Aishwarya Bhaskaran

Aishwarya Bhaskaran is a Lecturer in Theoretical Statistics at Macquarie University's School of Mathematical and Physical Sciences. She holds a PhD in Statistics from the University of Technology Sydney (Award Date: 1 August 2023) and completed a postdoctoral position at Macquarie University. Her research focuses on theoretical and methodological advancements in survival analysis, generalised linear mixed models, asymptotic theory, and variational approximation methods. She emphasizes scalability for large datasets and bridging statistical theory with real-world applications.

Education:

• PhD in Statistics, University of Technology Sydney (2023)

Research Interests: Her work spans survival analysis, generalised linear mixed models, asymptotic theory, Bayesian inference (particularly variational approximation methods), and scalable statistical methodologies. She explores applications in biostatistics, computational statistics, and mathematical modeling.

Teaching: She teaches STAT7111/8111: Generalized Linear Models (S2, 2024) and STAT3191/6191: Statistical Inference for Data Science (S1/S2, 2025).

Publications: Recent work includes advancements in asymptotic theory for mixed models, survival analysis methods, and scalable Bayesian variational techniques. Her 2024 papers highlight improvements in GLMM asymptotics and penalized likelihood approaches for censored data.

Collaborations: Engages in collaborations across statistical theory and methodology, with a focus on interdisciplinary applications. Active in Australia’s academic statistical community.