جست‌وجوی استاد و پژوهشگر

Prasanga Samarasingheمشاهده پروفایل

دانشیار

• Audio and Acoustic Signal Processing
• Spatial Audio
• Microphone and Loudspeaker Array Processing
• +۷ مورد دیگر

Dr. Prasanga Samarasinghe is an Associate Professor at the Australian National University (ANU) within the College of Systems & Society. Her research focuses on spatial audio, acoustic signal processing, and drone audition. She holds a B.E. in Electrical and Electronic Engineering from the University of Peradeniya (2010) and a PhD in Signal Processing from ANU (2015). Key professional achievements include a 2022 Fulbright Fellowship at Yale University and the 2023 ARC DECRA Fellowship. She has secured significant funding through ARC Linkage, Discovery grants, and industry partnerships with Sony, Dolby, and META. Her industry experience includes roles at Dolby Laboratories and collaborations with defense-related entities like the Australian Signals Directorate. Research Groups: Joint supervisor of ANU Audio and Acoustic Signal Processing Group Professional Roles: Member of IEEE Signal Processing Society's Audio & Acoustic Signal Processing TC (2021–2023), former Chair of IEEE ACT Section's COMMS/SP Chapter (2018–2020) Her work bridges theoretical advancements in spatial audio with practical applications in noise cancellation, drone audition, and virtual acoustics. She actively supervises PhD and Honours students in these areas. Awards: Fulbright Fellowship (2022), ARC DECRA (2023) Industry Collaborations: Sony-Japan, Dolby (Sydney/USA), META (USA), Australian Defence Portfolio

• Acoustics and noise control
• Dynamics, vibration and vibration control
• Signal processing
• +۳ مورد دیگر

Dr. Sipei Zhao is a Senior Lecturer at the School of Mechanical and Mechatronic Engineering at the University of Technology Sydney (UTS), where he has been employed since January 2021. Prior to this, he worked as a Post-doctoral Research Fellow at the Centre for Audio, Acoustics and Vibration of UTS from July 2018 to December 2020. His educational background includes a PhD in Electrical Engineering from RMIT University (2018), a Master's degree in Acoustics from Nanjing University (2015), and a Bachelor's degree in Electronics Engineering from Nanjing University (2012). Dr. Zhao's research focuses on acoustics and noise control, dynamics and vibration control, and signal processing. His work spans theoretical development and practical applications in active noise control, architectural acoustics, and machine learning for acoustic analysis. He has made significant contributions to distributed acoustic systems, neural network applications in sound field reconstruction, and innovative approaches to sound zone control. His recent publications demonstrate a strong trajectory in distributed acoustic systems, neural network applications in acoustics, and innovative approaches to sound field control and reproduction. His work combines theoretical rigor with practical implementations, often resulting in significant reductions in computational complexity while maintaining or improving performance. Best Student Paper at the 22nd International Congress on Sound and Vibration (ICSV22) in 2015 Best Paper Prize at the 21st International Conference of the Association for Computer-Aided Architectural Design Research in Asia (CAADRA2016) in 2016 Best Paper Award at the 23rd International Congress on Acoustics (ICA2019) in 2019 Young Professionals Grant from the International Institute of Noise Control Engineering (I-INCE) Ford Publication Commendation Prize from RMIT University in 2017 ARC Early Career Industry Fellowship in 2024 Dr. Zhao has successfully secured multiple research grants and contracts from organizations including the Australian Research Council, NSW Environment Protection Authority, and industry partners like Noizend Pty Ltd. His research has practical applications in industrial settings, transportation, and building acoustics. He serves as a peer reviewer for prestigious journals including the Journal of Sound and Vibration and IEEE/ACM Transactions on Audio, Speech, and Language Processing.