Parisa Hajibabaee

Location Main Campus

Office BARC-1107

Directory Business Analytics, Data Science

Dr. Parisa Hajibabaee joined Florida Polytechnic University as an assistant professor in the Department of Data Science and Business Analytics (DSBA) in 2023. She holds an undergraduate degree in industrial engineering from Alzahra University and earned her first master's degree in IT management from Shahid Beheshti University. After working as a business analyst in Iran, she embarked on her journey to the United States, where she earned her second master's degree in industrial engineering from West Virginia University, followed by a Ph.D. in computer science from the University of Massachusetts Lowell.

Hajibabaee’s research is featured in prestigious machine learning conferences and journals, including IEEE ACCESS, the Journal of Engineering Structures, the Journal of Public Transportation, and the International Conference on Machine Learning and Applications (ICMLA). Beyond academia, she is certified as an AWS Cloud Practitioner, demonstrating her practical skills in cloud technologies.

With a collaborative mindset, Hajibabaee looks forward to contributing her expertise to the dynamic field of data science and business analytics. Her extensive educational journey and hands-on experience make her a valuable addition to any team tackling complex challenges.

Education

Ph.D. in Computer Science, University of Massachusetts Lowell, 2023
M.S. in Industrial Engineering, West Virginia University, 2020
M.S. in IT Management, Shahid Beheshti University, 2013
B.S. in Industrial Engineering, Alzahra University, 2011

Expertise

Machine Learning
Data Science
Business Analytics
Multi-Criteria Decision Making

Select Publications

Hajibabaee, P., Pourkamali-Anaraki, F., & Hariri-Ardebili, M. A. (2023). Dimensionality reduction techniques in structural and earthquake engineering. Engineering Structures, 278, 115485.
Hajibabaee, P., Pourkamali-Anaraki, F., & Hariri-Ardebili, M. A. (2021). Kernel Matrix Approximation on Class-Imbalanced Data With an Application to Scientific Simulation. IEEE Access, 9, 83579–83591. https://doi.org/10.1109/access.2021.3087730
Hajibabaee, P., Pourkamali-Anaraki, F., & Hariri-Ardebili, M. A. (2021, December). An empirical evaluation of the t-sne algorithm for data visualization in structural engineering. In 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA)(pp. 1674-1680). IEEE.
Pyrialakou, V. D., Hajibabaee, P., Williams, A., & Farrokhvar, L. (2023). Integrating ride-hailing services with transit: An exploratory planning framework. Journal of Public Transportation, 25, 100056.

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