Research Focus - C-FAIR
Centre for Artificial Intelligence Research (C-FAIR)
Research Focus
C-FAIR’s research agenda is structured around three integrated pillars, spanning the full spectrum from foundational theory to responsible real-world deployment:
Foundational AI Research (Building Next Gen AI models)
Applied AI Research (Solving interdisciplinary research problems)
Social & Responsible AI Research (Ethics, policy & Societal relevance)
Following are the sub-topics of research under each branch:
• Core machine learning and deep learning theory
• Optimization, representation learning, and foundation models
• Large Language Models (architectures, training, evaluation)
• Quantum machine learning algorithms
• Hybrid quantum classical AI systems
• Post-quantum and quantum-safe AI research
• Neuromorphic computing and brain-inspired architectures
• Edge AI, embedded intelligence, and IoT integration
• AI accelerators and hardware–software co-design
• New Learning theories, Training algorithms and Scaling models
• Multimodal and Agentic reasoning
• Human-like robots, cognitive embodiment, social robots
• Robotics, autonomous vehicles, drones
• Cyber-physical systems and smart manufacturing
• Digital twins and predictive maintenance
• Medical imaging and clinical decision support
• AI for genomics, proteomics, and drug discovery
• Personalized and preventive healthcare systems
• Precision agriculture and smart irrigation
• Climate modeling and environmental intelligence
• AI for energy optimization and sustainability
• Explainable, trustworthy, and transparent AI
• Fairness, bias mitigation, and AI governance
• Human–AI interaction and policy frameworks
• AI productization and technology transfer
• Startup incubation and innovation ecosystems
• Responsible deployment and commercialization of AI