持续招收2026级硕士、博士研究生，欢迎邮件联系
戚世乐，南京航空航天大学，人工智能学院，教授，博士生导师，脑机智能技术教育部重点实验室副主任，国家级青年人才，江苏省特聘教授，南航长空学者。
2018年博士毕业于中国科学院自动化研究所，模式识别国家重点实验室，脑网络组研究中心；2018—2021年先后在美国知名神经影像研究所The Mind Research Network (MRN)和The Center for Translational Research in Neuroimaging and Data Science (TReNDS)任职博士后。
主要研究方向：多模态大数据融合分析、脑影像—基因组学、个体差异建模、脑疾病病理机制等。已发表学术论文70余篇，包括以第一/通讯作者发表在综合性顶级期刊Nature Communications（2篇）、神经科学顶级期刊Brain、精神疾病学顶级期刊Biological Psychiatry、BMC Medicine、Schizophrenia Bulletin（2篇）、Translational Psychiatry（2篇）、Molecular Autism等和医学影像方法学顶级期刊IEEE TIP、IEEE SPM、IEEE TMI、Human Brain Mapping（5篇）等。研究成果获得教育部自然科学二等奖（2025，3/5），获得国际脑图谱大会OHBM最佳论文奖4次(2017/2020/2021/2025，top1%)。
主持国家级和省部级人才项目、国自然面上、江苏省重点研发计划子课题、江苏省青年基金、南航人才启动专项基金、中央高校基础科研基金。任中国图象图形学会CSIG脑图谱专委会、医学图像计算MICS专委会、江苏省人工智能学会医学图像处理专委会的青年委员。担任期刊PLOS Mental Health, Journal of Clinical and Basic Psychosomatics编委。
5篇代表作: (全部论文可google scholar检索: https://scholar.google.com/citations?hl=en&user=-QPgz1IAAAAJ&view_op=list_works)
[1] Qi*, et al., Zhang*, Calhoun. Derivation and Utility of Schizophrenia Polygenic Risk Associated Multimodal MRI Frontotemporal Network. Nature Communications, 2022, 13(1). (中科院一区，IF: 15.7，综合性顶级期刊).
[2] Liang, et al., Qi*, Calhoun. Confound controlled multimodal neuroimaging data fusion and its application to developmental disorders. IEEE Transactions on Image Processing, 2025, 34:5271-5284. (中科院一区，IF: 13.7，CCF A).
[3] Qi, Yang, et al., Sui*, Ma*. MicroRNA132 Associated Multimodal Neuroimaging Patterns in Unmedicated Major Depressive Disorder. Brain, 2018, 141 (3). (中科院一区，IF: 11.7，神经科学顶级期刊).
[4] Liang, et al., Qi*, Calhoun. Multimodal data fusion in neuroscience: promises, challenges and future directions. IEEE Signal Processing Magazine, 2025, 42 (5), 8-21. (IF: 10.3，信号处理顶级期刊，年发文量~50篇).
[5] Qi, et al., Calhoun*, Sui*. Reward processing in novelty seekers: a transdiagnostic psychiatric imaging biomarker. Biological Psychiatry, 2021, 90(8). (中科院一区，IF: 9，精神疾病学顶级期刊).
指导学生SCI期刊论文:（节选10篇）
[1] Liang (硕士生), et al., Qi*, Calhoun. Psychotic Symptom, Mood and Cognition-associated Multimodal MRI Reveal Shared Links to the Salience Network within the Psychosis Spectrum Disorders. Schizophrenia Bulletin, 2023, sbac158. (SCI中科院一区).
[2] Qiu (硕士生), et al., Qi*, Calhoun. Associations between drinking, smoking with psychotic, depressive and developmental disorders revealed via multimodal neuroimaging. Translational Psychiatry, 2024,14 (1), 326. (SCI中科院一区).
[3] Zhao (硕士生), et al., Qi*, Calhoun. Cross-Cohort Replicable Resting-State Functional Connectivity in Predicting Symptoms and Cognition of Schizophrenia. Human Brain Mapping, 2024, 45 (7), e26694. (SCI中科院二区).
[4] Ji (博士生), et al., Qi*, Calhoun. Identifying psychosis subtypes use individualized covariance structural differential networks and multi-site clustering. Schizophrenia Research, 2024, 264 (130-139). (SCI中科院二区).
[5] Zhang (硕士生), et al., Qi*. Consistent Frontal-Limbic-Occipital Connections in Distinguishing Treatment-Resistant and Non-Treatment-Resistant Schizophrenia. Neuroimage Clincal, 2025,103726. (SCI中科院二区).
[6] Wu (硕士生), et al., Qi*. The impact of atlas parcellation on functional connectivity analysis across six psychiatric disorders. Human Brain Mapping, 2025, 46 (5), e70206. (SCI中科院二区).
[7] Liang (博士生), et al., Qi*, Calhoun. Confound controlled multimodal neuroimaging data fusion and its application to developmental disorders. IEEE Transactions on Image Processing, 2025, 34:5271-5284. (SCI中科院一区，CCF A).
[8] Liang (博士生), et al., Qi*, Calhoun. Multimodal data fusion in neuroscience: promises, challenges and future directions. IEEE Signal Processing Magazine, 2025, 42 (5), 8-21. (IF 10.3).
[9] Ji (博士生), et al., Qi*. Prototypical Representation Learning for Multi-Site Domain Generalization in Schizophrenia Diagnosis. IEEE Transactions on Biomedical Engineering, 2026 (In press). (SCI中科院二区).
[10] Ji (博士生), et al., Qi*, Zhang. Causal-augmented Source-free Domain Adaptation with Scale-free Transformer for Schizophrenia Classification. IEEE Transactions on Neural Systems and Rehabilitation Engineering, (In press).
指导学生会议论文:（节选10篇）
[1] Ji (博士生), et al., Qi*. Adaptive-Similarity-Based Dynamic Functional Connectivity with Spatial-Temporal Attention and Domain Adaptation. ICASSP, 2025. (Oral，CCF B)
[2] Hu (硕士生), et al., Qi*. Reference-Guided Parallel Independent Component Analysis: Estimating Cognition Associated Multimodal Patterns In Schizophrenia. ICASSP, 2025. (CCF B).
[3] Wei (硕士生), et al., Qi*. Cooperative and Competitive Functional Connectivity Based on Improved Ising Model. ICASSP, 2025. (CCF B).
[4] Huang (本科生), et al., Qi*. MPIDS: Multi-Group Perturbation Based Individualized Differential Structural Brain Network. ISBI, 2025. (Oral).
[5] Ji (博士生), et al., Qi*. MMM-BNF: multi-atlas, multi-modal and multi-site dynamic brain network fusion for the diagnosis of schizophrenia. OHBM, 2025. (Merit Abstract Award，top 1%).
[6] Zhang (博士生), et al., Qi*. Site Common Information-Guided Site-to-Individual-to-Global Multi-View GCN for Psychiatric Diagnosis. EMBC, 2025. (Oral，CAAI B).
[7] Ji (博士生), et al., Qi*. MMM-DBNF: multi-atlas, multi-modal and multi-site dynamic brain network fusion for the diagnosis of schizophrenia. EMBC, 2025. (Oral，CAAI B).
[8] Huang (本科生), et al., Qi*. SFINe: Structural-Functional Individual Brain Network Modeling Integrating Group-Level Characteristics. ICONIP, 2025. (CCF C).
[9] Wen (博士生), et al., Qi*. SHAPE: A Submodular-Homotopic Atlas Parcellation Encoder with Contrastive Learning for Individualized Brain Mapping. ICASSP, 2026. (CCF B).
[10] Zhao (博士生), et al., Qi*. BRAINBLIP: Bootstrapping Language-Image Pretraining from MRI and Cognition Alignment to Diagnose Multiple Brain Disorders. ICASSP, 2026. (CCF B).
研究生招生说明：
特别欢迎有较好计算机编程和英文写作能力、一定数学基础、有志于从事科学研究、对人工智能与脑科学交叉研究感兴趣、做事情有自驱力self-motivated的同学报考。课题组提供一定助研金补贴。
长期招聘博士后：
近年获得（或将获得）计算机科学、生物医学工程、生物统计学、数学、认知神经科学或心理学等其他相关领域的博士学位，具有人工智能、脑影像分析、影像基因组学、深度学习或脑疾病研究背景。
具有MRI或EEG或SNP等相关数据分析经验。
以第一作者发表过较高水平SCI论文。
具备很好的学习能力、独立工作能力和团队协作能力，具有一定科研项目申请经验和协助指导研究生经历。
视个人情况，课题组额外提供助研金补贴。