معرفی
Aleksey Polunchenko is an Associate Professor in the Department of Mathematics and Statistics at Binghamton University. His research focuses on mathematical statistics, particularly sequential change-point detection with applications in financial surveillance, anomaly detection, and statistical process control. He has made significant contributions to the analysis of the Shiryaev-Roberts procedure and related methods, including their asymptotic properties, robustness, and performance evaluation.
Education:
- PhD, University of Southern California
His recent publications explore the quasi-stationary distributions, first exit times, and asymptotic optimality of change-point detection algorithms, with applications in real-time financial monitoring and cybersecurity. While no scientific awards are listed, his work has been cited in multi-sensor systems and distributed detection frameworks.
Email: aleksey@binghamton.edu
