Areas of Expertise
      
        
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              C2D3 has the widest reach within the University of Cambridge, in terms of network and academic collaborations in the space of AI & Data Science. We can support and deliver projects within a large academic areas of expertise across all six Schools. Please find below our areas of expertise:
            AI, Machine Learning, and Data Science
      
			
						- AI policy and AI governance
 - Bayesian deep learning
 - Bayesian inference
 - Bayesian optimization
 - Data-efficient machine learning
 - Data management, security, and privacy
 - Data protection, including GDPR
 - Deep generative models
 - Emulation
 - Graph neural networks
 - High-performance computing
 - Image analysis
 - Image compression
 - Image processing and inverse imaging problems
 - Interpretable machine learning
 - Machine learning
 - Machine learning and AI for social data
 - Meta-learning
 - Molecule generation and optimization
 - Natural language processing
 - Neural network compression
 - Public perception
 - Reinforcement learning and causal inference
 - Responsible AI
 - Simulation-based inference
 - Technology, law, and policy
 
             Climate, Energy, and Environment
      
			
						- Climate communication
 - Climate justice
 - Decarbonisation and public health
 - Decarbonisation of buildings and infrastructure—including heat loss from UK buildings, building retrofit strategies, indoor overheating
 - Energy justice
 - Energy modelling
 - Environmental change
 - Environmental policy
 - Environmental science
 - Geospatial science
 - Heatwave mitigation
 - Low carbon technology
 - Negative emissions technology
 - Public perception (listed under AI as well)
 - Remote sensing
 - Satellite/Earth Observation
 - Terrestrial carbon
 
            Engineering, Physics, and Mechanics
      
			
						- Fluid mechanics
 - Geophysics and environmental modelling
 - Industrial modelling
 - Mechanics of granular media
 - Mechanics of porous media
 - Non-Newtonian fluid dynamics
 - Rheology
 
            Applications and Interdisciplinary Fields
      
			
						- Applications of Data Sciences in the area of energy systems and Built Environment, pertaining to model calibration and decision-making under uncertainty
 - Human behaviour modelling