I am Chen, and I received my Ph.D. from the joint doctoral program between the University of Birmingham and Southern University of Science and Technology. During my doctoral studies, my research focused on modeling individual psychological representations and behavioral interventions. By integrating generative artificial intelligence with active experimental design, I investigated and characterized individual differences in perception, memory, decision-making, and emotion, and explored the computational mechanisms underlying behavioral change.

More recently, my work has expanded toward self-evolving human–AI interaction systems. These systems learn by autonomously designing their own interactive environments and leverage large language models to construct psychological world models. In this process, I incorporate multimodal neural and behavioral feedback to replace traditional language-based human feedback, enabling the model to more directly capture latent cognitive and affective states. By combining active experiment design with multi-agent interaction environments to simulate complex social scenarios, I aim to achieve a deeper understanding of the human mind and to advance AI systems capable of supporting decision-making and behavioral intervention in everyday contexts.

I am currently founding 全域智能 (Omni-intelligence), a BCI foundation model company. If you are interested in academic collaboration, industry partnerships, or have relevant opportunities in AI and cognitive sciences, please feel free to contact me at chen.wei.hdg@gmail.com.

I graduated from Southwestern University of Finance and Economics with a bachelor’s degree in Finance, and I received my Ph.D. in Psychology from the joint doctoral program between University of Birmingham and Southern University of Science and Technology (SUSTech), co-advised by Prof. Dietmar Heinke and Prof. Quanying Liu. I have published 20+ first-/corresponding-author papers in top-tier conferences and journals, such as Nature Biomedical Engineering, NeurIPS, ICML, ICLR, IJCAI, ACMMM, CogSci, The Innovation and iScience, with over 593 citations and an H-index of 8. I serve as a reviewer for leading venues like NeurIPS, ICLR, ICML, AISTATS, CogSci and serve as a guest editor for Tsinghua Science and Technology on a special issue on foundation models in brain science.

📚 Publications

* denotes equal contribution; $^{\dagger}$ denotes co-corresponding authorship.

🧠 Capturing Mental Representations through Behaviour

• Jiachen Zou, Chen Wei, Quanying Liu, M Robinson.
  Using AI-generated real-world objects to uncover the structure of visual memory, Journal of Vision, 2025
• Yuang Cao*, Jiachen Zou*, Chen Wei$^{\dagger}$, Quanying Liu$^{\dagger}$.
  Dimensions of Vulnerability in Visual Working Memory: An AI-Driven Approach to Perceptual Comparison, CogSci, 2025
• Chen Wei*, Jiachen Zou*, Dietmar Heinke, Quanying Liu.
  CoCoG-2: Controllable generation of visual stimuli for understanding human concept representation, IJCAI-HBAI Workshop, 2024
• Chen Wei*, Jiachen Zou*, Dietmar Heinke, Quanying Liu.
  CoCoG: Controllable Visual Stimuli Generation based on Human Concept Representations, IJCAI, 2024

👥 Individual Variability of Mental Representations

• Haotian Deng, Sitian Wang, Ruxin Wang, Chen Wei$^{\dagger}$, Quanying Liu$^{\dagger}$.
  When Proxy Agents Disagree, Do Humans Mirror? Manipulating Human Behavior in Moral Dilemmas through Agents, AAAI Artificial Intelligence for Social Impact Track, 2026
• Chi Zhang*, Yulang Gao*, Jiachen Zou, Chen Wei$^{\dagger}$, Quanying Liu$^{\dagger}$.
  When Agents Steer Human Perception: How AI-Selected Images Can Covertly Alter Judgment Disagreements, Under Review at CVPR, 2026
• Haotian Deng, Sitian Wang, Ruxin Wang, Chen Wei$^{\dagger}$, Quanying Liu$^{\dagger}$.
  When LLM Agents Disagree, Do Humans Mirror? Behavioral Comparisons on Moral Dilemmas, MIND (Oral, Best Paper Finalist), 2025
• Chen Wei*, Chi Zhang*, Jiachen Zou, Haotian Deng, Dietmar Heinke, Quanying Liu.
  Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering and Manipulating Human Perceptual Variability, ICML, 2025
• Haotian Deng, Chi Zhang, Chen Wei$^{\dagger}$, Quanying Liu$^{\dagger}$.
  Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions, IJCNN (Oral), 2025

👁️ Neural Visual Decoding & Closed-Loop Control

• Dongyang Li, Kunpeng Xie, Mingyang Wu, Yiwei Kong, Jiahua Tang, Haoyang Qin, Chen Wei$^{\dagger}$, Quanying Liu$^{\dagger}$.
  MindPilot: Closed-loop Visual Stimulation Optimization for Brain Modulation with EEG-guided Diffusion, Under Review at ICLR, 2026
• Dongyang Li, Haoyang Qin, Mingyang Wu, Chen Wei$^{\dagger}$, Quanying Liu$^{\dagger}$.
  BrainFLORA: Uncovering Brain Concept Representation via Multimodal Neural Embeddings, ACMMM (Oral), 2025
• Dongyang Li, Haoyang Qin, Mingyang Wu, Jiahua Tang, Chen Wei$^{\dagger}$, Quanying Liu$^{\dagger}$.
  RealMind: Advancing Visual Decoding and Language Interaction via EEG Signals, ICME, 2025
• Jiahua Tang, Song Wang, Jiachen Zou, Chen Wei$^{\dagger}$, Quanying Liu$^{\dagger}$.
  Uncovering the EEG Temporal Representation of Low-dimensional Object Properties, IJCNN (Oral), 2025
• Dongyang Li*, Chen Wei*, Shiying Li, Jiachen Zou, Quanying Liu.
  Visual Decoding and Reconstruction via EEG Embeddings with Guided Diffusion, NeurIPS, 2024

🤖 AI for Psychology

• Chen Wei, Jiachen Zou, Chi Zhang, Jia Liu, Haiyan Wu, Quanying Liu.
  AI-Driven Novel Paradigms for Psychological Research, Under Review at Advances in Psychological Science, 2025
• Youzhi Qu, Penghui Du, Wenxin Che, Chen Wei, Quanying Liu, et al.
  Promoting interactions between cognitive science and large language models, The Innovation, 2024
• Youzhi Qu*, Chen Wei*, Penghui Du, Wenxin Che, Chi Zhang, Wanli Ouyang, Yatao Bian, Feiyang Xu, Bin Hu, Kai Du, et al.
  Integration of cognitive tasks into artificial general intelligence test for large models, iScience, 2024

🧮 Theoretical AI-Brain Alignment & Generalization

• Junjie Yu, Wenxiao Ma, Chen Wei, Jianyu Zhang, Haotian Deng, Zihan Deng, Yi Guo, Quanying Liu.
  Scale-Invariance in AI Representation Predicts AI-Brain Alignment, Under Review at ICLR, 2026
• Junjie Yu, Zhuoli Ouyang, Haotian Deng, Chen Wei, Wenxiao Ma, Jianyu Zhang, Zihan Deng, Yi Guo, Quanying Liu.
  Generalization Error Bound via Embedding Dimension and Network Lipschitz Constant, Under Review at ICLR, 2026

📈 EEG Signal Processing & Inverse Problem

• Song Wang*, Kexin Lou*, Chen Wei*, Zhiyuan Sheng, Jiahao Tang, Kaining Peng, Shuhao Mei, Liang Chen, Dongfeng Gu, Quanying Liu.
  Reconstructing whole-brain spatiotemporal dynamics using EEG/MEG Source Imaging with Geometric Constraints, Nature Biomedical Engineering, Accepted, 2025
• Song Wang, Chen Wei, Kexin Lou, Dongfeng Gu, Quanying Liu.
  Advancing EEG/MEG Source Imaging with Geometric-Informed Basis Functions, EMBC, 2024
• Junjie Yu, Chenyi Li, Kexin Lou, Chen Wei, Quanying Liu.
  Embedding decomposition for artifacts removal in EEG signals, Journal of Neural Engineering, 2022
• Haoming Zhang*, Mingqi Zhao*, Chen Wei, Dante Mantini, Zherui Li, Quanying Liu.
  EEGdenoiseNet: A benchmark dataset for deep learning solutions of EEG denoising, Journal of Neural Engineering, 2021
• Chen Wei*, Kexin Lou*, Zhengyang Wang, Mingqi Zhao, Dante Mantini, Quanying Liu.
  Edge Sparse Basis Network: A Deep Learning Framework for EEG Source Localization, IJCNN (Oral), 2021
• Haoming Zhang*, Chen Wei*, Mingqi Zhao, Quanying Liu, Haiyan Wu.
  A novel convolutional neural network model to remove muscle artifacts from EEG, ICASSP, 2021

📚 Books

• Quanying Liu, Youzhi Qu, Chen Wei, Zhichao Liang.
  Human Brain Intelligence and Artificial Intelligence. Tsinghua University Press, 2025.

• Quanying Liu, Chen Wei, Youzhi Qu, Zhichao Liang.
  Modelling and Controlling System Dynamics of the Brain: An Intersection of Machine Learning and Control Theory, in Systems Neuroscience, Springer Nature, 2024

🧑‍🏫 Teaching Experience

• 2023: Teaching Assistant, Machine Learning and Medical Engineering Applications, SUSTech, Shenzhen (Instructor: Prof. Quanying Liu)
• 2023: Teaching Assistant, Brain Intelligence and Artificial Intelligence, SUSTech, Shenzhen (Instructor: Prof. Quanying Liu)
• 2023: Teaching Assistant, Brain Signal Analysis and Feature Extraction Tutorial (Deep Learning & AI Applications), Institute of Psychology, CAS, Beijing (Instructor: Prof. Quanying Liu)

🎖 Honors & Awards

• 2024: IOP Top Cited Paper Award
• 2024: IOP Trusted Reviewer
• 2024: Best Paper Award – IJCAI Workshop on Human Brain and Artificial Intelligence
• 2023: Poster Excellence Award – BME Research Day, SUSTech
• 2020: 1st Prize – Guangdong Academic Forum, Biomedical Engineering Brain Science Symposium

🎤 Invited Talks

• 2024.12: Max Planck Institute and Justus Liebig University Giessen — Understanding and Manipulating Human Perception by Generating Visual Stimuli (Invited by Martin Hebart)
• 2024.08: IJCAI — CoCoG: Controllable Visual Stimuli Generation Based on Human Concept Representations
• 2024.08: IJCAI Workshop on Human Brain and Artificial Intelligence — CoCoG-2: Controllable Generation of Visual Stimuli for Understanding Human Concept Representation
• 2024.06: AI4Psych Seminar — Using Visual Generation Models to Enhance Psychological Experimental Design
• 2024.05: Tsinghua University — Controllable Visual Stimuli Generation Based on Human Concept Representations (Invited by Dan Zhang)
• 2021.05: IJCNN — Edge Sparse Basis Network: A Deep Learning Framework for EEG Source Localization

🎓 Education

• Ph.D. in Psychology (2021–2025)
  University of Birmingham / Southern University of Science and Technology
  Supervisors: Prof. Dietmar Heinke, Prof. Quanying Liu

• B.S. in Finance (2014–2018)
  Southwestern University of Finance and Economics

💼 Work Experience

• Founder (2025–present)
  全域智能 (Omni-intelligence) — BCI Foundation Model Company

• Research Assistant (2019–2021)
  Southern University of Science and Technology, China
  Supervisor: Prof. Quanying Liu

🔧 Service

• Editorial Roles: Guest Editor, Special Issue on “Foundation Models for Brain Science”, Tsinghua Science and Technology, 2025
• Conference Reviewer: NeurIPS, ICML, ICLR, AISTATS, AAAI, CogSci, ACMMM, IJCNN, AAAI Artificial Intelligence for Social Impact Track, IJCAI Workshop on Human Brain and Artificial Intelligence
• Journal Reviewer: Neuroscience, Machine Learning: Science and Technology, Journal of Neural Engineering, Biomedical Physics & Engineering Express
• Membership: Associate Member, Institute of Physics (IOP); Member, IEEE

🌟 Other Experience

• 2019: Translator of Chinese edition of Computational Modeling of Cognition and Behavior (Farrell & Lewandowsky, Cambridge University Press, 2018)
• 2024.07: Initiator & Lecturer: Delivered 8 youth-focused AI science lectures, Shenzhen Science Museum (July 2024), 3,000+ audience

Updated: Aug 2025