I’m a Ph.D. candidate in the Department of Computer Science and Engineering at The Ohio State University, where I’m fortunately advised by Prof. DeLiang Wang in the Perception and Neurodynamics Laboratory (PNL). I hold an M.S. in Electrical and Computer Engineering from Georgia Institute of Technology and a B.E. in Information Engineering from Southeast University.

My research interests are in automatic speech recognition, speech separation, and self-supervised learning.

Feel free to contact me via email: yang.5662@osu.edu or yfyang@ieee.org.

Education

Ph.D. in Computer Science and Engineering, The Ohio State University, USA, 2026 (expected)
- Advisor: Prof. DeLiang Wang
M.S. in Electrical and Computer Engineering, Georgia Institute of Technology, USA, 2020
- Advisor: Prof. David V Anderson
B.E. in Information Engineering, Southeast University, China, 2018
- Advisor: Prof. Chuan Zhang

Industry Experience

Research Scientist Intern, Meta (May - August 2025)
- Reality Labs voice AI assistant team
- Focus: Multichannel ASR for smart glasses
- Mentor: Yiteng Huang and Yong Xu
Research Scientist Intern, Meta (May - August 2024)
- GenAI Llama speech team
- Focus: Multichannel self-supervised learning for smart glasses
- Mentor: Desh Raj
Research Intern, Mitsubishi Electric Research Laboratories (May - August 2023)
- Speech and Audio group
- Focus: Source separation and self-supervised learning
- Mentor: François Germain
Research Intern, Microsoft Research Asia (May - August 2019)
- Speech group
- Focus: Overlapped speech detection
- Mentor: Frank K.P. Soong

Publications

Y. Yang, A. Pandey, and D.L. Wang, “Towards decoupling frontend enhancement and backend recognition in monaural robust ASR,” Computer Speech & Language, 101821, 2025. [pdf]
Y. Yang, H. Taherian, V.A. Kalkhorani, and D.L. Wang, “Elevating robust multi-talker ASR by decoupling speaker separation and speech recognition,” arXiv:2503.17886, 2025. [pdf]
Y. Yang, H. Taherian, V.A. Kalkhorani, and D.L. Wang, “Elevating robust ASR by decoupling multi-channel speaker separation and speech recognition,” in Proc. IEEE ICASSP, 2025, 5 pages. [pdf]
Y. Yang, D. Raj, J. Lin, N. Moritz, J. Jia, G. Keren, E. Lakomkin, Y. Huang, J. Donley, J. Mahadeokar, and O. Kalinli, “M-BEST-RQ: A multi-channel speech foundation model for smart glasses,” in Proc. IEEE ICASSP, 2025, 5 pages. [pdf]
Y. Yang, A. Pandey, and D.L. Wang, “Time-domain speech enhancement for robust automatic speech recognition,” in Proc. Interspeech, 2023, pp.4913-4917. [pdf]
Y. Yang, P. Wang, and D.L. Wang, “A Conformer based acoustic model for robust automatic speech recognition,” arXiv:2203.00725, 2022. [pdf]
D. Caulley, Y. Yang, and D. Anderson, “EACELEB: an east Asian language speaking celebrity dataset for speaker recognition,” arXiv:2203.05333, 2022. [pdf]
C. Zhang^*, Y. Yang^*, S. Zhang, Z. Zhang, and X. You, “Residual-based detections and unified architecture for massive MIMO uplink,” Journal of Signal Processing Systems, vol. 91, no. 9, pp. 1039–1052, 2019. [pdf]
Y. Yang, W. Zhang, J. Jin, Z. Zhang, X. You, and C. Zhang, “Efficient compressed Landweber detector for massive MIMO,” in Proc. IEEE SiPS, 2018, pp. 65–70. [pdf]
Y. Yang, Y. Xue, X. You, and C. Zhang, “An efficient conjugate residual detector for massive MIMO systems,” in Proc. IEEE SiPS, 2017, pp. 1–6. [pdf]