研究员
姓 名: 胡鹏伟
性 别:
职 务:
职 称: 研究员
通讯地址: 乌鲁木齐市北京南路40号附1号
邮政编码: 830011
电子邮件:

简历:

中国科学院新疆理化技术研究所  研究员                 2023.11-至今

中国科学院新疆理化技术研究所  副研究员               2022.12-2023.11

德国默克集团                 人工智能首席科学家      2020.10-2022.11

IBM研究院                    研究科学家              2018.11-2020.10

教育背景:     

计算机科学       香港理工大学         博士           2012.11-2018.11  

主要研究领域及成就:

主要研究方向为人工智能表示学习,复杂网络分析,生物医学分子网络分析、智能类器官等。入选国家海外高层次人才引进项目,天池计划领军人才项目,主持及参与新疆杰出青年科学基金,国家自然科学基金面上项目、青年项目等。曾担任德国默克集团人工智能首席科学家,负责人工智能与生物医疗交叉领域的全球创新研发工作。目前担任BMC Bioinformatics等多家SCI期刊副编辑。担任AAAI、ACL、EMNLP、BIBM、AMIA等国际顶级会议程序委员会委员、领域主席,CCF生信专委会执行委员,中国生物工程学会生物医药大数据专委会委员。曾获 IJCAI DCM Best Paper、ICIC Best Paper、中华医学会智能辅助诊疗大赛一等奖。

主要荣誉:

国家海外高层次人才

新疆“天池计划”领军人才

新疆自然科学基金杰出青年项目

ICIC 2023, Best Paper

IJCAI DCM 2020,Best Paper

中华医学会智能辅助诊疗创新大赛,一等奖

中国中文信息学会智能医疗对话诊疗大赛,三等奖

代表性文章:

(1) Bo-Wei Zhao, Lei Wang, Peng-Wei Hu, Leon Wong, Xiao-Rui Su, Bao-Quan Wang, Zhu-Hong You, Lun Hu. “Fusing Higher and Lower-order Biological Information for Drug Repositioning via Graph Representation Learning. ” IEEE Transactions on Emerging Topics in Computing, 2023. 

(2) Yue-Chao Li, Zhu-Hong You, Chang-Qing Yu, Lei Wang, Leon Wong, Lun Hu, Peng-Wei Hu, Yu-An Huang. "PPAEDTI: Personalized Propagation Auto-Encoder Model For Predicting Drug-Target Interactions.” IEEE Journal of Biomedical and Health Informatics, 2023, 27(1): 573-582.

(3) Xin Luo, Liwei Wang, Peng-Wei Hu, Lun Hu. Predicting Protein-Protein Interactions Using Sequence and Network Information via Variational Graph Autoencoder. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2023, 10.1109/TCBB.2023.3273567, 1-13 .

(4)Jiajia Li, Feng Tan, Cheng He, Zikai Wang, Haitao Song, Pengwei Hu, Xin Luo, Saliency-Aware Dual Embedded Attention Network for Multivariate Time-Series Forecasting in Information Technology Operations, IEEE Transactions on Industrial Informatics, 2023.

(5)Bo-Wei Zhao, Xiao-Rui Su, Peng-Wei Hu, Yu-Peng Ma, Xi Zhou, Lun Hu. A geometric deep learning framework for drug repositioning over heterogeneous information networks. Briefings in Bioinformatics, 2022, 23.6, bbac384.

(6)Lun Hu, Zhenfeng Li, Zehai Tang, Cheng Zhao, Xi Zhou, Peng-Wei Hu,Effectively predicting HIV-1 protease cleavage sites by using an ensemble learning approach. BMC Bioinformatics, 2022, 23.1: 447.

(7)Lun Hu, Hong Yan, Peng-Wei Hu, Tiantian He, Exploiting higher-order patterns for community detection in attributed graphs. Integrated Computer-Aided Engineering 28.2 (2021): 207-218.

(8)Peng-Wei Hu, Yu-An Huang, Keith CC Chan, and Zhu-Hong You, Learning multimodal networks from heterogeneous data for prediction of lncRNA-miRNA interactions. IEEE Transactions on Computational Biology and Bioinformatics, 2020, 17(5): 1516-1524

(9)Yu-An Huang, Peng-Wei Hu, Keith CC Chan, and Zhu-Hong You. “Graph convolution for predicting associations between miRNA and drug resistance.” Bioinformatics, 2020, 36, no. 3: 851-858.

(10)Peng-Wei Hu, Keith CC Chan, and Zhu-Hong You. Large-scale prediction of drug-target interactions from deep representations. In 2016 International Joint Conference on Neural Networks (IJCNN), pp. 1236-1243. IEEE, 2016.

研究领域:

 人工智能,生物医疗信息,智能类器官


研究领域: