Ph.D. in Computer Science, University of Southern California (1988-1991)

M.S. in Computer Science, Beijing (Peking) University (1983-1986)

B.S. in Computer Science, Beijing University (1979-1983)

DeLiang WANG is a Professor in the School of Data Science, Chinese University of Hong Kong, Shenzhen. From October 1991 to June 2025, he was with the Department of Computer Science and Engineering and the Center for Cognitive and Brain Sciences at The Ohio State University, Columbus, OH, where he was a Professor and University Distinguished Scholar. From October 1998 to September 1999, he was a visiting scholar in the Department of Psychology at Harvard University, Cambridge, MA. From October 2006 to June 2007, he was a visiting scholar at Oticon A/S, Copenhagen, Denmark. From October 2014 to December 2014, he was a visiting scholar at Starkey Hearing Technologies, Eden Prairie, MN. From July 1986 to December 1987, he was an Assistant Investigator with the Institute of Computing Technology, Academia Sinica, Beijing.

DeLiang WANG received the NSF Research Initiation Award in 1992 and the ONR Young Investigator Award in 1996. He received the Ohio State University College of Engineering Lumley Research Award in 1996, 2000, 2005, and 2010. His 2005 paper, "The time dimension for scene analysis", received the 2007 Outstanding Paper Award from the IEEE Computational Intelligence Society. His 2014 paper with Yuxuan Wang and Arun Narayanan, "On training targets for supervised speech separation", received the 2019 Best Paper Award from the IEEE Signal Processing Society. The 2019 paper first authored by Ashutosh Pandey, "A new framework for CNN-based speech enhancement in the time domain", received the 2022 Young Author Best Paper Award (to Pandey) from the IEEE Signal Processing Society. He received the 2008 Helmholtz Award and the 2019 Ada Lovelace Service Award from the International Neural Network Society. In 2025, he received the Neural Networks Pioneer Award from the IEEE Computational Intelligence Society. He was an IEEE Distinguished Lecturer (2010-2012), and is a Fellow of IEEE, ISCA, and AAIA.

He is the Editor-In-Chief of Neural Networks, a premier journal published by Elsevier. In addition, he serves on the advisory board of Cognitive Computation. He also served as President of the International Neural Network Society in 2006, and currently serves on its governing board.

1. Terman D. and Wang D.L. (1995): “Global competition and local cooperation in a network of neural oscillators,” Physica D, vol. 81, pp. 148-176.

2. Wang D.L. (2005): “The time dimension for scene analysis,” IEEE Transactions on Neural Networks, vol. 16, pp. 1401-1426.

3. Wang D.L. and Brown G.J., Eds. (2006): Computational Auditory Scene Analysis: Principles, Algorithms, and Applications. Hoboken NJ: Wiley & IEEE Press.

4. Wang Y. and Wang D.L. (2013): “Towards scaling up classification-based speech separation,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 21, pp. 1381-1390.

5. Wang Y., Narayanan A. and Wang D.L. (2014): “On training targets for supervised speech separation,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 22, pp. 1849-1858.

6. Williamson D.S., Wang Y., and Wang D.L. (2016): “Complex ratio masking for monaural speech separation,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 24, pp. 483-492.

7. Wang D.L. (March 2017): “Deep learning reinvents the hearing aid,” IEEE Spectrum, pp. 32-37 (cover story).

8. Chen J. and Wang D.L. (2018): “Supervised speech separation based on deep learning: An overview,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 26, pp. 1702-1726.

9. Pandey A. and Wang D.L. (2019): “A new framework for CNN-based speech enhancement in the time domain,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 27, pp. 1179-1188.

10. Liu Y. and Wang D.L. (2019): “Divide and conquer: A deep CASA approach to talker-independent monaural speaker separation,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 27, pp. 2092-2102.

11. Wang Z.-Q., Wang P., and Wang D.L. (2020): “Complex spectral mapping for single- and multi-channel speech enhancement and robust ASR,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 28, pp. 1778-1787.

12. Wang Z.-Q. and Wang D.L. (2020): “Deep learning based target cancellation for speech dereverberation,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 28, pp. 941-950.

13. Zhang H. and Wang D.L. (2021): “Deep ANC: A deep learning approach to active noise control,” Neural Networks, vol. 141, pp. 1-10.

14. Tan K., Wang Z.-Q., and Wang D.L. (2022): “Neural spectrospatial filtering,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 30, pp. 605-621.

15. Kalkhorani V.A. and Wang D.L. (2024): “TF-CrossNet: Leveraging global, cross-band, narrow-band, and positional encoding for single- and multi-channel speaker separation,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 32, pp. 4999-5009.

A complete list of publications can be found at https://pnlwang.github.io/