陈挺

陈挺
陈挺 教授
 Professor of Biology, Computer Science and Mathematics
University of Southern California

个人简历:        

讲师(遗传学),哈佛大学医学院(Harvard Medical School),美国, 1997-2000;

教授(生命科学,计算机科学,数学),南加州大学(USC),美国,2000-2016;

教授(计算机科学),清华大学,至今

主要科研领域及方向:             

陈挺教授现为清华大学计算机科学与技术系教授。同时在北京信息科学与技术国家研究中心,清华大学人工智能研究院任职。担任清华大学数据科学研究院,医疗和健康大数据研究中心主任。1988年保送进入清华大学计算机系学习,1993年获学士学位,1997年获美国纽约州立大学石溪分校(Stony Brook University)计算机科学博士学位。1997至2000年,任美国哈佛大学医学院(Harvard Medical School)遗传学讲师;2000至2016年,历任美国南加州大学(University of Southern California)生命科学系,计算机科学系,数学系助理教授、副教授、正教授,曾经担任南加州大学计算生物学部主任(相当于系主任)。

陈挺教授长期研究大数据高效算法设计和机器学习,并应用于研究人类基因组、转录组和蛋白组的高通量大数据分析和功能预测。在生物调控系统的数学模型、蛋白质组学以及质谱仪数据处理、高通量基因组测序数据处理、宏基因组数据处理,复杂疾病的遗传学研究、医学信息处理等方面均取得了一系列重要的研究成果。主持及参与美国自然科学基金会(NSF)、美国国家卫生研究院(NIH),中国自然科学基金(NSFC)等项目十余项。在Cell、Science、Nature Communications、PNAS、Genome Research、American Journal of Human Genetics, Cell Systems, Genome Biology, Nucleic Acid Research等国际著名期刊发表学术论文120余篇,被引超过10000次(Google Scholar),其中20篇论文被引用超过100次。

2004年获得美国史隆基金会研究奖(Sloan Fellow)。

代表论文:     

1. Zhang K, Liu X, Shen J, et al. (2020) Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements and Prognosis of COVID-19 Pneumonia Using Computed Tomography. Cell. DOI: 10.1016/j.cell.2020.04.045

2. Liu X, Wang K, Zhang K, Chen T*, and Wang G* (2020) KISEG: A Three-Stage Segmentation Framework for Multi-level Acceleration of Chest CT Scans from COVID-19 Patients. Medical image computing and computer assisted intervention. MICCAI 2020.

3. Wang K, Liu X, Zhang K, Chen T*, and Wang G* (2020). Anterior Segment Eye Lesion Segmentation with Advanced Fusion Strategies and Auxiliary Tasks Medical image computing and computer assisted intervention. MICCAI 2020.

4. Wang K, Chen X, Chen N and Chen T* (2020) Automatic Emergency Diagnosis with Knowledge-Based Tree Decoding. IJCAI 2020.

5. Huang S, Su H, Zhu J* and Chen T* (2020) SVQN: Sequential Variational Soft Q-Learning Networks. ICLR 2020.

6. Wang K, Chen N and Chen T* (2020) Joint Medical Ontology Representation Learning for Healthcare Predictions. IJCNN 2020.

7. Yang Y, Wang X, Zhu C, Chen N and Chen T* (2020) Inferring multiple metagenomic association networks based on variation of environmental factors. Genomics, Proteomics & Bioinformatics.

8. Xie K, Liu Z, Chen N and Chen T* (2020) Reconstructing the Pseudo Development Time of Cell Lineages in Single-Cell RNA-Seq Data and Applications in Cancer. Genomics, Proteomics & Bioinformatics.

9. Gu J, Shi Y, Chen N, Wang H* and Chen T* (2020) Ambient fine particulate matter and hospital admissions for ischemic and hemorrhagic strokes and transient ischemic attack in 248 Chinese cities. Science of the Total Environment. https://doi.org/10.1016/j.scitotenv.2020.136896

10. Feng Y, Xu Z, Gan L, Chen L, Yu B, Chen T*, and Wang F* (2019) DCMN: Double Core Memory Network for Patient Outcome Prediction with Multimodal Data. ICDM 2019.

11. Zhu C, Zhang J, Guan R, Hale L, Zhou K, Chen N, Li M, Lu Z, Ge Q, Yang Y, Zhou J* and Chen T* (2019) Alternate succession of aggregate-forming cyanobacterial genera correlated with their attached bacteria by co-pathways. Science of the Total Environment. 688:867-879, 2019. https://doi.org/10.1016/j.scitotenv.2019.06.150

12. Cui H, Zeng J*, Chen T* (2019) DeepShape: Estimating Isoform-Level Ribosome Abundance and Distribution with Ribo-seq data. the International Conference on Intelligent Biology and Medicine (ICIBM 2019). Best Paper Award.

13. Zhu C, Zhang J, Nawaz M, Mahboob SZ, Al-Ghanim KA, Khan IA, Lu Z & Chen T* (2019) Seasonal succession and spatial distribution of bacterial community structure in a eutrophic freshwater Lake, Lake Taihu. Science of the Total Environment. 669:29-40, 2019. https://doi.org/10.1016/j.scitotenv.2019.03.087

14. Huang S, Su, H, Zhu J* and Chen T* (2019) Combo-Action: Training Agent for FPS Game with Auxiliary Tasks. AAAI 2019.

15. Liu Z, Lou H, Wang H, Xie K, Chen N, Aparicio O, Zhang M, Jiang R* and Chen T* (2017) Reconstructing Cell Cycle Pseudo Time-Series via Single-cell Transcriptome Data. Nature Communications. 2017 Jun 19;8(1):22. DOI: 10.1038/s41467-017-00039-z

16. Yang Y, Chen N*, Chen T* (2017). mLDM: a new hierarchical Bayesian statistical model for sparse microbial association discovery. Cell Systems. Volume 4, Issue 1, p129–137.e5, 25 January 2017.

17. Jiang L, Chen N* and Chen T* (2016) DACE: A Scalable DP-means algorithm for clustering extremely large sequence data. Bioinformatics. doi:10.1093/bioinformatics/btw722.

18. Zeng F, Jiang R* and Chen T* (2013) PyroHMMSNP: a SNP caller for Ion Torrent and 454 Sequencing Data. Nucleic Acid Research. 1-13, doi:10.1093/nar/gkt372.

19. Lehmann K and Chen T* (2012) Exploring functional variant discovery in non-coding regions with SInBaD. Nucleic Acid Research, August 31, 2012 doi:10.1093/nar/gks800.

20. Hao X, Jiang R, and Chen T* (2011) Clustering 16S rRNA for OTU prediction: a method of unsupervised Bayesian clustering. Bioinformatics. 2011 Mar 1;27(5):611-8. Epub 2011 Jan 13.

21. Chen Y, Souaiaia T, and Chen T* (2009) PerM: Efficient Mapping of Short Sequencing Reads with Periodic Full Sensitive Spaced Seeds. Bioinformatics. 25(19):2514-21.

22. Wang L, Sun F and Chen T*. (2008) Prioritizing functional modules mediating genetic perturbations and their phenotypic effects: a global strategy. Genome Biology. 9:R174, 2008.

23. Jiang R, Yang H, Kuo J CC, Sun F and Chen T*. (2007) Sequence-based prioritization of nonsynonymous single nucleotide polymorphisms for the study of disease mutations. American Journal of Human Genetics. 2007 Aug;81(2):346-60.

24. Jiang R, Tu Z, Chen T* and Sun F*. (2006) Network Motif Identification in Stochastic Networks. The Proceeding of National Academy of Sciences (PNAS). 2006. vol 103 no 2 page 9404-9. (* corresponding authors)

 

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