Biography
I am a Senior Member of IEEE, a committee member of the Chinese Association of Automation, and the Medical Image Computing Seminar (MICS). I have served as the PI for 10 funded projects since 2019, including grants from the National Natural Science Foundation of China (NSFC). I have published 50+ papers in leading journals and conferences, such as Nature Machine Intelligence, TPAMI, TCYB, TNNLS, TMM, TASLP, PR, ACL, MICCAI, and ACM-MM. My publications include two ESI Highly Cited Paper as the first author and have garnered over 2,400+ citations on Google Scholar. I have been a reviewer for the NSFC since 2022 and serve as a reviewer for premier journals, including TPAMI, TIP, TAC, and TMI. I have been an Area/Session Chair for several IEEE international conferences.
Key projects I have led include the development of the “Information System for the China National Biobank (Eastern Center),” a “Million-Scale Healthcare Data Extraction and Analysis System,” and “Immense Motor Function Rehabilitation Based on Brain-Computer Interface.” These projects have won several provincial and municipal innovation championships, such as the Zhejiang Provincial Rehabilitation Medicine Transformation Alliance Competition and the Hangzhou Bay Innovation Plan, the latter of which secured 2 million RMB in funding.
Google: https://scholar.google.com/citations?hl=zh-CN&user=hzEaITAAAAAJ ResearchGate: https://www.researchgate.net/profile/Jinpeng-Li-3
Education
2015 - 2019: PhD, National Laboratory of Multimodal Artificial Intelligence, Institute of Automation, Chinese Academy of Sciences. 2008 - 2015: BS and MS, School of Automation, University of Science and Technology, Beijing.
Research Areas
Neural Computation and BCI: 1) Neural information encoding/decoding based on fMRI and EEG. 2) Affective BCI based on EEG and supplementary modalities. 3) Immense motor function rehabilitation system based on EEG. 4) Generalizable BCI across individuals and experiments. Medical Image Analysis: 1) Multimodal clinical data analysis for cancer screening and diagnosis. 2) Explainable, verifiable and generalizable vison models. Machine Learning Algorithms: Self-supervised learning, weakly-supervised learning, and transfer learning algorithms and their applications in medical AI.
Courses Taught
Pattern Recognition for undergraduate students Machine Vision for graduate students
Selected Publications
- Du, Changde;Fu, Kaicheng;Wen, Bincheng;Sun, Yi;Peng, Jie;Wei, Wei;Gao, Ying;Wang, Shengpei;Zhang, Chuncheng;Li, Jinpeng;Qiu, Shuang;Chang, Le;He, Huiguang,Human-like object concept representations emerge naturally in multimodal large language models,Nature Machine Intelligence,2025
- Zhang, Shuangqing;Zhao, Gangming;Lyu, Fan;Wang, Songping;Zhang, Zhang;Zhao, Fang;Li, Jinpeng;Shan, Caifeng;Wang, Liang,MambaPTP: Exploring the Potential of Mamba for Pedestrian Trajectory Prediction,IEEE Transactions on Circuits and Systems for Video Technology,2025
- Wang, Sheng;Zhu, Enwei;Zhao, Fangyuan;Bu, Dechao;Li, Jinpeng;Zhao, Yi,MAT: Marker-Lattice Transformer for Entity, Relation and Attribute Extraction From Chinese Clinical Text,IEEE Transactions on Audio Speech and Language Processing,2025
- Li, Xujun;Wei, Xin;Jiang, Jing;Chen, Danxiang;Zhang, Wei;Li, Jinpeng*,ManiNeg: Manifestation-guided multimodal pretraining for mammography screening,Computers in Biology and Medicine,2025
- Du, C., Fu, K., Wen, B., Sun, Y., Peng, J., Wei, W., Gao, Y., Wang, S., Zhang, C., Li, J., Qiu, S., Chang, L., & He, H.,Human-like Object Concept Representations Emerge Naturally in Multimodal Large Language Models,Nature Machine Intelligence,2025
- Tao, Y., Xu, Y., Yu, Y., & Li, J.*,Accurate Coronary Microvascular Segmentation with Parallel Local-global Chains,IEEE BIBM 2025,2025
- Wang, A., Li, Y., Pang, Y., Li, J., Hu, Y., & Wang, Q.,SP-Net: Semantic Distillation and Pixel Refine Network for Surgical Triplet Recognition,IJCNN 2025,2025
- Jin, Ming;Du, Changde;He, Huiguang;Cai, Ting;Li, Jinpeng,PGCN: Pyramidal Graph Convolutional Network for EEG Emotion Recognition,IEEE Transactions on Multimedia,2024
- Du, C., Fu, K., Li, J., & He, H.,Decoding Visual Neural Representations by Multimodal Learning of Brain-Visual-Linguistic Features,IEEE Transactions on Pattern Analysis and Machine Intelligence,2023
- Zhu, E., Sheng, Q., Yang, H., Liu, Y., Cai, T., & Li, J.,A Unified Framework of Medical Information Annotation and Extraction for Chinese Clinical Text,Artificial Intelligence in Medicine,2023
- Lv, J., Hu, Y., Fu, Q., Hu, Y., Lv, L., Li, J., Zhao, Y.,Local Feature Matters: Cascade Multi-scale MLP for Edge Segmentation of Medical Images,IEEE Transactions on NanoBioscience,2023
- Fan, C., Ding M., Yi, J., Li, J., & Zhao, L.,Two-stage Deep Spectrum Fusion for Noise-robust End-to-end Speech Recognition,Applied Acoustics,2023
- Zhou, F, Lu, Y., Xu, Y., Li, J., Zhang, S., Lin, Y., & Luo, Q.,Correlation between Neutrophil-to-lymphocyte Ratio and Contrast-induced Acute Kidney Injury...,Renal Failure,2023
- Tao, Y., Zhu, J., Yu, X., Cong, H., Li, J., Cai, T., & Chen, Q.,Prognostic Risk of Immune-associated Signature in the Microenvironment of Brain Gliomas,Frontiers in Genetics,2023
- Zhu, E., Liu, Y., & Li, J.*,Deep Span Representation for Named Entity Recognition,ACL 2023,2023
- Jin, M., Li, J.*,Graph to Grid: Learning Deep Representations for Multimodal Emotion Recognition,ACM MM 2023,2023
- Li, L., Zhao, G., Yu, Y., & Li, J.*,Dynamic Triple Reweighting Network for Automatic Femoral Head Necrosis Diagnosis from Computed Tomography,ACM MM 2023,2023
- Liu, Y., Li, J.*, Zhu, E.,Revisiting De-Identification of Electronic Medical Records: Evaluation of Within- and Cross-Hospital Generalization,EMNLP 2023,2023
- Zhai, P., Zhu, E., Qi, B., Wei, X., & Li, J.*,Spiral Contrastive Learning: An Efficient 3D Representation Learning Method for Unannotated CT Lesions,ISBI 2023,2023
- Sun, J., Wang, R., Zhao, G., Chen, C., Qu, Y., Li, J., Hu, X., & Yu, Y.,START: Automatic Sleep Staging with Attention-based Cross-modal Learning Transformer,IEEE BIBM 2023,2023
- Wang, X., Pan, C., Dai, H., Zhao, G., Li, J., Zhang X., & Yu, Y.,Leveraging Frequency Domain Learning in 3D Coronary Segmentation,IEEE BIBM 2023,2023
- Zhai, P., Cong, H., Zhu, E., Zhao, G., Yu Y., & Li, J.,MVCNet: Multiview Contrastive Network for Unsupervised Representation Learning for 3D CT Lesions,IEEE Transactions on Neural Networks and Learning Systems,2022
- Qi, B., Zhao, G., Wei, X., Du, C., Pan, C., Yu, Y., & Li, J.*,GREN: Graph-Regularized Embedding Network for Weakly-Supervised Disease Localization in X-ray Images,IEEE Journal of Biomedical and Health Informatics,2022
- Li, Z., Zhu, E., Jin, M., Fan, C., Cai, T., He, H., & Li., J.*,Dynamic Domain Adaptation for Class-aware Cross-subject and Cross-session EEG Emotion Recognition,IEEE Journal of Biomedical and Health Informatics,2022
- Zhu, E., Yang, H., Sheng, Qi., & Li, J.*,Boundary Smoothing for Named Entity Recognition,ACL 2022,2022
- Wei, X., Cong, H., Zhang, Z., Peng, J., Chen, G., & Li, J.*,Faint Features Tell: Automatic Vertebrae Fracture Screening Assisted by Contrastive Learning,IEEE BIBM 2022,2022
- Pan, C., Qi, B., Zhao, G., Liu, J., Fang, C., Zhang, D., & Li, J.*,Deep 3D Vessel Segmentation based on Cross Transformer Network,IEEE BIBM 2022,2022
- Lv, J., Hu, Y., Fu, Q., Zhang, Z., Hu, Y., Lv, L., Yang, G., Li, J., & Zhao, Y.,CM-MLP: Cascade Multi-scale MLP with Axial Context Relation Encoder for Edge Segmentation of Medical Image,IEEE BIBM 2022,2022
- Li, L., Cong, H., Zhao, G., Peng, J., Zhang, Z., & Li, J.*,Structure Regularized Attentive Network for Automatic Femoral Head Necrosis Diagnosis and Localization,IEEE BIBM 2022,2022
- Pan, C., Zhao, G., Fang, J., Qi, B., Liu, J., Fang, C., Zhang, D., Li., J.*, & Yu, Y.,Computer-aided Tuberculosis Diagnosis with Attribute Reasoning Assistance,MICCAI 2022,2022
- Chen, Z., Xu, T., Li, J., & He, H.,Sharing Weights in Shallow Layers via Rotation Group Equivariant Convolutions,Machine Intelligence Research,2022
- Li, J., Zhao, G., Tao, Y., Zhai, P., Chen, H., He, H., & Cai, T.,Multi-task Contrastive Learning for Automatic CT and X-ray Diagnosis of COVID-19,Pattern Recognition,2021
- Li, J., Tao, Y., & Cai, T.,Predicting Lung Cancers Using Epidemiological Data: A Generative-Discriminative Framework,IEEE-CAA Journal of Automatica Sinica,2021
- Li, J., Tao, Y., Cong, H., Zhu, E., & Cai, T.,Predicting Liver Cancers Using Skewed Epidemiological Data,Artificial Intelligence in Medicine,2021
- Chen, Z., Xu, T. B., Liao, W., Li, Z., Li, J., Liu, C. L., & He, H.,SNAP: Shaping neural architectures progressively via information density criterion,Pattern Recognition,2021
- Chen, H., Jin, M., Li, Z., Fan, C., Li, J.*, & He, H.,MS-MDA: Multisource Marginal Distribution Adaptation for Cross-subject and Cross-session EEG Emotion Recognition,Frontiers in Neuroscience,2021
- Zhao, G., Qi, B., & Li, J.*,Cross-chest Graph for Disease Diagnosis with Structural Relational Reasoning,ACM MM 2021,2021
- Qi, B., Zhao, G., Wei, X., Fang, C., Chen, Z., & Li, J.*,Weakly Supervised Disease Localization in Chest X-rays via Looking into Image Relations,IEEE BIBM 2021,2021
- Yin, W., Qi, B., Cai, T., Li, J.,X-ray Image Enhancement using Blind Denoising Neural Networks,CEEIAI 2021,2021
- Chen, H., Li, Z., Jin, M., & Li, J.*,MEERNet: Multi-source EEG-based Emotion Recognition Network for Generalization across Subjects and Sessions,IEEE EMBC 2021,2021
- Li, Z., Chen, H., Jin, M., & Li, J.*,Reducing the Calibration Effort of EEG Emotion Recognition using Transfer Learning with Soft Labels,IEEE EMBC 2021,2021
- Jin, M., Chen, H., Li, Z., & Li, J.*,EEG-based Emotion Recognition using Graph Convolutional Network with Learnable Adjacency Matrix,IEEE EMBC 2021,2021
- Fan, C., Lv, Zhao., Li, J., & Zhao, G.,Deep Attention Fusion with Joint Training Method for Robust End-to-End Speech Recognition,NCMMSC 2021,2021
- Wang, J., Cong, H., Yin, W., Qi, B., Li, J., Cai, T.,X-ray Image Blind Denoising in Hybrid Noise Based on Convolutional Neural Networks,IW-IDP 2021,2021
- Li, J., Tao, Y., Li, Z., & Cai, T.,Investigating Critical Risk Factors of Liver Cancer with Deep Neural Networks,Computer Methods in Medicine and Health Care,2021
- Chen, H., He, H., Cai, T., & Li, J.*,Enhancing EEG-based Emotion Recognition with Fast Online Instance Transfer,Integrating Artificial Intelligence and IoT for Advanced Health Informatics,2021
- Zhai, P., Tao, Y., Chen, H., Cai, T., & Li, J.*,Multi-task Learning for Lung Nodule Classification on Chest CT,IEEE Access,2020
- Xing, J., Qiu, S., Ma, X., Wu, C., Li, J., Wang, S., & He, H.,A CNN-based Comparing Network for the Detection of Steady-state Visual Evoked Potential Responses,Neurocomputing,2020
- Li, J., Chen, H., & Cai, T.,FOIT: Fast Online Instance Transfer for Improved EEG Emotion Recognition,IEEE BIBM 2020,2020
- Li, J., Qiu, S., Shen, Y. Y., Liu, C. L., & He, H.,Multisource Transfer Learning for Cross-subject EEG Emotion Recognition,IEEE Transactions on Cybernetics,2019
- Li, J., Qiu, S., Du, C., Wang, Y., & He, H.,Domain Adaptation for EEG Emotion Recognition based on Latent Representation Similarity,IEEE Transactions on Cognitive and Developmental Systems,2019
- Du, C., Li, J., Huang, L., & He, H.,Brain Encoding and Decoding in fMRI with Bidirectional Deep Generative Models,Engineering,2019
- Wang, Y., Qiu, S., Zhao, C., Yang, W., Li, J., Ma, X., & He, H.,EEG-Based Emotion Recognition with Prototype-Based Data Representation,IEEE EMBC 2019,2019
- Wang, Y., Qiu, S., Li, J., Ma, X., Liang, Z., Li, H., & He, H.,EEG-based Emotion Recognition with Similarity Learning Network,IEEE EMBC 2019,2019
- Xing, J., Qiu, S., Wu, C., Ma, X., Li, J., & He, H.,A Comparing Network for the Classification of Steady-State Visual Evoked Potential Responses,IEEE CIVEMSA 2019,2019
- Li, J., Zhang, Z., & He, H.,Hierarchical Convolutional Neural Networks for EEG-based Emotion Recognition,Cognitive Computation,2018
- Du, C., Du, C., Wang, H., Li, J., Zheng, W. L., Lu, B. L., & He, H.,Semi-supervised Deep Generative Modelling of Incomplete Multi-modality Emotional Data,ACM MM 2018,2018
- Li, J., Zhang, Z., & He, H.,Implementation of EEG Emotion Recognition System based on Hierarchical Convolutional Neural Networks,BICS 2016,2016
- Li, J., Zhang, Z., & He, H.,Visual Information Processing Mechanism Revealed by fMRI Data,ICBI 2016,2016
- Sun, Q., Li, J., Yu, H.,Predictive Functional Controller for HAWE Generators based on Neural Network,CCC 2013,2013
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