Dr. Andrew Casey

Associate Professor

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Biography

Andrew Casey works on computational data analysis problems across multiple fields of research, with a primary focus on astrophysics. He aims to combine physically interpretable models with data-driven methods to drive advancements in stellar astrophysics. His research interests span astrophysics, aerospace engineering, biology, statistics, optimization, Bayesian inference, artificial intelligence, data science, algorithms, and other computational data analysis problems. He received his PhD in Astronomy & Astrophysics from the Australian National University and spent time at the Massachusetts Institute of Technology as a visiting graduate student. In 2014, he began post-doctoral research at the University of Cambridge as a Senior Member at King's College. In 2017, he accepted a research fellowship in astrophysics statistics at Monash University, and in September 2019 he began a Discovery Early Career Researcher Award project funded by the Australian Research Council. His expertise contributes to the UN Sustainable Development Goals.

Research Interests

Experience

Associate Professor

2017-01-01 — Present

Monash University • Melbourne

Teaching and conducting research in astrophysics and related fields.

Awards

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Young Tall Poppy Award

2018-11-15
#

Fresh Science

2018-06-15
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Australian Prime Minister's Endeavour Award

2011-01-01

Requirements for Monash University

Master Program
Requirements
GPA Requirement
Required:3
IELTS
Listening
Required:6
Reading
Required:6
Writing
Required:6
Speaking
Required:6
Overall
Required:6.5
TOEFL
Listening
Required:12
Reading
Required:13
Writing
Required:21
Speaking
Required:18
Total
Required:79
Prerequisites
Bachelor degree (or equivalent) in a related field
Application Checklist
  • Academic Transcripts
  • Proof of English Proficiency
  • Curriculum Vitae
  • Copy of Passport
Specialization Notes

Requirements are standardized across the Faculty of Information Technology for most Master's programs including Computer Science and Data Science.