Shinji Watanabe is an Associate Professor at Carnegie Mellon University, Pittsburgh, PA. He received his B.S., M.S., and Ph.D. (Dr. Eng.) degrees from Waseda University, Tokyo, Japan. He was a research scientist at NTT Communication Science Laboratories, Kyoto, Japan, from 2001 to 2011, a visiting scholar at Georgia Institute of Technology, Atlanta, GA, in 2009, and a senior principal research scientist at Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA USA from 2012 to 2017. Before Carnegie Mellon University, he was an associate research professor at Johns Hopkins University, Baltimore, MD, USA, from 2017 to 2020. His research interests include automatic speech recognition, speech enhancement, spoken language understanding, and machine learning for speech and language processing. He has published over 500 papers in peer-reviewed journals and conferences and received several awards, including the best paper award from ISCA Interspeech in 2024. He is a Senior Area Editor of the IEEE Transactions on Audio Speech and Language Processing. He was/has been a member of several technical committees, including the APSIPA Speech, Language, and Audio Technical Committee (SLA), IEEE Signal Processing Society Speech and Language Technical Committee (SLTC), and Machine Learning for Signal Processing Technical Committee (MLSP). He is an IEEE and ISCA Fellow.

Hung-yi Lee is a professor of the Department of Electrical Engineering at National Taiwan University (NTU), with a joint appointment at the Department of Computer Science & Information Engineering of the university. His recent research focuses on developing technology that can reduce the requirement of annotated data for speech processing (including voice conversion and speech recognition) and natural language processing (including abstractive summarization and question answering). He won Salesforce Research Deep Learning Grant in 2019, AWS ML Research Award in 2020, Outstanding Young Engineer Award from The Chinese Institute of Electrical Engineering in 2018, Young Scholar Innovation Award from Foundation for the Advancement of Outstanding Scholarship in 2019, Ta-You Wu Memorial Award from Ministry of Science and Technology of Taiwan in 2019, and The 59th Ten Outstanding Young Person Award in Science and Technology Research & Development of Taiwan. He owns a YouTube channel teaching deep learning technology in Marian, which has more than 300,000 subscribers.

Ming Li received his Ph.D. in Electrical Engineering from University of Southern California in 2013. He is currently a Professor of Electronical and Computer Engineering at Division of Natural and Applied Science and Principal Research Scientist at Digital Innovation Research Center at Duke Kunshan University. He is also an Adjunct Professor at School of Computer Science of Wuhan University. His research interests are in the areas of audio, speech and language processing as well as multimodal behavior signal analysis and interpretation. He has published more than 200 papers and served as the member of IEEE speech and language technical committee, APSIPA speech and language processing technical committee. He was an area chair at Interspeech 2016, Interspeech 2018, Interspeech 2020, SLT2022, Interspeech 2024, Interspeech 2025, ASRU 2025. He is the technical program co-chair at Odyssey 2022 and ASRU 2023. He is an editorial member of IEEE Transactions on Audio, Speech and Language Processing, Computer Speech and Language and APSIPA Transactions on Signal and Information Processing. Works co-authored with his colleagues have won first prize awards at Interspeech Computational Paralinguistic Challenges 2011, 2012 and 2019, ASRU 2019 MGB-5 ADI Challenge, Interspeech 2020 and 2021 Fearless Steps Challenges, VoxSRC 2021, 2022 and 2023 Challenges, ICASSP 2022 M2MeT Challenge, IJCAI 2023 ADD challenge, ICME 2024 ChatCLR challenge and Interspeech 2024 AVSE challenge. As a co-author, he has won the best paper award in DCOSS2009 and ISCSLP2014 as well as the best paper shortlist in Interspeech 2024. He received the IBM faculty award in 2016, the ISCA Computer Speech and Language 5-years best journal paper award in 2018 and the youth achievement award of outstanding scientific research achievements of Chinese higher education in 2020. He is a senior member of IEEE.

Shuai Wang is a tenure-track Associate Professor at Nanjing University and an adjunct faculty member at the Chinese University of Hong Kong, Shenzhen (CUHK-SZ). He received his Ph.D. from Shanghai Jiao Tong University in 2020 and his B.Sc. from Northwestern Polytechnical University in 2014. Dr. Wang has published over 60 papers on speaker modeling and has received several honors, including the IEEE Ramaswamy Grant at ICASSP 2018, and first place in both VoxSRC 2019 and DIHARD 2019. He is the initiator of the open-source projects WeSpeaker and WeSep, which are widely adopted by both academia and industry.

Visionary leader and operational architect at Nexdata, Pan leverages over a decade of AI data expertise to lead elite teams in delivering end-to-end solutions for LLM, GenAI, and traditional AI models. She has successfully executed 1000+ projects by integrating global-scale multi-sensor data collection, AI-powered annotation, and a unified platform that streamlines the entire training data pipeline.