Dr. Garth Tarr

Associate Professor

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Biography

Garth Tarr is an accomplished Associate Professor specializing in Statistics and Data Science at the University of Sydney. With extensive expertise in feature selection and predictive modeling, Garth collaborates with industry bodies to provide actionable data-driven insights. He is also recognized for delivering exceptional learning experiences to students, having led the School of Mathematics and Statistics in implementing innovative educational methods. Garth is a member of the Sydney Precision Data Science Centre, focusing on robust statistics, biostatistics, and the modeling of complex agricultural data. His research aligns with the Faculty of Science's strategic strengths, contributing to areas such as food security and sustainable decision-making. Garth’s commitment to educational excellence has been acknowledged through multiple Vice-Chancellor’s Awards at the University of Sydney. He actively supervises PhD students and has delivered numerous short courses on advanced statistical techniques.

Research Interests

Experience

Associate Professor

2016-01-01 — Present

University of Sydney • Sydney, Australia

Teaching and researching in Statistics and Data Science.

Awards

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Vice-Chancellor’s Award Teaching and Learning Excellence

2023-01-01
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EJG Pitman Prize

2012-01-01

Courses

DATA2002 Data Analytics: Learning from Data DATA2902 Data Analytics: Learning from Data (Advanced) OLET5608 Linear Modelling

Requirements for University of Sydney

Doctorate Program
Requirements
GPA Requirement
Required:3.3
IELTS
Listening
Required:6
Reading
Required:6
Writing
Required:6
Speaking
Required:6
Overall
Required:6.5
TOEFL
Listening
Required:17
Reading
Required:17
Writing
Required:19
Speaking
Required:17
Total
Required:85
PTE
Listening
Required:54
Reading
Required:54
Writing
Required:54
Speaking
Required:54
Overall
Required:61
Prerequisites
A master's degree with a research component or a bachelor's degree with first or second-class honours. Demonstrated research experience and capability.
Application Checklist
  • Academic transcripts
  • Curriculum Vitae (CV)
  • Research proposal (1000+ words)
  • Two academic referee reports
  • Evidence of residency status
  • Written statement of support from potential supervisor
Specialization Notes

This entry applies to Faculty of Science PhD programs including Departments such as Life and Environmental Sciences, Physics, Chemistry, and Mathematics and Statistics.