Biography

I am currently an associate professor (PhD supervisor) in the College of Computer Science at Beijing University of Technology (BJUT). IEEE Senior Member and CCF Senior Member. I obtained my Ph.D. in Computer Science from Beijing University of Technology in June 2020. My research interests are in the general areas of machine learning, data mining and brain science, with a current focus on developing novel techniques to learn the brain effective connectivity networks from neuroimaging data.

Openings: I am looking for motivated students (including PhDs and masters) working in data mining and machine learning. If you are interested in joining my group, please send me your CV. (拟招生2027年秋季入学博士1名，硕士2名)

News: Won the Best Student Paper Awards Research Runner Up at KDD 2025! (top 6 of total 2955 submissions)

Selected Publications as First or Corresponding Author

“*” Indicates the corresponding author, and “_” indicates that the first author is a student under my supervision.

2026

• [ACM MM 2026] Xinyi Huang, Pengrui Xiang, Jie Wang, Xuchen Zhai, Jinduo Liu*, Honggui Han. EviGuard: Evidence-Guided Connector Intervention for Cross-Modal Safety Unlearning in Multimodal LLMs. The 34th ACM International Conference on Multimedia, 2026. (CCF A)
• [IJCAI 2026] Zhihao Su, Junzhong Ji, Minqi Yu, Jinduo Liu*. STCBN-EC: A Spatio-Temporal Constrained Bayesian Causal Network for Multimodal Brain Effective Connectivity Learning. The 35th International Joint Conference on Artificial Intelligence, 2026. (CCF A-B)
• [IJCAI 2026] Xinyi Huang, Jie Wang, Pengrui Xiang, Yifan Wang, Yu Fu, Jinduo Liu*. BEACON: Budget-Efficient Discovery of Policy Violations in Large Language Models via Cognitive-Guided Monte Carlo Tree Search. The 35th International Joint Conference on Artificial Intelligence, 2026. (CCF A-B)
• [IEEE TAI] Jinduo Liu, Ting Wang, Yilin Lu, Junzhong Ji. CTRL: Cross-modal Transformer with Reinforcement Learning for Climate Causal Discovery. IEEE Transactions on Artificial Intelligence, 2026.
• [ASOC] Jinke Wu, Jinduo Liu*. MetaAN: A Meta-Learned Aligned Network for Cross-Subject Emotion Recognition Based on Electroencephalogram Signals. Applied Soft Computing, 2026.
• [EAAI] Junzhong Ji, Muran Zhu, Jinduo Liu*. CellRa: A Region-aware Method for Cell Segmentation. Engineering Applications of Artificial Intelligence, 160, 111877, 2026.
• [ICIC 2026] Pengrui Xiang, Xinyi Huang, Kunyi Zhou, Bokai Cheng, Jinduo Liu *, Honggui Han *. BRACE: A Benign-history Robust Anchored Calibration and Evaluation Framework for Large Language Model Refusal. 2026 International Conference on Intelligent Computing, 2026. (CCF C, Oral)

2025

• [KDD 2025] Wen Xiong, Jinduo Liu*, Junzhong Ji, Fenglong Ma. Brain Effective Connectivity Estimation via Fourier Spatiotemporal Attention. The 31st SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-25), 1657-1668, 2025. (Best Student Paper Award Research Runner Up, CCF A, Acceptance rate=19%)
• [NeurIPS 2025] Wen Xiong, Junzhong Ji, Jinduo Liu*. BrainEC-LLM: Brain Effective Connectivity Estimation by Multiscale Mixing LLM. The Thirty-ninth Annual Conference on Neural Information Processing Systems (NeurIPS-25), 38, 123110-123143, 2025. (CCF A, Acceptance rate=24.5%)
• [ICML 2025] Minqi Yu, Jinduo Liu*, Junzhong Ji. Causal Invariance-aware Augmentation for Brain Graph Contrastive Learning. The Forty-second International Conference on Machine Learning (ICML-25), 73221-73240, 2025. (CCF A, Acceptance rate=26.9%)
• [IJCAI 2025] Jihao Zhai, Junzhong Ji, Jinduo Liu*. Inferring Causal Protein Signaling Networks with Reinforcement Learning via Artificial Bee Colony Neural Architecture Search. The 34th International Joint Conference on Artificial Intelligence (IJCAI-25), 8996-9004, 2025. (CCF A, Acceptance rate=19%)
• [MICCAI 2025] Zhihao Su, Jihao Zhai, Junzhong Ji, Jinduo Liu*. MSGFlowNet: Learning Effective Connectivity Network based on Sparse Generative Flow Network from fMRI and EEG Data. Medical Image Computing and Computer Assisted Intervention 2025 (MICCAI-25), 418-428, 2025. (CCF B, Regular Paper Acceptance rate=29%)
• [BIBM 2025] Jialin Song, Jiarui Wang, Hanrui Jiang, Jinduo Liu*. A Spatio‑Temporal Expert Fusion Framework Integrating Mamba and KAN for EEG Emotion Recognition. IEEE International Conference on Bioinformatics and Biomedicine (BIBM-25), 2798-2803, 2025. (CCF B, Regular Paper Acceptance rate=19.6%)
• [JCST] Muran Zhu, Jinduo Liu*, Junzhong Ji. Electrocardiogram Signal Classification Based on Bidirectional LSTM and Multi-Task Temporal Attention. Journal of Computer Science and Technology, 40(5): 1401-1413, 2025. (CCF B)
• [EAAI] Minqi Yu, Jinduo Liu*, Junzhong Ji. Multi-atlas Functional and Effective Connectivity Attention Fusion Method for Autism Spectrum Disorder Diagnosis. Engineering Applications of Artificial Intelligence, 160, 111877, 2025.
• [KBS] Junzhong Ji, Jingdong Fan, Jinduo Liu*. MsAD-LEC: Estimating Large-scale Brain Effective Connectivity Network based on Multi-subgraph Attention Diffusion. Knowledge-Based Systems, 309, 112858, 2025.

2024

• [AAAI 2024] Zuozhen Zhang, Junzhong Ji, Jinduo Liu*. MetaRLEC: Meta-Reinforcement Learning for Discovery of Brain Effective Connectivity. The 38th AAAI Conference on Artificial Intelligence (AAAI-24), 38 (9), 10261-10269, 2024. (CCF A, Acceptance rate=20.6%)
• [IJCAI 2024] Jinduo Liu, Feipeng Wang, Junzhong Ji. Concept-Level Causal Explanation Method for Brain Function Network Classification. The 33rd International Joint Conference on Artificial Intelligence (IJCAI-24), 3087–3096, 2024. (CCF A, Acceptance rate=14%)
• [IEEE TMI] Jinduo Liu, Lu Han, Junzhong Ji. MCAN: Multimodal Causal Adversarial Networks for Dynamic Effective Connectivity Learning from fMRI and EEG Data. IEEE Transactions on Medical Imaging, 43 (8), 2913-2923, 2024.
• [CAAI TRIT] Jinduo Liu, Jihao Zhai, Junzhong Ji. Inferring Causal Protein Signaling Networks from Single-cell Data based on Parallel Discrete Artificial Bee Colony Algorithm. CAAI Transactions on Intelligence Technology, 9(6), 1587–1604, 2024.
• [IEEE TSIPN] Junzhong Ji, Feipeng Wang, Lu Han, Jinduo Liu*. Causal Learning and Knowledge Fusion Mechanism for Brain Functional Network Classification. IEEE Transactions on Signal and Information Processing over Networks, 10, 650-664, 2024.
• [IEEE TNSRE] Han Lv, Jinduo Liu*, Qian Chen, Junzhong Ji, Jihao Zhai, Zuozhen Zhang, Zhaodi Wang, Shusheng Gong, Zhenchang Wang. Brain network evaluation by functional-guided effective connectivity reinforcement learning method indicates therapeutic effect for tinnitus. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 32, 1132-1141, 2024.
• [IEEE TIM] Junzhong Ji, Lu Han, Feipeng Wang, Jinduo Liu*. Dynamic Effective Connectivity Learning based on non-Parametric State Estimation and GAN. IEEE Transactions on Instrumentation and Measurement, 73, 1-12, 2024.
• [CIBM] Junzhong Ji, Zuozhen Zhang, Lu Han, Jinduo Liu*. MetaCAE: Causal Autoencoder with Meta-Knowledge Transfer for Brain Effective Connectivity Estimation. Computers in Biology and Medicine, 170, 107940, 2024.
• [APIN] Junzhong Ji, Ting Wang, Jinduo Liu*, Muhua Wang, Wei Tang. River Runoff Causal Discovery with Deep Reinforcement Learning. Applied Intelligence, 1-19, 2024.

2023

• [IEEE MEDAI] Muran Zhu, Xiaotong Huo, Zuozhen Zhang, Jinduo Liu*, Junzhong Ji *. “Arrhythmia Detection from Electrocardiogram Signal Data based on Wavelet Transform and Deep Reinforcement Learning”. IEEE International Conference on Medical Artificial Intelligence, 325-333, 2023. (Best Student Paper Runner-Up)
• [IEEE TNSRE] Han Lv#, Jinduo Liu#, Qian Chen, Zuozhen Zhang, Zhaodi Wang, Shusheng Gong, Junzhong Ji and Zhenchang Wang. “Brain effective connectivity analysis facilitates the treatment outcome expectation of sound therapy in patients with tinnitus”. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 31, 1158-1166, 2023.
• [Bioengineering] Jihao Zhai, Junzhong Ji, Jinduo Liu*. “Learning Causal Biological Networks with Parallel Ant Colony Optimization Algorithm”. Bioengineering, 10 (8), 909, 2023.
• [Brain Sciences] Zuozhen Zhang, Ziqi Zhang, Junzhong Ji, Jinduo Liu*. “Amortization Transformer for Brain Effective Connectivity Estimation from fMRI Data”. Brain sciences, 13 (7), 995, 2023.
• [CAC 2023] Wenxin Zou, Junzhong Ji, Yutong Wang, Jiayi Wang, Yutong Qian, Jinduo Liu*. “Convolutional LSTM with Self-Attention Mechanism for Extreme Weather Prediction”. China Automation Congress (CAC), 6782-6787, 2023.

2016-2022

• [IEEE TNNLS] Jinduo Liu, Junzhong Ji, Guangxu Xun and Aidong Zhang. “Inferring Effective Connectivity Networks from fMRI Time Series with a Temporal Entropy-score”. IEEE Transactions on Neural Networks and Learning Systems, 33(10), 5993-6006, 2022.
• [IEEE BIBM] Yilin Lu, Jinduo Liu*, Junzhong Ji, Han Lv, Mengdi Huai. “Brain Effective Connectivity Learning with Deep Reinforcement Learning”. 2022 IEEE International Conference on Bioinformatics and Biomedicine, 2022.
• [AAAI 2022] Mengdi Huai, Jinduo Liu, Chenglin Miao, Liuyi Yao and Aidong Zhang. “Towards automating model explanations with certified robustness guarantees”. Proceedings of the AAAI Conference on Artificial Intelligence, 36(6), 6935-6943, 2022.
• [IEEE TMI] Junzhong Ji*, Jinduo Liu*, Lu Han and Feipeng Wan. “Estimating effective connectivity by recurrent generative adversarial networks”. IEEE Transactions on Medical Imaging, 40(12), 3326-3336, 2021.
• [AAAI 2020] Jinduo Liu, Junzhong Ji, Guangxu Xun, Liuyi Yao, Mengdi Huai and Aidong Zhang. “EC-GAN: inferring brain effective connectivity via generative adversarial networks”. The 34th AAAI Conference on Artificial Intelligence (AAAI-20), 34(4), 4852-4859, 2020.
• [IEEE JBHI] Jinduo Liu, Junzhong Ji, Xiuqin Jia and Aidong Zhang. “Learning brain effective connectivity network structure using ant colony optimization combining with voxel activation information”. IEEE journal of biomedical and health informatics, 24(7), 2028-2040, 2020.
• [IEEE BIBM] Jinduo Liu, Junzhong Ji, Liuyi Yao and Aidong Zhang. “Estimating brain effective connectivity in fMRI data by non-stationary dynamic Bayesian networks”. 2019 IEEE International Conference on Bioinformatics and Biomedicine, 834-839, 2019.
• [IEEE BIBM] Jinduo Liu, Junzhong Ji, Aidong Zhang and Peipeng Liang. “An ant colony optimization algorithm for learning brain effective connectivity network from fMRI data”. 2016 IEEE International Conference on Bioinformatics and Biomedicine, 360-367, 2016.

Group

Master's student（硕士研究生）:
2022: Jihai Zhai (IJCAI 2025, CAAI TRIT 2024, Bioeng 2023, 国家奖学金，校优秀硕士论文)
2023: Wen Xiong (KDD 2025最佳论文, NeurIPS 2025, 国家奖学金, 小米特等奖学金, 北京市优秀毕业生, 北工大百佳毕业生，校优秀硕士论文), 
      Minqi Yu (ICML 2025, EAAI 2025, 国家奖学金, 小米奖学金, 北京市优秀毕业生, 北工大百佳毕业生，校优秀硕士论文)
2024: Zhihao Su (MICCAI 2025, IJCAI 2026), 
      Yilin Lu (IEEE TAI 2025)
      
Undergraduate student (本科生):
2021: Jinke Wu (ASOC 2026, 国家奖学金)
2023: Xinyi Huang (ACM MM 2026, IJCAI 2026, ICIC 2026),
      Yifan Wang (国创项目)
2024: Jialin Song (BIBM 2025, 北京市自然科学基金本科生启研计划, 国创项目),
      Jiatian Cao (北京市自然科学基金本科生启研计划)

Contact

Our group is looking for highly motivated PhD and Master students with strong mathematical or programming background [中文招生主页链接].
E-mail: Jinduo AT bjut DOT edu DOT cn