【中文版】我校国际教育学院学生参与的研究成果入选ICPR 2026国际会议
近日，由我校信息科学与技术学院与国际教育学院联合培养的研究团队提出的论文被国际学术会议ICPR 2026（International Conference on Pattern Recognition）正式接收发表。该论文由国际教育学院学生R. Valiyev作为核心成员参与完成，Valiyev来自阿塞拜疆巴库工程大学，在我校就读计算机科学与技术专业双学位项目，该论文的发表展现了我校国际学生在人工智能前沿领域的创新研究能力。
国际化协作，跨国研究团队
该研究由我校信息科学与技术学院与国际教育学院联合指导，在课题研究过程中，Valiyev同学积极投身科研创新实践，与中外团队成员紧密协作，在医学图像识别关键技术的研发中发挥了重要作用。这一成果充分展现了我校国际教育学院鼓励国际学生参与前沿科研、培养创新实践能力的人才培养成效。
国际学生科研创新实践
该研究聚焦医学图像智能识别技术，致力于解决临床场景中罕见疾病和微小病变的自动识别难题。Valiyev在项目中深入参与算法设计与实验验证，将所学知识与创新思维融入科研实践，在6个国际生物医学数据集上取得了领先的识别效果，为计算机辅助诊断技术的发展贡献了创新力量。
研究意义与应用价值
该研究成果能够有效提升罕见疾病和微小病变的识别准确率，为计算机辅助诊断技术的发展提供了新的解决方案，具有重要的临床应用价值。这也是我校推进国际科研合作、培养具有全球视野的创新型人才的重要成果。
国际教育学院始终致力于为国际学生搭建科研创新平台，鼓励学生参与前沿学术研究，培养跨文化协作与创新能力。未来，学院将持续推进国际合作与交流，支持更多国际学生投身高水平创新实践活动，为开放北化建设，国际化创新人才培养贡献力量。
图1：基于AI的智能医学图像识别技术示意图
指导教师：李瑞瑞，副教授，北京化工大学信息科学与技术学院，主要研究方向为医学多模态数据分析与人工智能。
[English] Research Achievement by the School of International Education Student Accepted at ICPR 2026
A research paper co-authored by School of International Education student R. Valiyev from Baku Engineering University (Azerbaijan) has been accepted for publication at the International Conference on Pattern Recognition (ICPR 2026), demonstrating the innovative research capabilities of our international students in the field of artificial intelligence.
School of International Education student, Cross-Border Research Team
Co-supervised by the School of Information Science and Technology and the School of International Education, this work features R. Valiyev as a core contributor. Throughout the project, Valiyev actively engaged in scientific research and innovation, collaborating closely with team members from both China and abroad. His contributions to the development of medical image recognition technology exemplify the School of International Education's commitment to fostering innovation and practical research skills among international students.
International Student Research and Innovation
The research focuses on intelligent medical image recognition, addressing the challenge of automatic detection of rare diseases and subtle lesions in clinical settings.Valiyev participated extensively in algorithm design and experimental validation, applying his knowledge and innovative thinking to achieve leading recognition performance across six international biomedical datasets and contributing creative solutions to computer-aided diagnosis technology.
Research Significance and Application Value
The research effectively improves the recognition accuracy of rare diseases and subtle lesions, offering new solutions for computer-aided diagnosis technology with significant clinical application value. It also represents an important achievement in our university's efforts to promote international research collaboration and cultivate globallyminded innovative talent.
The School of International Education remains dedicated to building research and innovation platforms for international students, encouraging participation in cutting-edge academic research while cultivating cross-cultural collaboration and creative problem-solving skills. The College will continue to advance international cooperation and support more international students in high-level innovation activities,contributing to the development of an open BUCT and the cultivation of internationally-oriented innovative talents.
Figure 1: Illustration of AI-based intelligent medical image recognition technology
Supervisor: Li Ruirui, Associate Professor, School of Information Science and Technology, Beijing University of Chemical Technology. Her research focuses on medical multimodal data analysis and artificial intelligence.