About me
Aiming to design Trustworthy & Efficient AI Models by studying neural network through brain, computer, math and physics, while actively pursuing innovations in next-generation AI paradigms, to enhance human intelligence, improve AI, and connect AI with the brain.
- 🪧Seeking a Postdoc Position: Generative AI & AI Efficiency & Mechanism Explainability. I believe my interdisciplinary background in 1) computer science, 2) artificial intelligence, and 3) cognitive neuroscience can bring valuable contributions to your team. If you are interested in my experience, please feel free to contact me.
- 🧠Ph.D., 2022~Now, majored in Cognitive Neuroscience. State Key Laboratory of Cognitive Neuroscience and Learning (IDG/McGovern Institute for Brain Research) at Beijing Normal University. Advised by Prof. Jing Sui & Prof. Vince D. Calhoun (TReNDS: Translational Research in Neuroimaging and Data Science). Research on AI♻️Brain.
- 👨⚕️M.E., 2019~2022, majored in Software Engineering. Advised by Prof. Zhongyu li & Dr.Bin Kong. Research on Deep Learning. 🤖B.E., 2014~2018, majored in Software Engineering. Research on Embedded Software & Robot.
Interests | Education |
🎯Generative AI 🧠Brain-inspired AI 🌍Foundation Model 📈Continual Learning | 🎓Ph.D. in Beijing Normal University, 2022-Present State Key Laboratory of Cognitive Neuroscience and Learning 🎓M.E. in Xi’an JiaoTong University, 2019-2022 Faculty of Electronic and Information Engineering |
I am dedicated to designing intelligent computing models, focusing on developing meta-methods for reasoning, learning, security, and efficiency. My interests span Multimodal AI, Physics AI, AI Social Simulation, AI Games, Continual Learning, Reinforcement Learning, Twin Brains, Neuro-symbolic AI, Neural Decoding, Neural Coding and Robotics. If you are interested in any of these topics, please feel free to contact me. I am open to cooperation.
Activities
- 🙇♂️Working on my Ph.D thesis.
- 🧪Studing on LLM & Diffusion model.
- 🧪Coding about Multi-modal classification of psychiatric disorders.
News
- 🎉 2025/01 A patent (No. 202410125896.X) for the application of artificial intelligence in radiotherapy.
- 🎉 2024/08 In collaboration with the Department of Oncology and Radiology of Peking University Third Hospital and other hospitals, we submitted a journal paper to the Medical physics 2024 (JCR Q1, Top 3 Medical Physics journals), Accepted.
- 🎉 2024/04 A paper about eliminating site effects will be submitted to EMBC 2024, CAAI B, Accepted.
- 🎉 2023/12 An abstract of neuroimage classification was submitted to OHBM2024, Poster presentation.
- 🎉 2023/10 Join in the National key research and development program.
Selected Publications
# Equal contributions
- For a complete list (including works under review), please contact me via email.
Model Design
- Xueying Yang#, Xiangxiang Cui#, et al. “Uncertainty quantification-guided patient-specific quality assurance using Bayesian neural networks based on field complexity features and fluence maps”. In Physics in Medicine and Biology 2025 (JCR Q1), Status: Major Revisions
- Xiangxiang Cui#, Xueying Yang#, et al. “A StarGAN and Transformer-Based Hybrid Classification-Regression Model for Multi-institution VMAT Patient-Specific Quality Assurance.” In Medical Physics 2024 (JCR Q1, Top 3 Medical Physics journals). [GAN|Site effect]
- Xiangxiang Cui, Dongmei Zhi, Weizheng Yan, et al. “CGDM-GAN: An Adversarial Network Approach with Self-supervised Learning for Site Effect Removal. “ In EMBC 2024, CAAI B. [GAN|Self-supervised learning|Site effect]
- Xiangxiang Cui, et al. “Multi-Scale Analysis Framework Integrating Brain Functional Connectivity and Activity” In the Annual Meeting of the organization for Human Brain Mapping (OHBM) 2024. [Classification|NeuroAI]
- Xiangxiang Cui, et al. “CGDM-GAN: An Adversarial Network Approach with Self-Supervised for Removing Site Effects” In the Annual Meeting of the organization for Human Brain Mapping (OHBM) 2023. [Classification|Site effect]
- Xiangxiang Cui, et al. “Variable-frame CNNLSTM for Breast Nodule Classification using Ultrasound Videos” Preprint 2023. [Videos classification]
- Yichen Wang, Zhongyu Li, Xiangxiang Cui, et al. “Key-frame Guided Network for Thyroid Nodule Recognition using Ultrasound Videos” In MICCAI 2022. [Videos classification]
- Xiangxiang Cui, et al. “DEAttack: A differential evolution based attack method for the robustness evaluation of medical image segmentation.” In Neurocomputing 2021, IF:5.779. [Model robustness|Segmentation|Adversarial attack]
Model Explainability
- Multimodal
- Cognitive Coding
Engineering experiences
![]() | Slurm Cluster Management(Centos)
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![]() | Multi-User Server Management(Ubuntu)
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![]() | Dance Robot
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![]() | Web Online Compiler
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![]() | The Embedded Car
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![]() | Union Search
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![]() | Algorithm Greedy Snakes Game
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![]() | Compus Today Android APP
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![]() | Electronic Labeling Systems
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Services
Conference Reviewers: ICLR2025