Rohitash Chandra

Dr. Rohitash Chandra is a Senior Lecturer in Data Science at the University of New South Wales (UNSW) School of Mathematics and Statistics. He leads research in AI methodologies (e.g., Bayesian deep learning, neuroevolution) with applications to climate extremes, geoscience models, mineral exploration, biomedicine, and ancient religious text analysis. He is the Data Theme Lead of the ARC ITTC Training Centre for Data Analytics in Minerals and Resources (2020–2025) and a Chief Investigator in NHMRC projects on AI-driven drug repurposing for COVID-19.

Education: PhD in Artificial Intelligence (Victoria University of Wellington, 2012), MSc (University of Fiji, 2008), BSc (University of the South Pacific, 2006).

Research Interests: His work spans AI-driven climate modeling (cyclone forecasting, paleoclimate analysis), geoscience applications (remote sensing for mineral exploration), medical diagnosis (skin cancer detection, drug repurposing), and AI in humanities (sentiment analysis of religious texts like the Bhagavad Gita). He pioneers methods like Bayeslands for geoscientific parameter estimation and Bayesreef for reef evolution modeling.

Articles Trends: Recent work focuses on LLM applications in cultural analysis, economic forecasting frameworks, and Bayesian neural networks for uncertainty quantification. His publications bridge AI with interdisciplinary challenges in earth sciences, healthcare, and social sciences.

Grants & Awards: Recipient of the UNSW Science Silverstar Award (2022), Sydney Fellowship (2017–2019), and over $10M in ARC/industry funding. He has supervised 40+ students across PhD, masters, and honours programs.

Labs & Teams: Founder of the Transitional Artificial Intelligence Research Group (t-AI). Collaborates with EarthByte Group, UN agencies, and institutions like Imperial College London on projects ranging from Mars landscape modeling to Hindu philosophy LLMs like Vedanta-GPT.