LecturerAnurag is the head of the Acoustics lab in the Engineering Department at University of Cambridge. He is a University Lecturer at Univeristy of Cambridge, a Fellow at Emmanuel College and the managing director of Cambridge Aeroacoustics Limited. His research interests are in the field of acoustics and aerodynamics of aerospace, domestic appliances and biomedical appications. His collaborators include Rolls-Royce, General Electric, Boeing, Mitsubishi Heavy Industries, JCB, Dyson, Addenbrookes and Papworth Hospitals.
Alastair is currently working on understanding how wheezing sounds in the lung are produced through experimentation and modelling. The aim is to produce as simple a relationship as possible between the wheezing frequency and the tube material properties and geometry. This could then be used by clinicians to learn about changes in stiffness of lung tissue and the position of blockages and stenoses. He is also helping in the development of a microphone array that will be used for sound localisation in the chest. In his previous work with the group he developed a new kind of transformation to allow better understanding of how sound propagates in the presence of background flow, using analogies between aeroacoustics and relativity.
Ed is working on understanding and classifying heart sounds. He is producing physical models to understand the causes of the heart murmurs associated with aortic stenosis and mitral regurgitation. He is also using machine learning techniques to try and classify heart sounds as either normal or abnormal.
Max is working on understanding sound propagation through the human chest. The aim is to develop a method of generating acoustic maps of the chest that can help clinicians diagnose certain diseases. Max is working with Alastair on the development of a microphone array that will be used for sound localisation in the chest. In his previous work with the group he has studied the aeroacoustics of free reeds.
Oscar is developing noise prediction methods for turbomachinery operating at low Reynolds number. Noise reduction of air-moving devices such as axial compressors is becoming increasingly important for the industrial engineer, as stringent regulations are placing acoustic design on near equal terms with aerodynamic efficiency. Consequently, noise can no longer be accepted as an undesirable by-product, but rather must be accounted for at an earlier stage, ideally in tandem with aerodynamic design. Oscar is working to implement low order models that can be used to assess noise levels early in the design process. This work involves using analytical models together with computationally demanding fluid dynamics simulations to devise quick but accurate methods for noise production. Oscar is also interested in utilising machine learning algorithms in optimisation for low noise design.
Andrew is developing machine learning techniques to diagnose cardiovascular disease from heart sounds. He is working with Ed to develop an intelligent stethoscope, which is capable of reliable screening of valvular heart disease. The device will help clinicians detect heart problems earlier and more accurately, to improve patient prognoses and reduce unnecessary referrals to cardiologists.