The research pathway integrates clean energy and water solutions, indigenous technology development, optimized energy extraction techniques using machine learning, waste water treatment for resource recovery, smart materials, and AI-based design for smart mobility.
Addressing inaccessible or unaffordable healthcare by leveraging multisensor fusion, low-power IoT devices, and digital twin technology.
Developing a smart grid mobility system with a security focus, promoting green supply chain management for circular economy principles, employing IoT and AI-based system design to enhance sustainability.
Manage industrial waste through recycling and segregation with system level modeling, implementing smart waste bins with AI models, and promoting sustainable materials for a circular economy.
Integrate food security efforts with IoT-driven smart organic urban farming, utilizing AI in agriculture, and optimizing manure production through integrated smart waste management practices.
Enhance food security through IoT-enabled smart organic urban farming, leveraging AI for agricultural optimization, and producing manure via integrated smart waste management practices.
The research pathway addresses CO emissions through the estimation of COx, CO sequestration methods including underground storage via adsorption and chemical looping, with a focus on sustainable agriculture practices.
Reducing GHG emissions through solar-powered electric cars, leveraging advanced battery tech, integrating IoT for smart mobility, and applying sustainable solutions across various domains.
Addressing the lack of sustainable behavior by focusing on capacity building and integrating traditional knowledge, leveraging IoT, apps, and general AI technologies, incorporating design thinking for sustainable behaviors, and embracing sacred ecology principles.
Exploring materials science through Indigenous Knowledge Systems (IKS) alongside indigenous technology development, utilizing traditional resources like food, cow dung, and cow dung ash, and innovating new materials for energy and environmental research.
Implementing smart structures and smart manufacturing techniques with AI/ML for predictive monitoring and safety analysis of structures, in alignment with the Industry 5.0 paradigm.
Protein folding using the Quantum Lyapunov Spectrum alongside the PINN method and Out of Time Order Correlation for drug delivery development with medical applications.
Fabricating quantum devices utilizing solution or deposition methods, advanced lithography, and data processing techniques, incorporating 2D quantum materials for the development of healthcare devices.
Coherent quantum transport, involving quantum computing and topologically protected states, is being investigated alongside communication strategies utilizing quantum dots and topological insulators to establish a high coherence quantum channel.
Resource provisioning is being optimized through the integration of quantum algorithms, including Quantum Approximate Optimization Algorithms, with the utilization of Quantum Annealers, in conjunction with classical, quantum, and hybrid computing paradigms.
Creating self-reliant smart communities through the synthesis of global policy pluralism, mental models and quantum mind theories, and quantum simulation techniques.
Developing lightweight quantum protocols and quantum physical unclonable functions (PUFs) for quantum-safe Internet of Things (IoT) systems.
Enhancing weather forecasting through climate change modeling, leveraging big data analytics or quantum algorithms, integrating quantum neural networks with IoT technologies.
Investigating the scaling of materials and correlation methods for developing super-responsive devices, employing Quantum Neural Networks (QNNs) or Quantum Machine Learning (QML) techniques.
Exploring the scaling and biocompatibility of nanosensors in conjunction with biomaterials and quantum sensors, employing density functional theory (DFT) for biomaterial synthesis, and integrating brain-inspired computing for advanced applications.