Dr. Bogdan Gadidov is an adjunct lecturer of Data Science in the Applied Engineering and Sciences Department at the University of New Hampshire. He has also taught courses in the Graduate Program in Analytics and Data Science at UNH.
His research focuses on non-parametric regression and smoothing techniques, with applications on financial data. He is also interested in healthcare applications of non-parametric techniques, working on several studies analyzing survival outcomes for patients with a ventricular assist device. Other research areas have included NLP techniques for analyzing online text reviews and comments.
- Ph.D. in Analytics and Data Science, Kennesaw State University
- M.S. in Applied Statistics, Kennesaw State University
- B.S. in Industrial and Systems Engineering, Georgia Institute of Technology
- Data 800 – Introduction to Analytical Statistics
- Data 801 – Foundations of Data Analytics
- Data 820 – Programming for Data Science
- Data 822 – Data Mining and Predictive Modeling
refereed journal articles
Rohm, C., Gadidov, B., Ray, H., Mannino, S., Prasad, R. (2020, December). Vasopressors and inotropes as predictors of mortality in acute severe cardiogenic shock treated with the Impella device. Cardiovascular Revascularization Medicine.
Rohm, C., Gadidov, B., Leitson, M., Ray, H., & Prasad, R. (2019, August). Predictors of mortality and outcomes of acute severe cardiogenic shock treated with the Impella device. American Journal of Cardiology 124(4), 499-504.
Huber, S., Kasabwala, K., Gadidov, B., Priestley, & J., Culligan, P. (2019). Understanding your online ratings: a methodological analysis using urogynecologists in the United States. Female Pelvic Medicine & Reconstructive Surgery 25(2) 193-197.
Huber SA, Priestley J, Kasabwala K, Gadidov B, Culligan P. Understanding Your Online Ratings: A Methodological Analysis Using Urogynecologists in the United States. Female Pelvic Med Reconstr Surg. 2019 Mar/Apr;25(2):193-197.
Refereed Chapters in Books
Gadidov B., & Priestley J. L. (2017). Does Yelp matter? Analyzing (and guide to using) ratings for a quick serve restaurant chain. In Srinivasan S. (Eds.), Studies in Big Data: Vol. 26. Guide to big data applications (pp. 503-522). Cham, Switzerland: Springer International Publishing.
Gadidov, B., & Le, Linh. (2018). A Case Study of Mining Social Media Data for Disaster Relief: Hurricane Irma. Paper presented at SAS Global Forum 2018, Denver, CO.
Gadidov, B., & Ray, H. E. (2017). Analyzing residuals in a proc surveylogistic model. Paper presented at SAS Global Forum 2017, Orlando, FL.
Gadidov, B., & McBurnett, B. (2015). Population stability and model performance metrics replication for business model at SunTrust Bank. Paper presented at SouthEast SAS Users Group 2015, Savannah, GA.