Wenwu Wang is a Professor of Signal Processing and Machine Learning at the University of Surrey, UK, where he serves as Co-Director of the Machine Audition Lab within the Centre for Vision, Speech and Signal Processing. He is also the Associate Head (External Engagement) of the School of Computer Science and Electronic Engineering and an AI Fellow at the Surrey Institute for People-Centred Artificial Intelligence. His research interests span signal processing, machine learning, artificial intelligence, perceptual modelling, machine audition, multimodal fusion and learning, and statistical anomaly detection. He has authored or co-authored over 400 publications in these fields including two books: Machine Audition: Principles, Algorithms and Systems (IGI Global, 2010) and Blind Source Separation: Advances in Theory Algorithms and Applications (Springer, 2014). He has played a leading role (as PI or Co-I) in more than 40 research projects supported by UKRI, EPSRC, the EU, Dstl, MoD, DoD, Home Office, Royal Academy of Engineering, and major industrial partners including BBC, NPL, Samsung, Tencent, Huawei, Saab, B&O, Atlas, and Kaon, with a total grant portfolio exceeding £30 million.

Prof. Wang’s work has received numerous award recognitions, including the 2022 IEEE Signal Processing Society Young Author Best Paper Award, ICAUS 2021 Best Paper Award, DCASE Judge’s Awards (2020, 2023, 2024), DCASE Reproducible System Awards (2019, 2020), LVA/ICA 2018 Best Student Paper Award, FSDM 2016 Best Oral Presentation, and Dstl Challenge 2012 Best Solution Award.

He currently serves as Senior Area Editor (2025–2027) for IEEE Open Journal of Signal Processing, Associate Editor (2024–2026) for IEEE Transactions on Multimedia, Associate Editor for Scientific Reports (Nature, since 2022), Specialty Editor-in-Chief for Frontiers in Signal Processing (since 2021), and Associate Editor (since 2019) for EURASIP Journal on Audio Speech and Music Processing. He was previously Senior Area Editor (2019–2023) and Associate Editor (2014–2018) for IEEE Transactions on Signal Processing, and Associate Editor (2020–2025) for IEEE/ACM Transactions on Audio, Speech and Language Processing. He has also served as Guest Editor (2023–2024) for IEEE Transactions on Circuits and Systems for Video Technology, focusing on AI-generated multimedia content.

Prof. Wang has held numerous leadership roles, including serving as a Board Member (2023–2024) of the IEEE Signal Processing Society (SPS)’s Technical Directions Board and the elected Chair (2023–2024) of the IEEE SPS Machine Learning for Signal Processing Technical Committee. He is the elected Chair (2025–2027) of the EURASIP Technical Area Committee on Acoustic, Speech, and Music Signal Processing, an elected member of the IEEE SPS Signal Processing Theory and Methods Technical Committee (2021–2026), and a longstanding member (since 2019) of the International Steering Committee for Latent Variable Analysis and Signal Separation.

He has served on organizing committees for major conferences such as IEEE ICASSP (2024, 2019), MLSP (2024, 2013), INTERSPEECH (2022), and IEEE SSP (2009). He will serve as Technical Program Co-Chair for MLSP 2025 and as a member of the organizing committee for ICASSP 2029.

His international recognition is reflected in more than 20 keynote and plenary talks at major conferences and workshops worldwide. Highlights include his keynote address at the IEEE Spoken Language Technology Workshop (SLT 2024) on “Large Language-Audio Models and Applications”, at the 2024 Codec SUPERB Workshop on “Neural Audio Codecs”, and at the 10th Intelligent Systems Conference (IntelliSys 2024) on “Generative AI for Text to Audio Generation.” He delivered a Perspective Talk at ICASSP 2023 on “Audio-Text Cross Modal Generation”, a survey talk at INTERSPEECH 2023 on “Automated Audio Captioning: Audio-Text Cross Modal Learning”, and a keynote at the 21st UK Conference on Computational Intelligence (UKCI 2022) on “Deep Learning for Automated Audio Captioning.” In addition, he gave plenary talks at the GHOST DAY Applied Machine Learning Conference (AML 2024 & 2022) on “Generative AI for Text to Audio Generation” & “Automated Audio Captioning”, reinforcing his leadership in generative AI and deep learning for audio applications.

Prof. Wang has also delivered influential tutorials, including a well-attended session at ICASSP 2013 on “Sparse Representation and Dictionary Learning”, and a tutorial at the 2025 IEEE Symposium Series on Computational Intelligence (SSCI) on “Language-Audio Cross-Modal Generation.” His commitment to education extends to advanced training events, such as the UDRC Summer School (2014–2017), SpaRTaN-MacSeNet Spring School (2016), and the London Intelligent Sensing Summer School (2017), where he has taught topics ranging from audio source separation to audio-visual tracking.

He was born in Anhui, China. He received the B.Sc. degree in 1997, the M.E. degree in 2000, and the Ph.D. degree in 2002, all with the highest honor, from Harbin Engineering University, China, where he also received the Outstanding Postgraduate Award (2000) and numerous scholarships for academic excellence. He then worked in King's College London (2002–2003), Cardiff University (2004–2005), Tao Group Ltd. (now Antix Labs Ltd.) (2005–2006), and Creative Labs (2006–2007), before joining University of Surrey, UK, in May 2007, where he initially held a prestigious RCUK Academic Fellowship, then promoted to Lecturer in 2009, Senior Lecturer in 2013, Reader in 2015, and Professor in 2019. He was a Visiting Scholar at the Perception and Neurodynamics Laboratory (PNL) and the Center for Cognitive and Brain Sciences, in Ohio State University, USA, in 2008. He has been a Guest Professor at Tianjin Univrsity (2020–2023) and Qingdao University of Science and Technology (2018–).

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