Dr. Alexander Gluhovsky

Professor

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Biography

Alexander Gluhovsky is a Professor Emeritus at Purdue University's Department of Earth, Atmospheric, and Planetary Sciences. He specializes in applied mathematics, focusing on key areas such as geophysical fluid dynamics, atmospheric climate modeling, and computational statistics. His research engages low-order models and turbulent flows, alongside time series analysis methodologies in atmospheric studies, incorporating advanced statistical techniques including resampling methods and extreme value analysis. Gluhovsky has greatly contributed to understanding climate dynamics, through extensive publication of scholarly articles in prominent journals, covering topics ranging from statistical inference in atmospheric time series to modeling techniques for predicting climate behaviors. His educational background includes a Ph.D. from the USSR Academy of Sciences and a Master's from Moscow State University, equipping him with a solid foundation in mathematics and statistics. He is actively involved in teaching various courses in statistical methods and dynamics related to atmospheric sciences, enhancing student understanding and engagement in these critical fields.

Research Interests

Courses

Introduction Probability Models Elementary Statistical Methods Introduction Statistics Probability Introductory Time Series Statistical Methods Biology Statistical Methods Chaotic Dynamics Statistical Methods Atmospheric Sciences Statistics Extremes Trends, Extremes, Predictability Chaos Complexity Atmospheric Climate Dynamics Climate Time Series Analysis Data Analysis Techniques Introductory Statistics Geosciences

Requirements for Purdue University

Master Program
Requirements
GPA Requirement
Required:3.5
TOEFL
Listening
Required:22
Reading
Required:22
Writing
Required:22
Speaking
Required:22
Total
Required:100
IELTS
Listening
Required:7
Reading
Required:7
Writing
Required:7
Speaking
Required:7
Overall
Required:7.5
Duolingo
Overall Score
Required:135
Overall
Required:135
Prerequisites
Bachelor's degree in CS or related field Foundational concepts of computer science Data structures Computer architecture Operating systems Mathematics through differential equations Linear and matrix algebra
Application Checklist
  • Official Transcripts
  • Academic Statement of Purpose
  • Personal History Statement
  • Resume
  • Three Letters of Recommendation
  • CS Supplementary Form
Specialization Notes

GRE is not required.