPP (1): GRAPP, HUCAPP, IVAPP (pp. 678-689).
Dahshan, M. and Galanti, T. (2024). Teachers in the Loop: Integrating Computational Thinking and Mathematics to Build Early Place Value Understanding. Education Sciences, 14(2), p.201.
Mohamed, M.F.,Dahshan, M., Li, K. and Salah, A. (2023). Virtual Machine Replica Placement Using a Multiobjective Genetic Algorithm. International Journal of Intelligent Systems, 2023(1), p.8378850
Dahshan, M., Polys, N., Jayne, R., and Pollyea, R. (2020). Making sense of scientific simulation ensembles with semantic interaction. In Computer Graphics Forum (Vol. 39, No. 6, pp. 325-343).
Panwar, P., pang, Y., Zhang, D.,Dahshan, M., Debardeleben, N., Ravindran, B. and Jian, X. (2019). Quantifying memory underutilization in hpc systems and using it to improve performance via architecture support. In Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture (pp. 821-835).
Dahshan, M.and Elkassass, S. (2014). Framework for securing data in cloud storage services. In 2014 11th International Conference on Security and Cryptography (SECRYPT) (pp. 1-8). IEEE.