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    Professor Junsong Chen: five years of the entrepreneurial journey in Business Syntegrative Education

    Professor Junsong Chen: five years of the entrepreneurial journey in Business Syntegrative Education

    03 Jul 2026

    150 days, 15 countries, 15,000 km: Student cycles from Suzhou to 红杏视频

    150 days, 15 countries, 15,000 km: Student cycles from Suzhou to 红杏视频

    21 Jul 2026

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    Our PhD students

    Our PhD students
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    We currently offer PhDs in the area of Computer Science and Software Engineering. Our current PhD students and their research areas include:

    Name Research Topic
    1 Xiaotian Ren Portfolio management and artificial intelligence
    2 Yuzheng Feng AI technology and Computer vision
    3 Zhenrong Zhang Abnormal detection based on computer vision
    4 Zhilu Zhang Portfolio Management with Deep Reinforcement Learning Based Market Sentiment
    5 Zhepeng?Li? A New Multi-Agents Reinforcement Learning based Portfolio Management System?
    6 Tong Chen? Extracting Events and their Relations from Natural Language Texts?
    7 Yiyi?Miao? Detection, Localization and Classification of B-Lines in Lung Ultrasound for Differentiation of Pulmonary Fibrosis and?Exdate
    8 Bolin Ren? Self-Supervised Learning in a Spatial-temporal Attention Based CAD Pre-screening on Carotid Ultrasound Sequences?
    9 Yangu?Zhou? Deep learning based multi-modal multi-party emotion recognition in conversation?
    10 Zixuan?Chu? Artificial intelligence & deep learning & computer vision?
    11 Huijia?Wang? Portfolio Management based on Multi-Agent Deep Reinforcement Learning?
    12 Huajun?Yuan? Leveraging AI and Edge Computing for Real-Time High-Definition Map Generation?
    13 Biwen Meng Research of Domain Adaptive Computer-Aided Quantitative Analysis for Digital Pathological Images??
    14 Ziyu Ye Research of Online Cyberbullying Detection Based on Contrastive Self-Supervised Learning
    15 Jianfeng Wang Data-Efficient Machine Learning Algorithms, Self-Supervised Learning, Few-Shot Learning
    16 Jiahao Wang Research of Domain Adaptive Computer-Aided Quantitative Analysis for Digital Pathological Images
    17 Rong Xia Deep Learning for Pan-Cancer Epitranscriptomes
    18 Zhixiang Lu Meta Learning for Domain Adaptation in Multimodal Medical Segmentation
    19 Yulong Li Embodied Intelligence, Large Language Models in Medical
    20 Boqian Wang IKWYS: The high-quality image generation model based on EEG signals
    21 Minze Wang Stable-Diffusion-based Conditional Generation
    22 Zhaodong Wu The General Medical Model with Medical MLLM, Partially-Shot, Visual and Language Prompts
    23 Haoran Zhu The application of neural networks in healthcare and bioinformatics
    24 Zhixing Wu Nanopore sequencing, Machine learning, Deep learning, Construction and optimization of large-scale models
    25 Haochen Xue Multimodal Large Language Model
    26 Dexin Liu Leveraging Knowledge Bases and Graphs for Enhanced Natural Language Understanding and Generation
    27 Xin Gao Prompt Learning for Video Anomaly Detection
    28 Daniil Mikriukov Deep Reinforcement Learning Optimization for Financial Portfolio Management: Integrating Advanced Mathematical Models, Bayesian-Averaging Heterogeneous Vector Autoregressive Methods, Accelerated Convergence Techniques, and LLM-Enhanced Multi-Agent Market Simulations
    29 Yudi Zhang Pathological Image Classification and Detection, Medical Multimodal Large Models
    30 Xuehan Chen Modality Interaction for Computer Vision
    31 Yuxuan Zhang More efficient industrial Large-scale Models Agent solutions
    32 Jiayan Jiang Multimodal Data Fusion and Representation Learning for Computational Oncology
    33 Kanlong Yang AI application
    34 Ziyu Liu Facial generation, reactive facial behavior understanding and animation generation based on diffusion models
    35 Zimeng Liu Novel Deep Learning Architectures and Their Applications in Time Series

    We also collaborate with the XJTLU-JITRI Academy of Industrial Technology in the supervision of PhD students.

    Opportunities are available for candidates to undertake an Enterprise Entrusted PhD project founded by our industry partners.