Dr. Vijay Dhanasekaran

Associate Professor

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Biography

Vijay Dhanasekaran is an Adjunct Associate Professor at Monash University, specializing in the Laboratory of Virus Evolution. His research focuses on applying computational and experimental methods at the intersection of medicine, epidemiology, and population genetics to identify determinants of transmission and evolution across spatio-temporal scales. Dhanasekaran’s work emphasizes disease surveillance and genome sequencing, integrating genomic data with clinical, epidemiological, and immunological data derived from disease surveillance laboratory experiments, particularly using phylogenetic methods. His studies explore factors influencing the diversity and evolution of pathogens, particularly considering natural reservoirs in birds and bats, livestock production systems, and the origins of human pandemics. His research functionally investigates the effects of host innate and adaptive immune responses on the transmission of human pathogens, including influenza and Enterovirus 71. This scholarship has significantly contributed to the fields involved in epidemic preparedness and response, specifically regarding methodologies that incorporate multi-stream data to better understand infectious disease dynamics.

Research Interests

Experience

Adjunct Associate Professor

2019-03-01 — 2022-03-31

Monash University • Melbourne, Australia

Conduct research in virus genomics and evolution, focusing on disease surveillance and epidemiology.

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.