Dr. Songlin Fei

Professor

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Biography

Dr. Songlin Fei serves as a professor and the Dean's Remote Sensing Chair in the Department of Forestry and Natural Resources (FNR) at Purdue University. His research focuses on advanced spatial analysis and pattern recognition, with a particular emphasis on modeling the distribution of invasive species and understanding dynamics in forest ecosystems. Dr. Fei is dedicated to leveraging digital technologies to enhance the measurement, monitoring, and management of urban and rural forests, with the ultimate aim of maximizing their social, economic, and ecological benefits. He collaborates extensively within Purdue's Integrated Digital Forestry initiative, fostering partnerships for innovative research and education. Dr. Fei's work also contributes to the advancement of quantitative methods related to statistical and analytical modeling of natural systems, essential for ecosystem management and restoration. His scholarly contributions include numerous publications and involvement in various research centers focused on human-environment modeling and spatial data analysis. He actively engages with students and the broader research community, participating in workshops and seminars to disseminate knowledge and inspire new discoveries in the field.

Research Interests

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.