
Keywords
Fields of Research (FoR)
Computational statistics, Probability theory, Machine learning, Deep learning, OptimisationSEO tags
Biography
Homepage: https://saratmoka.com
I am a Lecturer (equivalent to Assistant Professor in North America) in the School of Mathematics and Statistics at the University of New South Wales, Sydney, since 2023. My research and teaching interests span Statistics, Probability Theory, Machine Learning, and Deep Learning. Previously, I was a Research Fellow in the School of Mathematical and Physical Sciences at Macquarie University, and before that, an...view more
Homepage: https://saratmoka.com
I am a Lecturer (equivalent to Assistant Professor in North America) in the School of Mathematics and Statistics at the University of New South Wales, Sydney, since 2023. My research and teaching interests span Statistics, Probability Theory, Machine Learning, and Deep Learning. Previously, I was a Research Fellow in the School of Mathematical and Physical Sciences at Macquarie University, and before that, an ACEMS (ARC Centre of Excellence for Mathematical and Statistical Frontiers) Postdoctoral Researcher at the University of Queensland, Brisbane. I hold a PhD in Applied Probability from the Tata Institute of Fundamental Research (Mumbai), as well as master’s and bachelor’s degrees in engineering from the Indian Institute of Science (Bengaluru) and Andhra University, respectively. Prior to my PhD, I worked as a scientist at the Indian Space Research Organization, focusing on communication networks related to rocket launch activities. I am a co-author of a book on `Mathematical Engineering of Deep Learning`.
For more details, visit https://saratmoka.com
My Grants
- Estimating the Number of Tyres in Stockpiles: Phase II (2024). Project commissioned by Environmental Protection Authority (EPA) Victoria. Jointly with Prof. Samuel Muller, Macquarie University.
My Qualifications
- PhD in Applied Probability
- Master of Engineering in Telecommunication
- Bachelor of Engineering in Electronics and Electrical Engineering
My Research Activities
My research aims to devise efficient algorithms for addressing challenging problems, often they are NP-hard, within the realms of Applied Probability, Computational Statistics, Machine Learning, and Deep Learning. Keywords relevant to my research include Model Selection, Best Subset Selection, Monte Carlo Simulation, Spatial Point Processes, Bayesian Inference, Perfect Sampling, Importance Sampling, Unbiased Estimation, Large Deviations Theory, Variance Reduction Techniques, and Queueing Theory.
Click here for a list of publications to gain a detailed insights into my research.
My Research Supervision
Areas of supervision
- Applied Probability including Monte Carlo Simulation, Random Graphs, Unbiased Estimation, and Large Deviations Theory
- Computational Statistics including Optimization Methods for sparsity constrained problems
- Deep Learning including Model Compression and Graph Neural Networks
Please visit https://saratmoka.com/projects/ to see some of the ongoing projects in my group.
Currently supervising
Please visit https://saratmoka.com/supervision/ for details.
My Engagement
I am keen to engage with industry to address challenges that require innovative statistical and probabilistic solutions. My current industry collaborators include EPA Victoria and CSIRO.
My Teaching
Please visit https://saratmoka.com/teaching/ for a list of courses I am currently teaching or taught in the past.
Contact
Publications
ORCID as entered in ROS
