Mathematik und Informatik

Prof. Dr. Xiaoyi Jiang, Institut für Informatik

Private Homepage
Research InterestsComputer Vision
Pattern Recognition
Current PublicationsXiao J, Zhong Y, Jia Y, Wang Y, Jiang X, Wang S A novel deep ensemble model for imbalanced credit scoring in internet finance. International Journal of Forecasting Vol. 40 (1), 2024 online
Xiao J, Wen Z, Jiang X, Yu L, Wang S Three-stage research framework to assess and predict the financial risk of SMEs based on hybrid method. Decision Support Systems Vol. 177, 2024 online
Steinhorst, Phil; Duhme, Christof; Jiang, Xiaoyi; Vahrenhold, Jan Recognizing Patterns in Productive Failure. Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1, 2024 online
Chen J, Pi D, Jiang X, Xu Y, Chen Y, Wang X Denosieformer: A transformer based approach for single-channel EEG artifact removal. IEEE Transactions on Instrumentation and Measurement Vol. 73, 2024 online
Eminaga o, Saad F, Tian Z, Wolffgang U, Karakiewicz P, Ouellet V, Azzi F, Spieker T, Helmke B, Graefen M, Jiang X, Xing L, Witt J, Trudel D, Leyh-Bannurah SM Artificial intelligence unravels interpretable malignancy grades of prostate cancer on histology images. npj Imaging Vol. 2, 2024 online
Zhang Q, Jiang X Classification performance boosting for interpolation kernel machines by training set pruning using genetic algorithm. Prof. of ICPRAM, 2024 online
Hegselmann S, Shen Z, Gierse F, Agrawal M, Sontag D, Jiang X A data-centric approach to generate faithful and high quality patient summaries with large language models. Conference on Health, Inference, and Learning (CHIL), 2024 online
Dewi C, Chen RC, Yu H, Jiang X Robust detection method for improving small traffic sign recognition based on spatial pyramid pooling. Journal of Ambient Intelligence and Humanized Computing Vol. 14 (7), 2023 online
Nienkötter A, Jiang X Kernel-based generalized median computation for consensus learning. IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 45 (5), 2023 online
Current ProjectsInterdisziplinäres Lehrprogramm zu maschinellem Lernen und künstlicher Intelligenz

The aim of the project is to establish and test a graduated university-wide teaching programme on machine learning (ML) and artificial intelligence (AI). AI is taught as an interdisciplinary cross-sectional topic that has diverse application possibilities in basic research as well as in economy and society, but consequently also raises social, ethical and ecological challenges.

The modular teaching program is designed to enable students to build up their AI knowledge, apply it independently and transfer it directly to various application areas. The courses take place in a broad interdisciplinary context, i.e., students from different departments take the courses together and work together on projects.

CRC 1450 Z01 - Interactive and computational analysis of large multiscale imaging data The multiscale imaging strategy central to this initiative imposes novel data analysis challenges. The high complexity of the acquired data results from their nature of being volumetric, time-varying, large, multiscale, and forming cohorts. Meeting these challenges requires basic research in the fields of image analysis, machine learning, and visualization. Machine learning will be used to uncover inherent relationships between patterns at multiple scales. An interactive visual approach supports the user-centric analysis of detected features. The deliverable of this project will be generally applicable, effective, and efficient methods supporting the overall goal of multiscale data analysis. online
E-Mailxjiang at uni-muenster dot de
Phone+49 251 83-33759
FAX+49 251 83-33755
Secretary   Sekretariat Steinhoff
Frau Gerlinde Steinhoff
Telefon +49 251 83-38447
Fax +49 251 83-33755
Zimmer 602
AddressProf. Dr. Xiaoyi Jiang
Institut für Informatik
Fachbereich Mathematik und Informatik der Universität Münster
Einsteinstrasse 62
48149 Münster
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