简历

工作经历

• 2023.09 - 至今：高级音频算法工程师, OPPO
  • 手机OPPO Find X8 和 X9 系列MTK平台手持&免提两种模式下的人声突显
  • 手机中端平台ADSP人声凸显小模型，(Reno14,k13系列)
  • 面试官（校招、社招、实习生），新员工导师
• 2023.08 - 2026.03：博士后, 中国科学院声学研究所
  • 导师：杨飞然
  • 方向：智能语音算法的端侧部署
• 2019.08 - 2019.12: 核心算法工程师(实习), 科大讯飞

教育经历

• 2016.09 - 2023.07: 博士, 信息与通信工程, 西北工业大学
  • 导师：Susanto Rahardja, IEEE Fellow, 新加坡工程院院士
  • 推免直博，校优秀毕业生
  • 智能声学与临境通信研究中心 (带头人: 陈景东教授)
• 2021.06 - 2022.06: 联合培养项目, 计算机科学, 新加坡国立大学
  • 导师：黄智勇
  • 国家公派CSC项目
  • 华为博士生学术资助计划
• 2012:09 - 2016.07: 学士, 电子信息工程, 西北工业大学
  • 校优秀毕业生, 校优秀毕业设计
  • “宝钢” 学生优秀奖, 中国电信奖学金
  • 作为校年度学生代表，事迹收录于《国家奖学金获奖学生风采录》
• 2017: 法国优秀硕士暑期学校，项目: 课程为社会、环境和历史遗产的多谱成像
• 2019: IEEE信号处理协会暑期学校， 主题: 智能信号与信息处理

论文

目前, 谷歌学术引用超1400, h指数20, i10指数32

• 期刊论文(第一作者)
  • M. Wang, J. Chen, X.L Zhang, S. Rahardja, “End-to-end Multi-modal Speech Recognition on An Air and Bone Conducted Speech Corpus”, IEEE/ACM Transactions on Audio, Speech and Language Processing, vol. 31, pp. 513-524, 2023.
  • M. Wang, M. Zhao, J. Chen, S. Rahardja, “Nonlinear Unmixing of Hyperspectral Data via Deep Autoencoder Networks”, IEEE Geoscience and Remote Sensing Letters, vol. 16, no. 9, pp. 1467-1471, Sept. 2019.
  • M. Wang, J. Chen, X.L. Zhang, Z. Huang, S. Rahardja, “Multi-modal Speech Enhancement with Bone-conducted Speech in Time Domain”, Applied Acoustics, vol.200, 109058, 2022.
  • M. Wang, S. Rahardja, P. Fränti, S. Rahardja, “Single-lead ECG Recordings modeling for End-to-end Recognition of Atrial Fibrillation with Dual-path RNN”, Biomedical Signal Processing and Control, vol. 79, no. 1, 104067, 2023.
  • M. Wang, H. Wang, Y. Yin, S. Rahardja, Z. Qu, “Temperature field prediction for various porous media considering variable boundary conditions using deep learning method”. International Communications in Heat and Mass Transfer, 132, 105916, 2022.
  • M. Wang, X.L. Zhang, S. Rahardja, “An Unsupervised Deep Learning System for Acoustic Scene Analysis”, Applied Sciences, vol. 10, no. 6, pp. 2076, Mar. 2020.
  • 王谋, 白吉生, 黄思维, 李茁, 刘鑫, 杨飞然, 王子腾. 基于注意力机制的酒瓶裂纹敲击异常声音检测系统. 计算机工程与应用. 2024. (会议论文推荐至期刊发表)
• 会议论文(第一作者)
  • M. Wang, K. Kuang, Z. Li, F. Yang, J. Bai, X. Liu, “Deep-filtering-based Speech Enhancement via Bone-conducted Speech”, 15th IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), 2025.
  • M. Wang, Z. Li, J. Wang, et al. “Implementation and Analysis of Neural Network Quantization in Speech Enhancement”, National Conference on Man-Machine Speech Communication (NCMMSC), 2025.
  • M. Wang, X.L. Zhang, S. Rahardja, “A Hybrid Approach for Mobile Phone Clustering with Speech Recordings”, 2019 12th International Conference on Ubi-media Computing and Workshops, Bali, Indonesia, 2019, pp. 205-209.
  • M. Wang, R. Wang, X.L. Zhang, S. Rahardja, “Hybrid Constant-Q Transform Based CNN Ensemble for Acoustic Scene Classification”, 2019 11th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, Lanzhou, China, 2019, pp. 1511-1516.
  • 王谋, 白吉生, 黄思维, 李茁, 刘鑫, 杨飞然, 王子腾. 基于注意力机制和数据过采样的酒瓶裂纹敲击异常声音检测系统. 第十九届全国人机语音通讯学术会议(NCMMSC). 2024.
• 期刊论文(其他作者)
  • H. Wang, M. Wang, Y.Yin, Z. Qu, “A universal structure of neural network for predicting heat, flow and mass transport in various three-dimensional porous media”, International Journal of Heat and Mass Transfer, vol. 241, 126688, 2025. (共同一作)
  • S. Rahardja, M. Wang, B. P. Nguyen, P. Fränti, S. Rahardja, “A Lightweight Classification of Adaptor Proteins Using Transformer Networks”. BMC Bioinformatics, vol. 23, 461, 2022. (共同一作)
  • Z. Shang, B. Liu, M. Wang, X. Liu, P. Zhang. “Light Lightweight Speech Enhancement via Learnable Prior and Schrödinger Bridge Generative Adversarial Network”, The Journal of the Acoustical Society of America. 2026.
  • L. Guo, Z. Bai, M. Wang, Z. Zhao, J. Chen, J. Benesty, “Harmonic model-based feature representation for temperature-modulated electronic noses”, Sensors and Actuators B: Chemical, 139566, 2026.
  • N. Gao, J. Guo, M. Wang, D. Qin, Q. Huang, X. Liang, G. Pan, “Sound-absorption of resonant composite metastructure based on machine learning reverse assisted design”, Applied Acoustics, 2026.
  • N. Gao, J. Guo, M. Wang, Y. Qu, X. Peng, Y. Tang, X. Liang, G. Pan, “On demand design of two-dimensional phononic crystal bandgap based on machine learning and multi-objective topology optimization”, Mechanical Systems and Signal Processing, 2026.
  • Dynamic Training Strategies for Domain Generalization in Self-supervised Anomaly Sound Detection, IEEE Transactions on Audio, Speech and Language Processing, 2026.
  • Z. ZHANG, N. GAO, X. LIANG, Y. TANG, X. PENG, Y. QU, M. WANG, G. PAN, “Noise suppression via controlled ion acoustic wave propagation”, SCIENCE CHINA Technological Sciences, 2026.
  • N Gao, J Guo, Z Zhang, D Qin, Q Huang, H Dong, M Wang, G Pan, Machine-learning-based lightweight optimization for vibration isolation of dual acoustic black hole beams. Structures, 2026.
  • N. Gao, M. Wang, X. Liang, G. Pan, “On-demand prediction of low-frequency average sound absorption coefficient of underwater coating using machine learning”, Results in Engineering, 104163, 2025.
  • S. Guan, J. Wang, M. Wang, J. Chen, “Online Sampling Rate Offset Estimation via Real Part Maximization”, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 33, pp. 3623-3637, 2025.
  • J. Bai, H. Liu, M. Wang, D. Shi, W. Wang, M. D. Plumbley, W. Gan, J. Chen, “AudioSetCaps: An Enriched Audio-Caption Dataset using Automated Generation Pipeline with Large Audio and Language Models”, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 33, pp. 2817-2829, 2025. [github]
  • K. Kuang, F. Yang, M. Wang, J. Yang, “Low-complexity bone conduction-aided speech enhancement leveraging sub-band and full-band architecture”, Applied Acoustics, 240, 110924, 2025.
  • N. Gao, J. Guo, M. Wang, D. Qin, X. Liang, Z. Zhang, G. Pan, “Achieving Precise Prediction of Sound Absorption Performance for Composite Acoustic Metamaterials Utilizing Machine Learning”, Journal of Sound and Vibration, 119469, 2025.
  • H. Yin, J. Chen, J. Bai, M. Wang, S. Rahardja, D. Shi, W. Gan. “Multi-granularity acoustic information fusion for sound event detection”, Signal Processing, 227, 109691, 2025.
  • D. Zhang, J. Chen, J. Bai, M. Wang, D. Shi, Q. Niu, A. Bernardini, “Sound Event Localization and Classification using Wireless Acoustic Sensor Networks in Outdoor Environments”, IEEE Sensors Journal, 2025.
  • F. Cao, Q. Zheng, Z. Xia, M. Wang, C. Hou, B. Li, H. Hou, B. Cheng, “Inverse design of bending channel sound-absorbing structures with porous material by two-stage deep neural network model”, Physica Scripta, 100, 5, 055963, 2025. (通讯作者)
  • D. Zhang, J. Chen, S. Huang, J. Bai, Y. Jia, M. Wang. “Synthesis-to-real robust training for enhanced sound event localization and detection using dynamic kernel convolution networks”, Applied Acoustics, 228, 110267, 2025.
  • D. Li, M. Wang, S. Rahardja. “Contrastive learning for deep tone mapping operator”, Signal Processing: Image Communication, 126, 117130, 2024.
  • S. Guan, M. Wang, Z. Bai, J. Wang, J. Chen, J. Benesty, “Smoothed Frame-Level SINR and Its Estimation for Sensor Selection in Distributed Acoustic Sensor Networks”, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 32, pp. 4554-4568, 2024.
  • D. Zhang, J. Chen, J. Bai, M. Wang, MS Ayub, Q. Yan, D. Shi, W-Seng Gan, “Multiple Sound Sources Localization Using Sub-band Spatial Features and Attention Mechanism”, Circuits, Systems, and Signal Processing, 2024.
  • C. Yan, S. Yan, T. Yao, Y. Yu, G. Pan, L. Liu, M. Wang, J. Bai, “A Lightweight Network Based on Multi-Scale Asymmetric Convolutional Neural Networks with Attention Mechanism for Ship-Radiated Noise Classification”, Journal of Marine Science and Engineering, vol. 12, no. 1, 130, 2024.
  • 刘升东, 杨飞然, 王谋, 李茁, 杨军. 扩散噪声环境下的多通道语音分离方法. 声学学报, vol. 49, no. 06, pp. 1304-1314, 2024.
  • J. Bai, J. Chen, M. Wang, M. S. Ayub, Q. Yan, “SSDPT: Self-Supervised Dual-Path Transformer for Anomalous Sound Detection in Machine Condition Monitoring”, Digital Signal Processing, vol. 135, 103939, 2023.
  • T. Liu, L. Guo, M. Wang, C. Su, J. Chen, W. Wu, “Review on Algorithm Design in Electronic Noses: Challenges, Status, and Trends”, Intelligent Computing, vol. 2, 0012, 2023.
  • J. Bai, J. Chen, M. Wang, “Multimodal Urban Sound Tagging With Spatiotemporal Context”, IEEE Transactions on Cognitive and Developmental Systems, vol. 15, no. 2, pp. 555-565, June 2023.
  • J. Bai, J. Chen, M. Wang, M. S. Ayub, Q. Yan, “A Squeeze-and-Excitation and Transformer based Cross-task Model for Environmental Sound Recognition”, IEEE Transactions on Cognitive and Developmental Systems, vol. 15, no. 3, pp. 1501-1513, Sept. 2023.
  • N. Gao, M. Wang, B. Cheng, “Deep auto-encoder network in Predictive Design of Helmholtz resonator: On-demand prediction of sound absorption peak”, Applied Acoustics,191, 108680, 2022.
  • B. Cheng, M. Wang, N. Gao, H. Hou, “Machine learning inversion design and application verification of a broadband acoustic filtering structure”, Applied Acoustics, 187, 108522, 2022.
  • M. Zhao, M. Wang, J. Chen, S. Rahardja, “Perceptual Loss Constrained Adversarial Autoencoder Networks for Hyperspectral Unmixing”, IEEE Geoscience and Remote Sensing Letters, vol. 19, pp.1-5, 2022.
  • Q. Wang, M. Wang, Y. Yang, X. Zhang, “Multi-modal Emotion Recognition using EEG and Speech Signals”, Computers in Biology and Medicine, vol. 149, 105907, 2022.
  • X. Li, J. Chen, J. Bai, M. S. Ayub, D. Zhang, M. Wang, Q. Yan, “Deep Learning-based DOA Estimation Using CRNN for Underwater Acoustic Arrays”, Frontiers in Marine Science, vol. 9, 2022.
  • M. Zhao, M. Wang, J. Chen and S. Rahardja, “Hyperspectral Unmixing for Additive Nonlinear Models With a 3-D-CNN Autoencoder Network”, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, 2021.
  • N. Gao, M. Wang, B. Cheng, H. Hou, “Inverse design and experimental verification of an acoustic sink based on machine learning”, Applied Acoustics, 180, 108153, 2021.
  • H. Wang, Y. Yin, B. Li, J. Bai, M. Wang, “High-Throughput Screening of Metal-Organic Frameworks for the Impure Hydrogen Storage Supplying to a Fuel Cell Vehicle”, Transport in Porous Media, 140, 727-742, 2021.
  • 朱文博, 王谋, 张晓雷, Susanto Rahardja, 基于语音分离的人工设计特征、参数化特征和可学习特征的比较, 中国传媒大学学报(自然科学版), vol. 28, no. 03, pp. 52-57, 2021.
• 会议论文(其他作者)
  • Bridging the Distribution Gap in Real-world Far-field Speech Enhancement via Lighweight Latent Representation Alignment. Interspeech, 2026.
  • Z. Li, M. Wang, F. Yang, X. Liu, “Model Optimization Methods for short-duration Speaker Verification”, 15th IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), 2025.
  • Y. Zhao, Z. Shang, M. Wang, X. Liu, “Restoring Harmonics: Enhancing Speech Quality with Deep Mask and Harmonic Restoration Network”. Interspeech, 2025.
  • Y. Jia, J. Bai, M. Wang, J. Chen, P. Lu, F. Deng, S. Huang, “Anomalous Sound Detection based on Dual-dimension Data Mixing and Progressive Parameter Fine-tuning”, 15th IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), 2025.
  • B. Liu, Z. Shang, H. Xie, M. Wang, X. Liu, P. Zhang, “Pitch-assistant Harmonic Recovery for Efficient Speech Enhancement”, 2025 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 2025.
  • H. Yin, M. Wang. J. Bai. D. Shi. W. Gan. J. Chen, “Sub-Band and Full-Band Interactive U-Net with Dprnn for Demixing Cross-Talk Stereo Music”, 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW), Seoul, Korea, Republic of, 2024, pp. 21-22.
  • J. Bai, H. Liu, M. Wang, S. Rahardja, “AudioSetCaps: Enriched Audio Captioning Dataset Generation Using Large Audio Language Models”, NeurIPS 2024 Workshop, 2024.
  • J. Bai, H. Yin, M. Wang, D. Shi, W. Gan, J. Chen, “Audiolog: LLMs-Powered Long Audio Logging with Hybrid Token-Semantic Contrastive Learning”, 2024 IEEE International Conference on Multimedia and Expo (ICME), Niagara Falls, ON, Canada, 2024, pp. 1-6.
  • M Liu, X. Li, M. Wang, X.L Zhang, S. Rahardja, “MTBV: Multi-Trigger Backdoor Attacks on Speaker Verification”, 2024 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), 2024.
  • X. Tan, J. Chen, J. Yang, S. Rahardja, M. Wang, S. Rahardja, “Ensemble of Deep Variational Mixture Models for Unsupervised Clustering”, 2024 IEEE International Conference on Image Processing (ICIP), Abu Dhabi, United Arab Emirates, 2024, pp. 807-813.
  • Z. Li, J. Lu, Z. Zhao, W. Wang, M. Wang, Z, Wang, X. Liu, “Progressive Sub-Graph Clustering Algorithm for Semi-Supervised Domain Adaptation Speaker Verification”, 2024 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), 2024.
  • 李茁, 王谋, 王子腾, 刘鑫, 杨飞然, 面向说话人识别的最近邻惩罚圆损失函数, 第十九届全国人机语音通讯学术会议(NCMMSC2024), 2024.
  • J. Bai, S. Huang, H. Yin, Y. Jia, M. Wang, J. Chen, “3D Audio Signal Processing Systems for Speech Enhancement and Sound Localization and Detection”, 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, 2023, pp. 1-2.
  • H. Yin, J. Bai, M. Wang, S. Huang, Y. Jia, J. Chen, “Convolutional Recurrent Neural Network with Attention for 3D Speech Enhancement”, 13th IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), Zhengzhou, China, 2023, pp. 1-5.
  • J. Chen, M. Wang, X. Zhang, Z. Huang, S. Rahardja, “End-to-end Multi-modal Speech Recognition with Air and Bone Conducted Speech”. 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Singapore, 2022, pp. 6052-6056.
  • J. Bai, S. Huang, Y. Jia, M. Wang, J. Chen, “Cross-stitch Network based System for Sound Event Localization and Detection in L3DAS22 Challenge”, L3DAS22 Challenge, 2022, pp. 6-10.
  • B. Li, M. Wang, Z. Mao, B. Song, W. Tian, Q. Sun, W. Wang, “Machine Learning Methods for Temperature Prediction of Autonomous Underwater Vehicle’s Battery Pack”, International Conference on Autonomous Unmanned System, 2022, pp. 3204–3215.
  • J. Bai, M. Wang, J. Chen, “Dual-Path Transformer for Machine Condition Monitoring”, 13th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, Tokyo, Japan, 2021, pp. 1144-1148.
  • W. Zhu, M. Wang, X.L. Zhang, S. Rahardja, “A comparison of handcrafted, parameterized, and learnable features for speech separation”, 13th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, Tokyo, Japan, 2021, pp. 635-639.
  • R. Wang, M. Wang, X.L. Zhang, S. Rahardja, “Domain Adaptation Neural Network for Acoustic Scene Classification in Mismatched Conditions”, 2019 11th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, Lanzhou, China, 2019, pp. 1501-1505.
  • S. Zhang, Y. Wu, M. Wang, “Pulse Signal Analysis for Pneumoconiosis Detection with SVM”, 2018 International Symposium on Computer, Consumer and Control, Taichung, Taiwan, 2018, pp. 221-224.

专利

• 王谋, 陈俊淇, 张晓雷, 王逸平, 一种端到端的骨气导语音联合识别方法，发明专利，202210153909.5.
• 王谋，张晓雷，王逸平, 一种端到端的骨气导语音联合增强方法, 发明专利，202011612056.4. 授权
• 王谋，张晓雷，王逸平, 一种应用于声场景的分类方法及装置, 发明专利，201810413386.7. 授权
• 白吉生，陈建峰，王谋，项彬，一种基于卷积神经网络的局部放电超声波检测和定位方法，发明专利，申请公告日：2023.5.15.
• 汪辉，白俊强，王谋，郭彬，刘成茂, 一种光电导航系统的超分辨率图像异常目标检测方法及系统, 发明专利，202011242621.2. 授权
• 申晓红，王谋，孙琦璇，董海涛，马石磊，张红伟，王逸平，一种基于HPSS的水下目标被动检测方法，发明专利，202010351761.7, 授权公告号CN111505650B.
• 申晓红，孙琦璇，王谋，董海涛，马石磊，锁健，王逸平，一种基于卷积神经网络的水下目标被动检测方法，发明专利，202010432897.0.
• 刘松涛，王谋，董鹏飞，易政宇，杨宏安， 自平衡3D激光扫描仪， 实用新型专利， 201520355566.6.

书籍

• 合著General Audio Signal Processing with Deep Learning，Springer, 2026
• 参与编写《复杂环境下语音信号处理的深度学习方法》，张晓雷著，清华大学出版社，2022

挑战赛

• 第一届”声华杯”声学技术大赛, TWS耳机语音增强, 二等奖, 2023
• 科大讯飞AI开发者大赛, 基于声纹的人声分离挑战赛, 二等奖, 2022
• DCASE Challenge 2020 Task5, 第二名

奖励

• NCMMSC2024 Best Paper Award, 证书编号：CCF-AWARD-TC-2024-03922, 2024.8.
• International Conference on Energy and AI 2023 Best Presentation Award, 2023.8.12.
• 陕西省机械工程学会科学技术奖，二等奖，2023.7.5
• 陕西高等学校科学技术研究优秀成果奖，二等奖，2023.4
• IEEE Transactions on Multimedia杰出审稿人
• 国际会议Ubi-Media 优秀论文奖, 2019
• 学科竞赛：
  • 世界首届大学生水下机器人大赛创意概念赛道一等奖
  • 第七届”互联网+”大赛陕西省省赛金奖
  • “兆易创新杯”第十七届中国研究生电子设计竞赛商业计划书专项赛全国一等奖，西北赛区一等奖
  • 陕西省第八届研究生电子设计竞赛暨第十六届中国研究生电子设计竞赛西北分赛区团队一等奖
  • 2018届全国大学生电子设计创意创新大赛，一等奖
  • “内江高新杯”创客大赛，二等奖
  • 2017年”深创杯”全国大学生创新创业大赛，杰出创新项目奖
  • 中国研究生数学建模竞赛，二等奖（2016），三等奖（2017）
  • 全国海洋航行器设计与制作大赛特等奖两项（2015，2022），一等奖一项（2015），二等奖两项（2015），西北赛区一等奖（2022）
  • 全国大学生电子设计竞赛全国二等奖及陕西赛区一等奖
  • “挑战杯”全国大学生课外学术作品竞赛全国二等奖及陕西省特等奖

学术任职

• 审稿人, IEEE Transactions on Multimedia, IEEE Transactions on Audio, Speech and Language Processing, IEEE Transactions on Industrial Electronics, IEEE Transactions on Information Forensics & Security, IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Cognitive and Developmental Systems, Neural Networks 等10余个国际期刊.

其他经历

• Technical Program Committee, ICSPCC 2026.
• 举办APSIPA ASC 2025 Grand Challenge, Spatiotemporal Enhanced Semi-supervised Acoustic Scene Classification.
• Sponsor & Web Chair, ISCPCC国际会议，印度尼西亚，2024
• 举办ICME 2024 Grand Challenge, 2024, Semi-supervised Acoustic Scene Classification under Domain Shift.
• 志愿者, APSIPA ASC国际会议(2018), IWAENC国际会议(2016).
• 志愿者, IEEE亚太区五十周年与IEEE西安分会十周年庆典, 2017.
• 创新工场 Deecamp 2018 人工智能训练营, AI自动作曲项目, 优秀Demo奖