Carl Edward Rasmussen

Professor Carl Edward Rasmussen is affiliated with the University of Cambridge, where he focuses on Machine Learning, Probabilistic Inference, Decision Making, and Reasoning Under Uncertainty. His work bridges theoretical advancements with practical applications in robotics, control systems, and computational biology.

• Academic Affiliation: University of Cambridge
• Academic Role: Professor

His research emphasizes scalable Gaussian process methods, Bayesian system identification, and reinforcement learning. Recent projects include transfer learning for antibacterial discovery, graph neural processes for molecular functions, and efficient variational inference techniques. Key themes in his publications highlight uncertainty quantification, model generalization, and nonparametric approaches.

Notable Scientific Contributions

• Advancements in sparse Gaussian process hyperparameter estimation
• Framework for Bayesian system identification in dynamic systems
• Hybrid models combining transformers and Gaussian processes