Peiliang Lou
Contact
[email protected] Google Scholar Profile
Research Interests
- Artificial Intelligence in Pathology
- Biomedical Text Mining
- Knowledge Engineering
Professional Skills
Python, Java, Machine learning, PyTorch, Protégé (a wide-adopted tool for constructing ontology and knowledge graph)
Education
- 2019-2023 Ph.D. in Computer Science and Technology, Xi’an Jiaotong University
- Ph.D. Thesis: The Methods of Representation, Fusion and Automatic Acquisition for Pathology Knowledge
- 2017-2019 M.E. in Computer Science and Technology, Xi’an Jiaotong University
- 2012-2016 B.E. in Computer Science and Technology, Xi’an Jiaotong University
Experience
- 2019–Now The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
- Research Assistant in the Department of Pathology
- Worked on the project “A Study on Formalized Representation of Pathology Knowledge”
- Collaborated with a team of pathologists to analyze the intrinsic meaning of pathology knowledge in terms of pathological entities, phenotypes and differential diagnosis
- Developed three directed heterogeneous graphs to represent pathology knowledge in a structured form.
- Experimentally validated the graph representations on three use cases including quantitative analysis of pathological features, deep phenotyping and automatic pathological diagnosis.
- 2016-2017 Intel Software Guard Extensions Infrastructure Team, Shanghai, China
- Constructed and maintained the test environment for SGX product code, implementing automated testing frameworks for efficiency.
- 2014-2017 Undergraduate Research Prof. Guoshuai Zhao
- Developed a recommendation method of Place-Of-Interest (POI) based on sentiment analysis of Sina Weibo social media data.
Publications
Published:
- Lou, P., Wang, C., Guo, R., Yao, L., Zhang, G., Yang, J., … & Li, C. (2022). HistoML, a markup language for representation and exchange of histopathological features in pathology images. Nature Scientific data, 9(1), 1-12.
- Lou, P., Jimeno Yepes, A., Zhang, Z., Zheng, Q., Zhang, X., & Li, C. (2020). BioNorm: deep learning-based event normalization for the curation of reaction databases. Bioinformatics, 36(2), 611-620.
- Zhao, G., Lou, P., Qian, X., & Hou, X. (2020). Personalized location recommendation by fusing sentimental and spatial context. Knowledge-Based Systems, 196, 105849.
- Lou, P., Dong, Y., Jimeno Yepes, A., & Li, C. (2021). A representation model for biological entities by fusing structured axioms with unstructured texts. Bioinformatics, 37(8), 1156-1163.
- Lou, P., Zhao, G., Qian, X., Wang, H., & Hou, X. (2016, April). Schedule a rich sentimental travel via sentimental POI mining and recommendation. In 2016 IEEE second international conference on multimedia big data (BigMM) (pp. 33-40). IEEE.
Under Revision:
- Lou, P., Wang, C., Guo, R., Yao, L., Li, C. The pathology markup language (PathoML): a standardized representation of computationally utilizing pathological features. Under revision in Nature Scientific data.
English Test Scores
- GRE: VR (151), QR (166), AW (3.0), Test date: 09/20/2015
- TOEFL: Total (107), R (30), L (26), S (26), Wr (25), Test date: 10/10/2015
- TOEFL: Total (105), R (30), L (24), S (26), Wr (25), Test date: 10/13/2019