1. Educational Background (in reverse chronological order)：

• 2016-2020: South China University of Technology, Mechanical Engineering and Automation, Doctoral Degree (Full-time)
• 2016-2020: South China University of Technology, Mechanical Engineering and Automation, Bachelor Degree (Full-time)

2. Work Experience (in reverse chronological order)：

• 2015-Present: School of Intelligence Science and Engineering, Harbin Institute of Technology, Shenzhen, Professor
• 2020-2025: Department of Electrical and Computer Engineering, National University of Singapore, Research fellow

Cai Siqi, PhD, is a Professor and qualified Ph.D. Supervisor at the School of Intelligence Science and Engineering, College of Artificial Intelligence, Harbin Institute of Technology, Shenzhen. From 2020 to 2024, Dr. Cai was a Research Fellow at the National University of Singapore (NUS), where she was technical lead in Human-Robot Collaborative AI and Neuromorphic Computing research projects. Dr Cai’s research interests include brain-computer interface and human-robot interaction as reflected in her scientific publications and invention patents. She has played leadership roles in several international conferences and professional associations, that include Workshop Chair and Local Chair (China) in IEEE 2022 International Conference on Acoustics, Speech, & Signal Processing (ICASSP), and Entrepreneurship Forum Co-Chair of IEEE 2024 ICASSP. She is a Council Member of the Chinese and Oriental Languages Information Processing Society (COLIPS, Singapore). Dr Cai currently serves as an Associate Editor of International Journal of Social Robotics and Lead Guest Editor of Neural Networks. She is a Senior Member of IEEE. Dr. Cai is also a recipient of the NSFC Excellent Young Scientists Fund (Overseas).

[1] Cai S, Li P, Li H. A Bio-Inspired Spiking Attentional Neural Network for Attentional Selection in the Listening Brain. IEEE Transactions on Neural Networks and Learning Systems, 2023 (SCI Q1, DOI: 10.1109/TNNLS.2023.3303308)

[2] Su E, Cai S, et al. STAnet: A Spatiotemporal Attention Network for Decoding Auditory Spatial Attention from EEG. IEEE Transactions on Biomedical Engineering, 2022 (SCI Q2, DOI: 10.1109/TBME.2022.3140246)

[3] Cai S, Su E, et al. EEG-based auditory attention detection via frequency and channel neural attention. IEEE Transactions on Human-Machine Systems, 2021, 52(2): 256-266 (SCI二区, DOI: )

[4] Cai S, Schultz T, Li H. Brain Topology Modeling With EEG-Graphs for Auditory Spatial Attention Detection. IEEE Transactions on Biomedical Engineering, 2023 (SCI Q2, DOI: 10.1109/TBME.2023.3294242)

[5] Fathi F, Cai S, Mousavi A A. A neuroscience-inspired spiking neural network for EEG-based auditory spatial attention detection. Neural Networks, 2022, 152: 555-565 (SCI Q2, DOI: 10.1016/j.neunet.2022.05.003)

[6] Pan Z, Borsdorf M, Cai S*, et al. NeuroHeed: Neuro-steered speaker extraction using EEG signals. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2024 (SCI Q2)

[7] He T, Wei M, Cai S*, et al. VocalMind: A Stereotactic EEG Dataset for Vocalized, Mimed, and Imagined Speech in Tonal Language. Scientific Data, 2025, 12(1): 657 (SCI Q2)

[8] Cai S, Zhang R, Zhu H, et al. Modeling the temporal dynamics of eeg signals in selective listening. IEEE Transactions on Consumer Electronics, 2025 (SCI Q2)

[9] Zhang X, Zhu P, Cai S*, et al. TrustCLIP: Learning from Noisy Labels via Semantic Label Verification and Trust-aligned Gradient Projection. Proceedings of the 33rd ACM International Conference on Multimedia, 2025: 4388-4397 (CCF-A)

[10] Cai S, Lin Z, Liu X, et al. Spiking neural networks for EEG signal analysis: From theory to practice. Neural Networks, 2025: 108127 (SCI Q2)