高欣
- 电子邮箱：xlhhh74@bupt.edu.cn
- 所在单位：智能工程与自动化学院
- 学历：研究生毕业
- 性别：男
- 学位：博士学位
- 职称：副教授
- 在职信息：在职
- 毕业院校：北京航空航天大学
- 博士生导师
- 硕士生导师
- 学科：控制科学与工程
- 所属院系：智能工程与自动化学院
- 曾获荣誉：
- 2021当选：河北省科技进步三等奖
- 2019当选：中国电力企业联合会电力科技创新特等奖
- 2019当选：中国电机工程学会中国电力科学技术进步二等奖
- 2019当选：国家电网有限公司科学技术进步一等奖
- 2014当选：军队科技进步三等奖
- 2020当选：获得北京邮电大学第三届“优秀研究生育人导师”称号
- 2024当选：北京邮电大学校级优秀硕士学位论文指导教师称号
- 2022当选：北京邮电大学校级优秀硕士学位论文指导教师称号
- 2021当选：北京邮电大学校级优秀硕士学位论文指导教师称号
- 2024当选：北京邮电大学人工智能学院院级优秀硕士学位论文指导教师称号
- 2023当选：北京邮电大学人工智能学院院级优秀硕士学位论文指导教师称号
访问量：
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[1]
Shiyuan Fu, Xin Gao*, et al. A time series anomaly detection method based on series-parallel transformers with spatial and temporal association discrepancies[J]. Information Sciences, 2024, 657: 119978. （SCI，中科院1区，Top期刊）
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[2]
Jiahao Yu, Xin Gao*, et al. An adversarial contrastive autoencoder for robust multivariate time series anomaly detection[J]. Expert Systems with Applications, 2024,245: 123010. （SCI，中科院1区，Top期刊）
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[3]
Jiahao Yu, Xin Gao*, et al. A filter-augmented auto-encoder with learnable normalization for robust multivariate time series anomaly detection[J]. Neural Networks, 2024, 170: 478-493. （SCI，中科院1区，Top期刊）
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[4]
Zhihang Meng, Xin Gao*, et al. An imbalanced contrastive classification method via similarity comparison within sample-neighbors with adaptive generation[J]. Information Sciences, 2024, 662: 120273. （SCI，中科院1区，Top期刊）
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[5]
Bing Xue, Xin Gao*, et al. A Robust Multi-Scale Feature Extraction Framework with Dual Memory Module for Multivariate Time Series Anomaly Detection[J]. Neural Networks. 2024,177:106395.（SCI，中科院1区，Top期刊）
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[6]
Shiyuan Fu, Xin Gao*, et al. Multivariate Time Series Anomaly Detection via Separation, Decomposition, and Dual Transformer-based Autoencoder[J]. Applied Soft Computing. 2024,159:111671.（SCI，中科院1区，Top期刊）
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[7]
Zijian Huang, Xin Gao*, et al. An imbalanced binary classification method via space mapping using normalizing flows with class discrepancy constraints[J]. Information Sciences, 2023, 623: 493-523. （SCI，中科院1区，Top期刊）
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[8]
Xin Gao*，Jiahao Yu, et al. An ensemble-based outlier detection method for clustered and local outliers with differential potential spread loss[J]. Knowledge-Based Systems, 2022, 258: 110003. （SCI，中科院1区，Top期刊）
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[9]
KangSheng Li, Xin Gao*, et al. Robust outlier detection based on the changing rate of directed density ratio[J]. Expert Systems with Applications, 2022, 207: 117988. （SCI，中科院1区，Top期刊）
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[10]
Xin Gao*, Xin Jia, et al. An ensemble contrastive classification framework for imbalanced learning with sample-neighbors pair construction[J]. Knowledge-Based Systems, 2022, 249: 109007. （SCI，中科院1区，Top期刊）
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[11]
Qingxuan Jia, Chunxu Chen, Xin Gao*，et al. Anomaly detection method using center offset measurement based on leverage principle[J]. Knowledge-Based Systems, 2020, 190: 105191. （SCI，中科院1区，Top期刊）
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[12]
Xin Gao*，Bing Ren, et al. An ensemble imbalanced classification method based on model dynamic selection driven by data partition hybrid sampling[J]. Expert Systems with Applications, 2020, 160: 113660. （SCI，中科院1区，Top期刊）
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[13]
Xin Gao*, Zhihang Meng, et al. An imbalanced binary classification method based on contrastive learning using multi-label confidence comparisons within sample-neighbors pair[J]. Neurocomputing, 2023, 517: 148-164. （SCI，中科院2区，Top期刊）
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[14]
Kangsheng Li, Xin Gao*, et al. Detection of local and clustered outliers based on the density–distance decision graph[J]. Engineering Applications of Artificial Intelligence, 2022, 110: 104719. （SCI，中科院2区，Top期刊）
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[15]
Xin Gao*, Yang He, et al. A multiclass classification using one-versus-all approach with the differential partition sampling ensemble[J]. Engineering Applications of Artificial Intelligence, 2021, 97: 104034. （SCI，中科院2区，Top期刊）
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[16]
Guangyao Zhang, Xin Gao*, et al. Probabilistic autoencoder with multi-scale feature extraction for multivariate time series anomaly detection[J]. Applied Intelligence, 2023, 53(12): 15855-15872. （SCI，中科院2区）
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[17]
Bing Xue, Xin Gao*, et al. A contrastive autoencoder with multi-resolution segment-consistency discrimination for multivariate time series anomaly detection[J]. Applied Intelligence, 2023, 53(23): 28655-28674. （SCI，中科院2区）
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[18]
Xin Jia, Xin Gao*, et al. Global reliable data generation for imbalanced binary classification with latent codes reconstruction and feature repulsion[J]. Applied Intelligence, 2023, 53(13): 16922-16960. （SCI，中科院2区）
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[19]
Zhiyu Liu, Xin Gao*, et al. Correlation-based feature partition regression method for unsupervised anomaly detection[J]. Applied Intelligence, 2022, 52(13): 15074-15090. （SCI，中科院2区）
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[20]
Xiao Fang, Xin Gao*, et al. A Non-Uniform Low-Light Image Enhancement Method with Multi-Scale Attention Transformer and Luminance Consistency Loss[J]. Visual Computer. 2024:1-18（SCI，中科院3区）
