### Contributions by role

### Contributions by subject area

# Catherine F Higham

## Summary

Dr. Catherine Higham works at the interface between mathematics, deep learning and experimental science. Her first degree was in mathematics and her PhD involved mathematical modelling and statistical inference applied to somatic genetic mutations arising in myotonic dystrophy and Huntington's disease. Subsequent areas of research include Bayesian inference in nonlinear ODEs and the circadian clock. Currently, she is developing and applying deep learning techniques to inverse problems arising in novel quantum imaging technologies such as the single pixel camera and lidar. She also has an interest in quantum machine learning and framing problems for quantum annealing.

Computational Biology Data Mining & Machine Learning Quantum Computing