Rate My Professor Suman Rakshit

In addition to agricultural applications, Rakshit's research extends to data science, machine learning, probability theory, statistical modeling, computational statistics, and programming languages. He has contributed significantly to fields such as ecology, astronomy, mineral prospectivity, and sports analytics. Notable publications include 'New Metrics for Identifying Variables and Transients in Large Astronomical Surveys' (2025), 'ROC Curves for Spatial Point Patterns and Presence-Absence Data' (2025), 'Mineral prospectivity analysis is unstable to changes in pixel size' (2025), 'A Novel Clustering Framework to Identify Team Playing Styles Within Australian Football' (2025, SN Computer Science), 'Probabilistic approaches for investigating species co-occurrence from presence-absence maps' (2023, Ecology and Evolution), 'Fundamental problems in fitting spatial cluster process models' (2022), 'Bayesian inference of spatially correlated random parameters for on-farm experiment' (2022), 'Variable selection using penalised likelihoods for point patterns on a linear network' (2021, Australian & New Zealand Journal of Statistics), 'Analysing point patterns on networks—A review' (2020, Spatial Statistics), and 'Second-order analysis of point patterns on a network using any distance metric' (2017). Rakshit has also presented his research at events such as the WA Branch Meeting of the International Biometric Society and Statistical Society of Australia, where he discussed experimental designs. His expertise includes network analysis, R statistical package, data analysis, statistical inference, logistic regression, hypothesis testing, and regression modeling.