Professor Francis Morgan Boland

My career as an engineer has been predominantly based within the academic sector. My teaching experience extends from electrical engineering principles to junior students and teaching advanced topics in signal processing and systems theory to senior undergraduate and postgraduate students. My research work is in the mathematics and algorithms of adaptive systems and digital signal processing for audio and acoustics. A key objective of my research is to create, for a listener, the immersive experience of spatially accurate audio cues that are stable with voluntary or random head and other movements by the user. My research group has achieved novel theoretical and experimental results that include a demonstration that for angle dependent head related impulse (HRIR) response functions, associated with binaural hearing, there exist angle independent sub-systems. We have recently reported a theoretical underpinning of this work by showing its equivalence to the approximate factorisation of sets of polynomials with sets of polynomials with random coefficients.[Details are included in our associated publications] 1 We proposed and verified that within the large data sets of angle dependent head related impulse (HRIR) response functions, associated with binaural hearing, there exist angle independent sub-systems. We have recently reported a theoretical underpinning of this work by showing its equivalence to the approximate factorisation of sets of polynomials with random coefficients and we have also shown that the method can be used to equalise headphone transfer functions. 2 We have implemented an Ambisonic soundfield using a virtual uniform circular array with a rotatable soundfield using headtracking to maintain a stable orientation. 3 We have developed algorithms for detecting and interpolating the reflections in Room Impulse Response functions and a novel method for measuring the standard acoustic decay response of a room. In recent years, the application focus of my research has been the delivery of accurate immersive audio environments over headphones. Results of this research have had a significant impact in audio for Virtual Reality (VR) environments. An outcome of the research is Thrive which is an audio signal processing algorithm and software system for VR. In 2015 the Thrive IP was licensed by Google and provided a basis for the open source environment Resonance Audio for developing rich immersive audio. My current research activities, supported by Science Foundation Ireland, includes Machine Learning for audio source localisation and calibration techniques for digital sound projectors in rooms with uncertain acoustics.

  Applied probability   Communication engineering, technology   Communications engineering   Computer vision and robotics   Control Engineering   Engineering & Physical Acoustics   Foundations and methods   Human computer interactions   Imaging and Computer Vision   Modelling, modelling tools, 3D modelling   Multimedia   Performance and technology   Signal processing   Signal, Video & Audio Processing   Sound Engineering   Speech processing/technology   Systems control, Modelling, Neural networks   Systems Engineering   Systems/Control   Telecommunication Engineering   Telecommunications   Vibration and Accoustic Engineering

Research interests in digital signal processing and technology for audio, acoustics. Systems theory for modelling and design in complex and adaptive systems.