I am a Research Assistant Professor at the College of Computing and Data Science (CCDS), Nanyang Technological University (NTU), Singapore. I received my Ph.D. in Computer Science and Engineering from NTU under the supervision of Prof. Cuntai Guan.
My research vision is to build brain-aware artificial intelligence that can understand, generalize, and ultimately augment human affective and cognitive states. I work at the intersection of brain-computer interfaces (BCIs), neural signal decoding, affective computing, and deep learning, with a particular focus on EEG.
A distinctive thread across my work is the integration of neurophysiological and neuropsychological knowledge into modern learning systems. I design models around how brain activity is organized across regions, time, and cognitive processes. I combine this model-design perspective with cross-subject and cross-task generalization, foundation-model learning, and translation toward real-world mental-health and human-computer-interaction applications.
My long-term goal is to connect brain science, generalizable AI, and clinical translation: developing models that are scientifically grounded, scalable across people and tasks, and useful beyond the laboratory.
Research
Neurophysiology-inspired AI
Neural architectures that encode brain organization, functional connectivity, temporal dynamics, and cognitive priors rather than relying only on generic deep-learning structures.
Generalizable EEG Intelligence
Cross-subject, cross-dataset, and cross-task neural decoding, including EEG foundation models and transferable representations for affective and cognitive states.
Translational Brain-Computer Interfaces
Multimodal and clinically oriented BCI systems for emotion understanding, mental health, cognitive-state modeling, neurofeedback, and human-computer interaction.
Brain-Computer Interfaces Affective Computing EEG Foundation Models Neural Signal Decoding Multimodal Learning AI for Mental Health
News
25 Sep 2026
Three papers were accepted by NeurIPS 2026. Thanks to all co-authors.
12 Jul 2026
One paper was accepted by IEEE Journal of Biomedical and Health Informatics (J-BHI). Thanks to all co-authors.
9 Jul 2026
One paper was accepted by IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI). Thanks to all co-authors.
16 May 2026
One paper was accepted by SIGKDD 2026. Thanks to all co-authors.
14 May 2026
Received the Silver Reviewer Award from ICML 2026.
1 May 2026
Two papers were accepted by ICML 2026. Thanks to all co-authors.
17 Feb 2026
One paper was accepted by PAKDD 2026. Thanks to all co-authors.
28 Jan 2026
One paper was accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). Thanks to all co-authors.
26 Jan 2026
Three papers were accepted by ICLR 2026. Thanks to all co-authors.
20 Nov 2025
One paper was accepted by IEEE Journal of Biomedical and Health Informatics (J-BHI). Thanks to all co-authors.
8 Nov 2025
One paper was accepted by AAAI 2026. Thanks to all co-authors.
19 Sep 2025
One paper was accepted by NeurIPS 2025. Thanks to all co-authors.
16 Jul 2025
One paper was accepted by IEEE Signal Processing Magazine (SPM). Thanks to all co-authors.
5 Jul 2025
One paper was accepted by ACM Multimedia 2025. Thanks to all co-authors.
3 Jul 2025
One paper was accepted by Neural Networks. Thanks to all co-authors.
11 Apr 2025
One paper was accepted by IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE). Thanks to all co-authors.
8 Apr 2025
One paper was accepted by EMBC 2025. Thanks to all co-authors.
14 Mar 2025
One paper was accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS). Thanks to all co-authors.
24 Dec 2024
Appointed Research Assistant Professor at Nanyang Technological University.
21 Dec 2024
Two papers were accepted by ICASSP 2025. Thanks to all co-authors.
16 Dec 2024
One paper was accepted by IEEE Transactions on Image Processing (TIP). Thanks to all co-authors.
16 Nov 2024
Two papers were accepted by IEEE Journal of Biomedical and Health Informatics (J-BHI). Thanks to all co-authors.
12 Nov 2024
One paper was accepted by IEEE Transactions on Affective Computing (TAFFC). Thanks to all co-authors.
17 Jun 2024
One paper was accepted by Neural Networks. Thanks to all co-authors.
8 May 2024
One paper was accepted by IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE). Thanks to all co-authors.
16 Apr 2024
One paper was accepted by IEEE Journal of Biomedical and Health Informatics (J-BHI). Thanks to all co-authors.
4 Jan 2024
One paper was accepted by Neural Networks. Thanks to all co-authors.
31 Aug 2023
LGGNet received the PREMIA Best Student Paper Awards Honourable Mention 2023.
12 Apr 2023
Two papers were accepted by EMBC 2023.
11 Jan 2023
One paper was accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS).
25 Nov 2022
PCT patent application PCT/SG2022/050243, ‘Mental Arousal Level Regulation System and Method,’ was published.
19 Aug 2022
My Ph.D. thesis, ‘Neurophysiology-Inspired Neural Networks for Affective Brain-Computer Interfaces,’ was submitted and endorsed.
26 Apr 2022
One paper was accepted by IJCNN 2022.
16 Apr 2022
One paper was accepted by IEEE Transactions on Affective Computing (TAFFC).
15 Apr 2022
One paper was accepted by CVPR Workshops 2022.
15 Apr 2022
Our team was runner-up in the Valence-Arousal Estimation Challenge of the ABAW competition at CVPR 2022.
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Selected Publications
EmT: A Novel Transformer for Generalized Cross-subject EEG Emotion Recognition
Yi Ding, Chengxuan Tong, Shuailei Zhang, Muyun Jiang, Yong Li, Kevin JunLiang Lim, Cuntai Guan
IEEE TNNLS, 2025 · Highly Cited
A neurophysiology-inspired graph-transformer that models spatial interactions and long-range temporal context for generalized EEG emotion classification and regression.
EEG-Deformer: A Dense Convolutional Transformer for Brain-Computer Interfaces
Yi Ding, Yong Li, Hao Sun, Rui Liu, Chengxuan Tong, Chenyu Liu, Xinliang Zhou, Cuntai Guan
IEEE J-BHI, 2025 · Highly Cited
A dense coarse-to-fine convolutional Transformer for robust neural decoding across attention, fatigue, and mental-workload BCI tasks.
LGGNet: Learning From Local-Global-Graph Representations for Brain-Computer Interface
Yi Ding, Neethu Robinson, Chengxuan Tong, Qiuhao Zeng, Cuntai Guan
IEEE TNNLS, 2023 · Highly Cited
A neurologically inspired graph neural network that explicitly models activity within and across functional brain regions for EEG decoding.
TSception: Capturing Temporal Dynamics and Spatial Asymmetry from EEG for Emotion Recognition
Yi Ding, Neethu Robinson, Su Zhang, Qiuhao Zeng, Cuntai Guan
IEEE TAFFC, 2022 · Highly Cited
A multi-scale CNN that captures EEG temporal dynamics and hemispheric spatial asymmetry for affective brain-computer interfaces.
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Academic Profile
I have authored or co-authored 40+ peer-reviewed papers in venues including IEEE TPAMI, IEEE TNNLS, IEEE TIP, IEEE TAFFC, IEEE J-BHI, IEEE Signal Processing Magazine, ICLR, ICML, NeurIPS, KDD, AAAI, and ACM Multimedia. My work spans foundational EEG representation learning, affective BCIs, multimodal emotion modeling, and translation of neural-decoding methods toward healthcare applications.
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For research collaboration, student supervision, or academic enquiries, please contact me at ding.yi@ntu.edu.sg.
