Mohammad Ali Alamdar Yazdi, PhD

Mohammad Ali Alamdar Yazdi is an Associate Professor of Practice at the Johns Hopkins Carey School Business. He holds an MS in Computer Science, an MEng and a PhD in Industrial and Systems Engineering, all from the Auburn University. He received a bachelor's degree in Industrial Engineering from Sharif University of Technology, Iran. He is interested in Data Analytics and Data Visualizations.

Education

• Ph. D, Industrial Systems Engineering, Auburn University
• MS, Comp Science and Software Engineering, Auburn University
• MS, Industrial and Systems Engineering, Auburn University
• BS, Industrial Engineering, Sharif University of Technology

Research

Selected publications

• Dada, M., Vishal Mundly, V., Chambers, C., Alamdar Yazdi, M. A., Ha, C., Toporcer, S., Zhou, Y., Gan, Y., Xing, Z., Mooney, M., Smith, E., Kumian, E., Williams, K. (2022). Managing prior approval for site-of-service referrals: an algorithmic approach. BMC Health Services Research, 22(1), 1-7. 
• Cai, M., Mehdizadeh, A., Hu, Q., Alamdar Yazdi, M. A., Vinel, A., Davis, K. C., ... & Rigdon, S. E. (2022). Hierarchical point process models for recurring safety critical events involving commercial truck drivers: A reliability framework for human performance modeling. Journal of Quality Technology, 54(4), 466-484.
• Mehdizadeh, A., Alamdar Yazdi, M. A., Cai, M., Hu, Q., Vinel, A., Rigdon, S. E., ... & Megahed, F. M. (2021). Predicting unsafe driving risk among commercial truck drivers using machine learning: lessons learned from the surveillance of 20 million driving miles. Accident Analysis & Prevention, 159, 106285 (1-12).
• Cai, M., Alamdar Yazdi, M. A., Mehdizadeh, A., Hu, Q., Vinel, A., Davis, K., ... & Rigdon, S. E. (2021). The association between crashes and safety-critical events: Synthesized evidence from crash reports and naturalistic driving data among commercial truck drivers. Transportation Research Part C: Emerging Technologies, 126, 103016 (1-19). 
• Mehdizadeh, A., Cai, M., Hu, Q., Alamdar Yazdi, M. A., Mohabbati-Kalejahi, N., Vinel, A., ... & Megahed, F. M. (2020). A review of data analytic applications in road traffic safety. Part 1: Descriptive and predictive modeling. Sensors, 20(4), 1107 (1-24). 
• Hu, Q., Cai, M., Mohabbati-Kalejahi, N., Mehdizadeh, A., Alamdar Yazdi, M. A., Vinel, A., ... & Megahed, F. M. (2020). A review of data analytic applications in road traffic safety. Part 2: Prescriptive modeling. Sensors, 20(4), 1096 (1-19).
• Alamdar Yazdi, M. A., Negahban, A., Cavuoto, L., & Megahed, F. M. (2019). Optimization of split keyboard design for touchscreen devices. International Journal of Human–Computer Interaction, 35(6), 468-477.
• Maman, Z. S., Alamdar Yazdi, M. A., Cavuoto, L. A., & Megahed, F. M. (2017). A data-driven approach to modeling physical fatigue in the workplace using wearable sensors. Applied Ergonomics, 65, 515-529.

Teaching

Current

• Business Analytics and Statistics
• Data Analytics 
• Data Science: Big Data Consulting Project
• Data Visualization 
• Python for Data Analysis

Previous

• Simulation and Strategic Options
• Statistical Analysis

Honors and distinctions

• Dean’s Award for Faculty Excellence at Carey Business School, 2022 & 2023 
• Outstanding Ph.D. Student of Department of Industrial and Systems Engineering, Auburn University, 2018