Peter Radchenko

Professor Peter Radchenko is a leading academic in Statistics at the University of Sydney Business School. Prior to joining Sydney in 2017, he held positions at the University of Chicago and the Marshall School of Business, University of Southern California. He earned a PhD in Statistics from Yale University and an undergraduate degree in Mathematics from Lomonosov Moscow State University.

Education:

• PhD in Statistics, Yale University
• Bachelor's in Mathematics/Applied Mathematics, Lomonosov Moscow State University

Research Interests: Professor Radchenko specializes in high-dimensional statistics and statistical machine learning, focusing on methods for analyzing complex modern datasets. His work addresses challenges in high-dimensional regression, large-scale clustering, functional data analysis, and optimization-driven statistical techniques. Notable contributions include mixed-integer optimization approaches for sparse models and advancements in variable selection under low-signal conditions.

Research Trends: His recent work emphasizes optimization-based solutions for discrete statistical problems, particularly in sparse modeling and subset selection. This aligns with broader themes of leveraging computational efficiency for high-dimensional data challenges.

Awards & Honors:

• Elected Member, International Statistical Institute (ISI)
• 2023 INFORMS Computing Society Prize Honorable Mention
• Australian Research Council Grants (2025, 2019)
• US National Science Foundation Grant (2012)
• Teaching Excellence Awards (University of Sydney, 2018–2024)

Grants & Advising: Current research student: Sanghyun KIM (Forecast Reconciliation). Grants include collaborations with Cornell University and multidisciplinary initiatives at the University of Sydney. His research has been supported by major funding bodies globally.

Labs & Teams: His work is embedded within the University of Sydney Business School’s analytics research groups, focusing on statistical methodology and its applications in business and health.