Driving Sustainable Change: UNSW Researchers Tackling Global Challenges
Published on the 12 March 2026 by UNSW Business School EDI Team
Each year, UNSW Business School proudly awards five Sustainable Development Goals (SDGs) Research Grants, empowering our HDR candidates to tackle pressing global challenges.
These grants support innovative research that drives progress toward the UN SDGs (2030 – 2050) through transformative industry or government interventions at local, national, or international levels.
Two of the grants are funded by the UNSW Business School’s SDG Committee, while the remaining three are generously supported by the UNSW Global Water Institute.
The funding is dedicated to advancing research projects that inspire real-world impact and sustainable solutions. For the 2025-2026 cycle, a panel of expert judges selected five exceptional recipients: Marian Cooray, Shuge Li, Danyue Liang, Shawn Yang and Trisha Hassan.
Their visionary research proposals and compelling presentations distinguished themselves through their rigor, relevance, and transformative potential. Each project exemplifies a commitment to driving meaningful change across industries and communities.
Congratulations to this year’s awardees — bold innovators charting the course toward a more sustainable and equitable future!
To learn more about these expectational research projects, UNSW Business School spoke to each awardee about their research and how this will enable positive Societal impact.
Name: Shawn Yang
School affiliation: School of Risk and Actuarial Studies
Thesis title: Bayesian Learning of Regional Economic Impacts of Climate Change
What is your thesis about (elevator pitch)?
The global economy is under threat from climate change, with projections indicating potential GDP losses of 11–29% over the next few decades. Yet both climate change itself and its economic damages are subject to deep uncertainty, making it difficult to provide reliable estimates for decision-making. My thesis develops a Bayesian learning framework, a statistical approach to updating beliefs as new data arrives, to evaluate these economic impacts, pooling information across regions to learn faster and more accurately than treating each region in isolation.
What contemporary issue does your thesis address?
Since regions face different exposures and evolving vulnerabilities, uncertainties in climate damage estimates vary significantly across space and time. Most existing models overlook this, hiding large cross-regional differences behind a single global figure. My thesis disaggregates GDP losses to capture regional heterogeneity and incorporate cross-regional correlations, using the FUND dataset and climate scenarios adopted by the IPCC as the empirical foundation.
The uncertainties around economic impacts of climate change on different regions complicate decision-making for climate policy. By learning economic impacts of climate change across multiple regions, my research aims to improve the timing and effectiveness of adaptation and mitigation policies, contributing directly to SDG 10 (Reduced Inequalities) and SDG 13 (Climate Action).
What has been the significance of receiving the UNSW SDG Grant on your research?
The grant supports my research in two important ways. First, it enables the acquisition of more detailed regional climate damage data, which strengthens the empirical foundation of the work. Second, it supports my participation in the International Congress on Insurance: Mathematics and Economics (IME), where I will present my research and engage with leading experts in climate risk and actuarial studies.
Name: Danyue Liang
School affiliation: School of Economics
Thesis title: College Application Behaviour Under Constrained Choice
What is your thesis about (elevator pitch)?
My thesis examines how students make college application decisions when the number of choices they can submit is limited. Using a natural experiment from New South Wales, Australia—where the maximum number of application preferences was reduced from nine to five—I study how tighter constraints affect students’ strategic behaviour and enrolment outcomes.
I find that when choices are restricted, students tend to behave more conservatively, applying to less selective programs than they otherwise would. This shift is particularly pronounced among high-achieving students and those from more advantaged backgrounds. Ultimately, these behavioural responses can influence both individual outcomes and the broader allocation of opportunities in higher education.
Why is this relevant today?:
My research addresses the broader issue of educational inequality and access to opportunity. While much attention is paid to how admissions systems are designed, less focus has been placed on how students actually respond to institutional constraints within those systems and governments worldwide are striving to design education systems that are both efficient and equitable.
As competition for university places intensifies and policymakers experiment with reforms to application systems, it is crucial to understand not only the theoretical properties of these mechanisms but also how real students behave under constraints. My findings show that limiting choice can induce more conservative decision-making and may lower enrolment outcomes for some students.
At the same time, constraints may have unintended equalizing effects by disproportionately affecting more advantaged applicants who tend to apply more aggressively. In an era of increasing concern about social mobility, inequality, and access to elite institutions, these insights have direct policy implications.
What has been the significance of receiving the UNSW SDG Grant on your research?:
The grant has supported data access and empirical analysis. It has enabled me to work with detailed administrative data, conduct more rigorous econometric testing, and explore heterogeneous effects across different student groups.
Name: Shuge Li
School affiliation: School of Marketing
Thesis title: The Impact of Dual-Goal EV Tax Credits and Consumer Demand
What is your thesis about (elevator pitch)?
My thesis examines how a redesigned clean-vehicle tax credit is changing the electric vehicle (EV) market. Unlike earlier consumer incentives, these credits pursue two goals at once: encouraging EV adoption while also strengthening domestic manufacturing and supply chains.
Using observational data and causal inference methods, I study whether the policy increases overall EV adoption, how it shifts demand across vehicle segments, and what this implies for firms and policymakers designing climate policies with multiple objectives.
What contemporary issue does your thesis address?
Governments around the world are accelerating decarbonisation, and transport is a major part of that challenge. A key question is how to design incentives that meaningfully boost EV adoption while also supporting resilient, localised supply chains—especially as geopolitical uncertainty and supply disruptions have become more salient. My research speaks directly to how “green industrial policy” works in practice when environmental goals and industrial goals are bundled together.
EV incentives are also increasingly conditional on where vehicles and batteries are made, not just whether they are electric. These rules can create different impacts across firms, vehicle models, and consumers—potentially accelerating adoption for some vehicles while discouraging others. This is timely because these programs are still being refined, and automakers are simultaneously making strategic decisions about pricing, sourcing, and where to invest. Understanding how demand responds helps inform better policy design and more realistic industry planning.
What has been the significance of receiving the UNSW SDG Grant on your research?:
The UNSW SDG Grant has strengthened both the scope and the practical relevance of my thesis. It supports the data and research capacity needed to evaluate market-wide policy impacts, and it helps connect the work more directly to SDG priorities—particularly climate action and sustainable industry.
One takeaway from this research is that policy details matter. When incentives are conditional, they can change not only whether people buy EVs, but which EVs they buy—and that can reshape market dynamics and supply-chain investment. Through this research, my goal is to offer empirical evidence that helps decision-makers design incentives that reduce emissions while remaining workable for consumers and firms.