Pavel Krivitsky

Dr. Pavel Krivitsky is a researcher at the School of Mathematics and Statistics of the University of New South Wales (UNSW) Sydney. His work focuses on developing methods and models for analyzing complex network data, with applications in epidemiology, social sciences, and national security. He maintains popular R packages like ergm and contributes to the Statnet Project and uDASH (UNSW Data Science Hub).

• PhD in Statistics, University of Washington (2009)
• MS in Statistics, University of Washington (2006)
• BS in Biometry and Statistics, Cornell University (2003)

His research spans social network analysis, computational statistics, and stochastic modeling, particularly for unusual or indirectly observed network data. Recent publications highlight advancements in multi-criteria recommender systems, network sampling techniques, and corrections for international datasets.

Scientific Awards:

• 2024 Mid-career Impact Award for Fundamental Research (UNSW Science)
• 2023 Journal of the American Statistical Association Discussion Paper
• 2019 Freeman Award for social structure research
• 2019 Richards Award for open-source software development

Dr. Krivitsky supervises PhD students Saman Forouzandeh (2021–2025) and Yun Pan (2022–). He teaches courses like MATH3831 (Statistics in Social and Market Research) and DATA5002 (Data Visualisation), previously instructing MATH5855 (Multivariate Analysis) and DATA1001 (Fundamentals of Data Science).