Our projects

Delving into the academic fields of information systems and management, specifically where technology meets organizations—this project will examine how organizations adopt, adapt to and manage generative AI.

This interdisciplinary project in Health Neuroscience aims to explore potential neuroprotective factors in age-related cognitive-affective decline, gather insights to brain-cognition link and understand the neurodegeneration due to neurological and psychiatric comorbidities.

The transport of particles in suspension is of great significance in a range of biomedical applications (e.g. cell separation, margination in blood). This project will apply advanced computational analysis to study these phenomena and improve the design of a range therapeutic medical treatments.

Theoretical modelling using Q-tensor and active gel theory as well as numerical simulation will be used to establish how the degree of cytoskeletal organisation in the cortex drives the formation of cell structures such as filopodia or lamellipodia.

The project will develop new methods for creating stereoenriched fluorocarbons via frustrated Lewis pair (FLP) mediated monoselective C–F activation. Such methods will be of immense value to the pharma industry and look to utilise waste fluorocarbons as base materials.

The evolution of the southern Thar Desert margin, which was once densely populated ca. 5000 years ago during the Bronze Age, is unexplored. This project aims to reconstruct high resolution hydroclimate changes across the last 10,000 years using lake sediments from the southern Thar Desert margin.

Road networks, resilience to disasters such as floods, earthquakes, bushfires, etc., is key to maintaining continuity and ensuring efficient and safe movement. This project uses crowdsourced data and simulation to evaluate and compare the disaster resilience of Indian and Australian cities.

The project investigates generative AI's impact on software engineering in India and Australia. It analyses psychological and social consequences and job transformations using mixed methods. It uncovers AI-driven practices and implications for future of work, talent mobility and industrial policy.

This project uses nanotechnology to develop a highly efficient, eco-friendly method for producing carbon aerogels from agricultural waste for water purification from industrial wastewater. The proposed green synthesis is to ensure the carbon-based aerogels are environmentally friendly.

Revolutionizing extraction and processing of hard rock Li resources with environmental sustainability using eco-efficient reagents to reduce water usage, waste and greenhouse gas, we will deliver alternative supplies to Li battery production for electric vehicles and renewable energy storage.