Nasibeh Azadeh Fard Headshot

Nasibeh Azadeh Fard

Visiting Professor
Department of Industrial and Systems Engineering
Kate Gleason College of Engineering

Nasibeh Azadeh Fard

Visiting Professor
Department of Industrial and Systems Engineering
Kate Gleason College of Engineering

Bio

Dr. Nasibeh Azadeh-Fard received her B.S. in Information Technology Engineering from Iran University of Science and Technology, and her M.S. and Ph.D. in Industrial and Systems Engineering from Virginia Tech. Prior to joining RIT, she was a postdoctoral fellow at Clemson University, Risk Engineering and System Analytics Center, where she conducted research on risk analysis and risk mitigation action plans for American International Group (AIG) insurance company.

Dr. Azadeh-Fard’s main research areas include healthcare systems engineering, risk analysis, early warning systems, and performance measurement and analysis. Her work has been published in peer reviewed journals including Journal of Patient Safety, Safety Science, and PLoS ONE.

Selected Publications

  • Azadeh-Fard, N., Ghaffarzadegan, N., Camelio, J., Can a patient’s in-hospital length of stay and mortality be explained by early-risk assessments?, PLoS ONE, 11(9), 2016.
  • Azadeh-Fard, N., Schuh, A., Rashedi, E., Camelio, J., Risk Assessment of Occupational Injuries Using Accident Severity Grade, Safety Science, Volume 76, 2015.
  • Bish, E., Azadeh-Fard, N., Steighner, L., Hall, K., Slonim, A., Proactive Risk Assessment of Surgical Site Infections in Ambulatory Surgery Centers, Journal of Patient Safety, 2014.

Currently Teaching

ISEE-661
3 Credits
In any system where parameters of interest change, it may be of interest to examine the effects that some variables exert (or appear to exert) on others. "Regression analysis" actually describes a variety of data analysis techniques that can be used to describe the interrelationships among such variables. In this course we will examine in detail the use of one popular analytic technique: least squares linear regression. Cases illustrating the use of regression techniques in engineering applications will be developed and analyzed throughout the course.
ISEE-510
3 Credits
Computer-based simulation of dynamic and stochastic systems. Simulation modeling and analysis methods are the focus of this course. A high-level simualtion language such as Simio, ARENA, etc., will be used to model systems and examine system performance. Model validation, design of simulation experiments, and random number generation will be introduced.
ISEE-789
3 Credits
Topics and subject areas that are not regularly offered are provided under this course. Such courses are offered in a normal format; that is, regularly scheduled class sessions with an instructor.
ISEE-610
3 Credits
Computer-based simulation of dynamic and stochastic systems. Simulation modeling and analysis methods are the focus of this course. A high-level simulation language such as Simio, ARENA, etc., will be used to model systems and examine system performance. Model validation, design of simulation experiments, and random number generation will be introduced.
ISEE-561
3 Credits
In any system where parameters of interest change, it may be of interest to examine the effects that some variables exert (or appear to exert) on others. "Regression analysis" actually describes a variety of data analysis techniques that can be used to describe the interrelationships among such variables. In this course we will examine in detail the use of one popular analytic technique: least squares linear regression. Cases illustrating the use of regression techniques in engineering applications will be developed and analyzed throughout the course.

Select Scholarship

Journal Paper
Shariatpanahi, Seyed Peyman, et al. "Assessing the Effectiveness of Disease Awareness Programs: Evidence From Google Trends Data For the World Awareness Dates." Telematics and Informatics 34. 7 (2017): 904-913. Web.
Azadeh-Fard, Nasibeh, Navid Ghaffarzadegan, and Jaime Camelio. "Can Early Risk Assessments Predict A Patient’s Hospital Length of Stay and Mortality?" PLoS ONE 11. 9 (2016): 1-9. Web.