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李畅，博士，副教授，2018年3月获得华中科技大学工学博士学位，2018年4月入职英国威廉希尔公司。目前主要从事图像处理、生物医学仪器信号测量与处理和信息融合等方面的研究工作。作为项目负责人承担了国家自然科学基金、安徽省自然科学基金、校学术新人提升A计划和B计划等多项科研项目。在IEEE SPM、IEEE TAC、IEEE JBHI、IEEE TIM、IEEE TNSRE和IEEE TII等权威期刊及会议发表相关论文100余篇，8篇论文入选高被引论文，论文总被引5000余次。入选斯坦福大学发布的全球前2%顶尖科学家榜单。担任IEEE TIP、IEEE TSP、IEEE TNNLS、IEEE TMM、IEEE TAC等多个国际知名期刊审稿人。

欢迎对相关研究方向感兴趣的同学报考我的研究生，可将个人简历发送至我的邮箱：changli@hfut.edu.cn。

图像处理、生物医学仪器信号测量与处理、机器学习、计算机视觉、信息融合。

Research Gate学术主页：https://www.researchgate.net/profile/Chang-Li-50

[1] “EEG-Based Emotion Recognition via Neural Architecture Search”, IEEE Transactions on Affective Computing, Vol. 14, No. 2, pp. 957-968, 2023. (ESI高被引论文) 

[2] “EEG-Based Emotion Recognition via Channel-Wise Attention and Self Attention”, IEEE Transactions on Affective Computing, Vol. 14, No. 1, pp. 382-393, 2023. (ESI高被引论文)

[3] “Source-Free Domain Adaptation for Privacy-Preserving Seizure Prediction”, IEEE Transactions on Industrial Informatics, 2023. 

[4] “Centroid-Guided Domain Incremental Learning for EEG-Based Seizure Prediction”, IEEE Transactions on Instrumentation and Measurement, 2023. 

[5] “Privacy-Preserving Domain Adaptation for Intracranial EEG Classification via Information Maximization and Gaussian Mixture Model”, IEEE Sensors Journal, 2023.

[6] “Online Test-Time Adaptation for Patient-Independent Seizure Prediction”, IEEE Sensors Journal, Vol. 23, No. 19, pp. 23133-23144, 2023. 

[7] “Patient-Specific Seizure Prediction From Electroencephalogram Signal via Multichannel Feedback Capsule Network”, IEEE Transactions on Cognitive and Developmental Systems, Vol. 15, No. 3, pp. 1360-1370, 2023.

[8] “EEG-based seizure prediction via hybrid vision transformer and data uncertainty learning”, Engineering Applications of Artificial Intelligence, Vol. 123, pp. 106401, 2023. 

[9] “EEG-based Emotion Recognition via Transformer Neural Architecture Search”, IEEE Transactions on Industrial Informatics, Vol. 19, No. 4, pp. 6016-6025, 2023.

[10] “Bi-CapsNet: A Binary Capsule Network for EEG-Based Emotion Recognition”, IEEE Journal of Biomedical and Health Informatics, Vol. 27, No. 3, pp. 1319-1330, 2023.

[11] “EEG-Based Seizure Prediction via Model Uncertainty Learning”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 31, pp. 180-191, 2023.

[12] “Spatio-temporal MLP network for seizure prediction using EEG signals”, Measurement, Vol. 206, pp. 112278, 2023.

[13] “EEG-based seizure prediction via Transformer guided CNN”, Measurement, Vol. 203, pp. 111948, 2022.

[14] “EEG-Based Emotion Recognition via Efficient Convolutional Neural Network and Contrastive Learning”, IEEE Sensors Journal, Vol. 22, No. 20, pp. 19608-19619, 2022.

[15] “Patient-Specific Seizure Prediction via Adder Network and Supervised Contrastive Learning”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 30, pp. 1536-1547, 2022.

[16] “Emotion recognition from EEG based on multi-task learning with capsule network and attention mechanism”, Computers in Biology and Medicine, Vol. 143, pp. 105303, 2022. (ESI高被引论文)

[17] “Multi-channel EEG-based emotion recognition in the presence of noisy labels”, Science China-Information Sciences, Vol. 65, No. 4, pp. 140405, 2022.

[18] “Spatial-Spectral Nonlinear Hyperspectral Unmixing Under Complex Noise”, IEEE Sensors Journal, Vol. 22, No. 5, pp. 4338-4346, 2022. 

[19] “Superpixel-Based Noise-Robust Sparse Unmixing of Hyperspectral Image”, IEEE Geoscience and Remote Sensing Letters, Vol. 19, pp. 6004405, 2022.

[20] “Toward Open-World Electroencephalogram Decoding Via Deep Learning: A Comprehensive Survey”, IEEE Signal Processing Magazine, Vol. 39, No. 2, pp. 117-134, 2022. (特邀综述, 信号处理领域国际顶级期刊)

[21] “Plane-Wave Image Reconstruction via Generative Adversarial Network and Attention Mechanism”, IEEE Transactions on Instrumentation and Measurement, Vol. 70, pp. 4505115, 2021.

[22] “Emotion Recognition from Multi-Channel EEG via Deep Forest”, IEEE Journal of Biomedical and Health Informatics, Vol. 25, No. 2, pp. 453-464, 2021. (ESI高被引论文)

[23] “AttentionFGAN: Infrared and Visible Image Fusion using Attention-based Generative Adversarial Networks”, IEEE Transactions on Multimedia, Vol. 23, pp. 1383-1396, 2021. (ESI高被引论文)

[24] “Multi-channel EEG-based emotion recognition via a multi-level features guided capsule network”, Computers in Biology and Medicine, Vol. 123, pp. 103927, 2020. 

[25] “Sparse unmixing of hyperspectral data with bandwise model”, Information Sciences, Vol. 512, pp. 1424-1441, 2020.

[26] “Robust Multichannel EEG Compressed Sensing in the Presence of Mixed Noise”, IEEE Sensors Journal, Vol. 19, No. 22, pp. 10574-10583, 2019.

[27] “Infrared and visible image fusion methods and applications: A survey”, Information Fusion, Vol. 45, pp. 153-178, 2019. (特邀综述, ESI高被引论文)

[28] “FusionGAN: A generative adversarial network for infrared and visible image fusion”, Information Fusion, Vol. 48, pp. 11-26, 2019. (ESI高被引论文)

[29] “Hyperspectral Unmixing with Bandwise Generalized Bilinear Model”, Remote Sensing, Vol. 10, No. 10, pp. 1600, 2018.

[30] “Infrared and visible image fusion via gradient transfer and total variation minimization”, Information Fusion, Vol. 31, pp. 100-109, 2016. (ESI高被引论文)

[1] 全球前2%顶尖科学家（2022、2023）

[2] 合肥工业大学年度“优秀班主任”称号（2019）

[3] 博士研究生国家奖学金（2016）

[4] 指导研究生获硕士研究生国家奖学金：张中振、赵禹阊、邓志伟、毛婷婷

[5] 指导研究生获合肥工业大学优秀毕业生：张中振（省优）、赵禹阊、林学娟

[6] 指导研究生获合肥工业大学三好学生：邓志伟（优秀三好）、邵成浩、赵红宇

[7] 指导本科生参加竞赛获国家级奖和省级奖10余项。