The Lab thrives to be a leading research institute in applicable technologies and their applications in economic development and social well-being. Developing human capabilities in sustainable computation through graduate research and fellowship programmes is also an essential objective in the following areas, though not limited to:
(1) Sustainability
(1.1) Plant Improvement and Sustainable Production
This work aims to contribute to sustainable food production in a changing climate in marginal environments. The overall goal is to increase the adaptive capacities, livelihoods, and food security of smallholder farmers and rural communities.
Areas of applied research:
Crop diversification using underutilized, stress-tolerant crops for food, feed and biofuel and different types of saline water, including reject brine and seawater;
• Plant breeding, genetics and genomics;
• Seed production, harvesting and post-harvest technologies;
• Agricultural value chains;
• Controlled-environment agriculture, including vertical farming.
(1.2) Climate change adaptation and modeling
This work aims to help our stakeholders, from smallholder farmers to agri-businesses to governments, better adjust to a changing climate. The overall goal is to enhance the livelihoods, adaptive capacities, and incomes of agricultural communities most vulnerable to the impacts of climate change.
Areas of applied research:
• Advanced climate modeling using big data and machine learning;
• Modeling and remote-sensing tools for climate change impact assessment;
• Future analysis and planning using water and crop modeling;
• Integrated drought management – monitoring/early warning systems, vulnerability and impact assessment, mitigation and response.
(1.3) Natural Resources Management
This work aims to contribute to more efficient and sustainable management of natural resources in marginal environments through best-bet practices, crops, and technologies. The overall goal is to increase agricultural productivity and thus improve food, nutrition and water security, and create jobs and livelihoods for communities living in these environments.
Water
We promote sustainable management of fresh water and efficient use of alternative water resources for agriculture, such as treated wastewater, drainage water, produced water, and different types of saline water, including rejected brine and seawater.
Areas of applied research:
• Irrigation efficiency and agricultural water productivity through modeling, water accounting, and other tools;
• Air-to-water technology;
• Precision agriculture;
• Remote sensing and GIS applications;
• Surface and groundwater modeling;
• Sustainable irrigation systems, including small-scale irrigation solutions, tailored to local environments.
Land
We work on reducing land degradation and restoring degraded lands. This includes the assessment of existing cropping systems in marginal environments and the development of profitable and sustainable crop production systems for degraded lands.
Areas of applied research:
• Integrated soil, water, and crop management practices;
• Soil improvement through organic and inorganic amendments;
• Land use, agro-climatic zoning, and reclamation and use of marginal lands.
(2) Ecology
(2.1) Circular Ecology and Resource Efficiency
This work aims to promote sustainable ecosystems by adopting circular economy models that enhance resource efficiency and biodiversity conservation. The overall goal is to protect and restore ecosystems while improving livelihoods and environmental resilience.
Areas of applied research:
• Circular models for natural resource management (reuse, recycling, and regeneration of resources);
• Ecosystem restoration through green infrastructure;
• Nature-based solutions for climate resilience;
• Biodiversity monitoring and conservation using advanced technologies (e.g., drones, sensors);
• Sustainable management of natural ecosystems and ecosystem services.
(2.2) Ecological Data Science and Artificial Intelligence
This work aims to support decision-making in environmental management by applying artificial intelligence, data science, and big data analytics to monitor and predict ecological changes. The overall goal is to enable proactive responses to environmental challenges and preserve ecological balance.
Areas of applied research:
• AI-driven predictive models for ecosystem health;
• Real-time monitoring of biodiversity using machine learning algorithms;
• Remote sensing technologies for forest and marine ecosystems;
• Predictive analytics for habitat loss and species extinction risk assessment;
• Advanced geospatial data integration for ecological mapping.
(3) Technology
(3.1) Resilient Technologies for Sustainable Development
This work focuses on creating resilient digital technologies that drive sustainable development across sectors. The goal is to ensure that technology contributes to environmental sustainability and societal well-being in the face of global challenges.
Areas of applied research:
• Internet of Things (IoT) solutions for resource management;
• Renewable energy integration in urban and rural settings;
• Low-energy and sustainable computing systems;
• Smart grid and clean energy technology innovation;
• Tech solutions for disaster risk management and climate resilience.
3.2 Smart Systems and Green Tech
This work addresses the integration of smart systems with green technologies to optimize energy efficiency, reduce carbon footprints, and promote sustainability. The overall goal is to create smarter cities and industries that prioritize environmental sustainability.
Areas of applied research:
• Smart buildings and infrastructure for energy conservation;
• Green technology for sustainable urban planning;
• Automation and AI in waste management and recycling;
• Blockchain and IoT for sustainable supply chains;
• Smart sensors and AI for water and energy efficiency.
(4) Healthcare
(4.1) Sustainable Healthcare Systems
This work aims to design environmentally sustainable healthcare systems by focusing on efficient resource use, waste reduction, and innovative healthcare delivery models. The goal is to minimize healthcare’s environmental impact without compromising the quality of care.
Areas of applied research:
• Circular economy approaches for healthcare waste management;
• Green hospital designs and eco-friendly medical technologies;
• Digital health platforms to reduce healthcare resource consumption;
• AI and IoT-enabled tools for remote healthcare and telemedicine;
• Sustainable healthcare practices in public health infrastructure.
(4.2) AI in Preventive Healthcare and Environmental Wellness
This work aims to leverage artificial intelligence to integrate environmental factors into preventive healthcare strategies. The overall goal is to enhance long-term health outcomes by addressing both environmental wellness and personal health.
Areas of applied research:
• AI tools for environmental health monitoring and predictive analytics;
• Preventive healthcare applications using environmental data;
• Smart health devices for continuous monitoring of environmental exposures;
• Machine learning for disease outbreak predictions linked to environmental changes;
• Health risk assessments based on environmental and lifestyle factors.