Regina Dolgoarshinnykh is an Adjunct Assistant Professor in the Department of Statistics at Columbia University. She joined the university in 2003 as an assistant professor and has since 2009 held a non-tenure track position. From 2010 onward, she has been an associate researcher and graduate consulting advisor in the Statistics Department. She currently serves as the Program Director of the M.S. in Actuarial Science program in the School of Professional Studies. Dolgoarshinnykh received her Ph.D. in Statistics from the University of Chicago in 2003, where her dissertation was titled "Epidemic Modelling: SIRS Models." Prior to her doctorate, she earned a B.A. in Mathematical and Actuarial Science from Central Connecticut State University. She is a member of the American Statistical Association and the Institute of Mathematical Statistics.

Dr. Dolgoarshinnykh teaches graduate-level courses including probability theory, statistical inference such as STAT GR6105 Statistical Inference Theory II, data science, epidemic modeling, theory of interest, and actuarial science topics like ACTU PS5823 Pricing and Reserving for Short-Term Insurance. She directs the department's doctoral student consulting service, running a university-wide statistical consulting program. Her research interests encompass probabilistic modeling of infectious disease spread and detecting transmission pathways in networks non-observable at event times, with focus on stochastic epidemic models. Key publications include her preprint "Sample path large deviations for SIRS epidemic processes" (2009) and "Critical scaling for the simple SIS stochastic epidemic," co-authored with S.P. Lalley in the Journal of Applied Probability (2006). She presented a seminar titled "Threshold Phenomena in Simple Epidemics with Recovery Time" at the DIMACS Center. Affiliated with the Institute for Social and Economic Research and Policy at Columbia University, she has over two decades of experience contributing to statistical education, research, and consulting.

Professional Email: rdolgoarshinnykh@stat.columbia.edu