刘克飞，中国科学技术大学苏州高等研究院特任副研究员。一般研究兴趣是开发新的机器学习和统计算法来解决生物医学应用中的实际问题，目前的研究着眼于利用知识引导的典型相关分析（knowledge-guided canonical correlation analysis）等多模态数据融合技术对多组学(muti-omics)和多模态影像数据进行整合分析，进行疾病预测和生物标志物识别。曾在IEEE Transactions on Signal Processing，Medical Image Analysis，Bioinformatics等期刊和ICASSP/ EUSIPCO/MICCAI/ISBI/BIBM/IPMI等国际会议上发表论文 60 余篇（包括10篇一作SCI 期刊论文和11篇一作国际会议论文），其中一项研究成果获得BIBM 2018最佳论文奖。长期担任机器学习和信号处理顶级会议(NeurIPS/ICML/ICLR/AAAI/IJCAI/KDD/SDM/MICCAI)和期刊(IEEE TSP/TPAMI/TMI等)的审稿人。
电子邮箱
kefeiliu@ustc.edu.cn
工作经历
2022/05-至今，中国科学技术大学苏州高等研究院，特任副研究员
2016/07-2021/12，宾夕法尼亚大学，生物统计学、流行病学与信息学系，助理研究员（Research Associate）
2014/01-2016/06，密歇根大学，计算医学与生物信息学系，博士后，合作导师: 叶杰平
2009/02- 2010/08，武汉滨湖电子有限责任公司，软件工程师
学习经历
2010/09-2013/10，香港城市大学，电子工程，博士，导师：So, Hing Cheung (蘇慶祥)
2006/09-2009/01，北京航空航天大学，基础数学，硕士，导师: 李尚志，杨东凯
2002/09-2006/06，武汉大学，数学与应用数学，学士
主要科研项目
1. Advancing multimodal data fusion techniques for computer-aided medical diagnosis，课题负责人
2. 基于多任务多视角学习的影像遗传学分析方法研究，国家自然科学基金，第一参与人
获奖及荣誉情况
1. 香港城市大学学费豁免奖学金（Research Tuition Scholarship，2013）
2. 香港城市大学研究生奖学金（Research Studentship，2010-2013）
3. 北京航空航天大学国防就业优秀毕业生奖学金（2009）
4. 北京航空航天大学理学院优秀硕士学位论文（2009）
5. 武汉大学乙等人民奖学金，武汉大学优秀学生（2005）
6. 武汉大学国家奖学金，武汉大学优秀学生（2004）
主要学术论文
期刊论文:
1. Lei Du, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han, Andrew J. Saykin, Lei Guo, and Li Shen, Detecting genetic associations with brain imaging phenotypes in Alzheimer's disease via a novel structured SCCA approach, Medical Image Analysis, vol. 61, Apr. 2020, article no. 101656.
2. Kefei Liu, Li Shen, and Hui Jiang, Joint between-sample normalization and differential expression detection through L0-regularized linear regression, BMC Bioinformatics, vol. 20, suppl. 16, Dec. 2019, article no. 593.
3. Lei Du, Kefei Liu, Lei Zhu, Xiaohui Yao, Shannon L. Risacher, Lei Guo, Andrew J. Saykin, and Li Shen, Identifying progressive imaging genetic patterns via multi-task sparse canonical correlation analysis: A longitudinal study of the ADNI cohort, Bioinformatics, vol. 35, no. 14, pp. i474—i483, Jul. 2019.
4. Kefei Liu, Jieping Ye, Yang Yang, Li Shen, and Hui Jiang, A unified model for joint normalization and differential gene expression detection in RNA-seq data, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 16, no. 2, pp. 442—454, Mar.—Apr. 2019.
5. Lei Du, Kefei Liu, Tuo Zhang, Xiaohui Yao, Jingwen Yan, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, and Li Shen, A novel SCCA approach via truncated L1-norm and truncated group lasso for brain imaging genetics, Bioinformatics, vol. 34, no. 2, pp. 278—285, Jan. 2018.
6. Kefei Liu, Hui Cao, Hing Cheung So, and Andreas Jakobsson, Multi-dimensional sinusoidal order estimation using angles between subspaces, Digital Signal Processing, vol. 64, pp. 17—27, May 2017.
7. Kefei Liu, João Paulo C. L. da Costa, Hing Cheung So, Lei Huang, and Jieping Ye, Detection of number of components in CANDECOMP/PARAFAC models via minimum description length, Digital Signal Processing, vol. 51, pp. 110—123, Apr. 2016.
8. Kefei Liu, Lei Huang, Hing Cheung So, and Jieping Ye, Multidimensional folding for sinusoidal order selection, Digital Signal Processing, vol. 48, pp. 349—360, Jan. 2016.
9. Kefei Liu, João Paulo C. L. da Costa, Hing Cheung So, and André L. F. de Almeida, Semi-blind receivers for joint symbol and channel estimation in space-time-frequency MIMO-OFDM systems, IEEE Transactions on Signal Processing, vol. 61, no. 21, pp. 5444—5457, Nov. 2013.
10. João Paulo C. L. da Costa, Kefei Liu, Hing Cheung So, Stefanie Schwarz, Martin Haardt, and Florian Roemer, Multidimensional prewhitening for enhanced signal reconstruction and parameter estimation in colored noise with Kronecker correlation structure, Signal Processing, vol. 93, no. 11, pp. 3209—3226, Nov. 2013. [First two authors contributed equally.]
会议论文:
1. Lei Du, Fang Liu, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, and Li Shen, A dirty multi-task learning method for multi-modal brain imaging genetics, in Proc. 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Shenzhen, China, Oct. 2019, pp. 447—455.
2. Lei Du, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, and Li Shen, Fast multi-task SCCA learning with feature selection for multi-modal brain imaging genetics, in Proc. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Madrid, Spain, Dec. 2018, pp. 356—361. [acceptance rate: 19.6%]. 最佳论文奖
3. Kefei Liu, Li Shen, and Hui Jiang, A unified model for robust differential expression analysis of RNA-seq data, in Proc. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Madrid, Spain, Dec. 2018, pp. 437—442. [acceptance rate: 19.6%]
4. Jingwen Yan, Kefei Liu, Huang Li, Enrico Amico, Shannon L. Risacher, Yu-chien Wu, Shiaofen Fang, Olaf Sporns, Andrew J. Saykin, Joaquín Goñi, and Li Shen, Joint exploration and mining of memory-relevant brain anatomic and connectomic patterns via a three-way association model, in Proc. IEEE 15th International Symposium on Biomedical Imaging (ISBI), Washington, DC, USA, Apr. 2018, pp. 6—9.
5. Xiaoqian Wang, Kefei Liu, Jingwen Yan, Shannon L. Risacher, Andrew J. Saykin, Li Shen, and Heng Huang, Predicting interrelated Alzheimer's disease outcomes via new self-learned structured low-rank model, in Proc. 25th International Conference on Information Processing in Medical Imaging (IPMI), Lecture Notes in Computer Science vol. 10265, Boone, NC, USA, Jun. 2017, pp. 198—209. [acceptance rate: 33%]
6. Kefei Liu, Florian Roemer, João Paulo C. L. da Costa, JieXiong, Yi-Sheng Yan, Wen-Qin Wang, and Giovanni Del Galdo, Tensor-based sparsity order estimation for big data applications, in Proc. 25th European Signal Processing Conference (EUSIPCO), Kos, Greece, Aug.—Sept. 2017, pp. 648—652. invited paper
7. Kefei Liu, João Paulo C. L. da Costa, Hing Cheung So, Florian Roemer, and Lei Huang, On the use of order selection rules for accurate parameter estimation in threshold region, 21st European Signal Processing Conference (EUSIPCO), Marrakech, Morocco, Sept. 2013.
