陈俊杰 - 哈尔滨工业大学（深圳） - 计算机科学与技术学院

个人简介

陈俊杰，博士，哈尔滨工业大学（深圳）计算机科学与技术学院助理教授。分别于2013年和2018年获得哈尔滨工业大学大学硕士和博士学位，随后相继在美国北卡罗莱纳大学夏洛特分校、天普大学从事博士后研究工作。研究课题集中于面向生物医学大数据的分析、隐私保护研究和机器学习归因推理。近五年发表SCI期刊论文15篇（其中JCR一区9篇，中科院一区4篇，5篇论文曾被选为ESI热点论文），会议论文4篇（其中1篇获得最佳论文），Google Scholar引用1400余次，H-index为12，另有国家专利2个，参与国家面上项目2项和参与撰写书籍1本。参与国际人类基因结构变异联盟（Human Genome Structure Variant Consortium，HGSVC）相关研究成果发表于《Science》。目前是多个知名SCI期刊审稿人（Briefings in Bioinformatics, Bioinformatics, IEEE-ACM TCBB）。工作经历 2021.02--今助理教授哈尔滨工业大学（深圳） 2019.09--2021.02 博士后美国天普大学 2018.03-2019.08 博士后美国北卡罗莱纳大学夏洛特分校教育经历 2013.09-2018.01 计算应用技术哈尔滨工业大学（深圳）博士 2011.09-2013.07 计算科学与技术哈尔滨工业大学（深圳）硕士 2007.09-2011.07 数学与应用数学河南科技大学学士

研究领域

基于机器学习技术的生物医学大数据分析个性化医疗和精准医疗是现代生物医学发展的目标，其中的关键技术是通过对生物医学大数据分析揭示人类基因的调控机制。该研究基于自然语言处理和深度学习等人工智能技术研究人类全基因组和生物医学大数据，揭示特定生物学过程和重大疾病的发生发展过程。面向合成生物学的人工智能方法及应用人工智能技术的迅猛发展为生物序列的智能设计提供了新的机遇。由于生物数据本身的高维特性以及数据中隐含模式的复杂性，人工智能技术算法在挖掘重要生物学特征、探求特征之间隐含的复杂关系等方面表现出了独特的优势。该研究基于生成对抗网络(GAN)和变分自编码器（VAE）等人工智能技术，智能化地探索核酸序列、蛋白质序列和新药物分子空间，以实现从头设计或定向优化生物元件和药物分子。面向生物医学数据的隐私保护计算随着机器学习技术对生物医学大数据的赋能，使得个性化医疗、精准医疗成为可能。然而在对大规模、高质量的生物医学数据建模的同时，数据和模型导致的隐私泄漏也已成为亟需解决的问题。该研究基于差分隐私、联邦学习、同态加密等信息安全框架，构建安全的机器学习模型，实现多场景安全可信的生物医学数据隐私保护方法。

近期论文

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SCI期刊论文 Peter Ebert#, Peter A. Audano#, Qihui Zhu#, Bernardo Rodriguez-Martin#, David Porubsky, Marc Jan Bonder, Arvis Sulovari, Jana Ebler, Weichen Zhou, Rebecca Serra Mari, Feyza Yilmaz, Xuefang Zhao, PingHsun Hsieh, Joyce Lee, Sushant Kumar, Jiadong Lin, Tobias Rausch, Yu Chen, Jingwen Ren, Martin Santamarina, Wolfram H？ps, Hufsah Ashraf, Nelson T. Chuang, Xiaofei Yang, Katherine M. Munson, Alexandra P. Lewis, Susan Fairley, Luke J. Tallon, Wayne E. Clarke, Anna O. Basile, Marta Byrska-Bishop, André Corvelo, Mark J.P. Chaisson, Junjie Chen, Chong Li, Harrison Brand, Aaron M. Wenger, Maryam Ghareghani, William T. Harvey, Benjamin Raeder, Patrick Hasenfeld, Allison Regier, Haley Abel, Ira Hall, Paul Flicek, Oliver Stegle, Mark B. Gerstein, Jose M.C. Tubio, Zepeng Mu, Yang I. Li, Xinghua Shi, Alex R. Hastie, Kai Ye, Zechen Chong, Ashley D. Sanders,MichaelC.Zody,Michael E. Talkowski, Ryan E. Mills, Scott E. Devine, Charles Lee*, Jan O. Korbel*, Tobias Marschall*, Evan E. Eichler*. Haplotype-resolved diverse human genomes and integrated analysis of structural variation. Science, 2021, eabf7117. (SCI，影响因子：41.845，JCR：Q1，h-index：1058) Xinghua Shi, Saranya Radhakrishnan, Jia Wen, Jin Yun Chen, Junjie Chen, Brianna Ashlyn Lam, Ryan E. Mills, Barbara E. Stranger, Charles Lee, and Sunita R Setlur*. Association of CNVs with methylation variation, Genomic Medicine 2020, 5(1): 41. (SCI，影响因子：5.631，JCR：Q1， h-index：11) Junjie Chen and Xinghua Shi*. Sparse convolutional denoising autoencoders for genotype imputation. Genes, 2019, 10(9): 652. (SCI，影响因子：3.759，JCR：Q2，h-index：40) Junjie Chen, Mingyue Guo, Xiaolong Wang and Bin Liu*. A comprehensive review and comparison of different computational methods for protein remote homology detection. Briefings in Bioinformatics 2018,19(2):231-244. (SCI，影响因子：8.990，JCR：Q1，h-index：90，ESI热点论文) Junjie Chen, Mingyue Guo, Shumin Li and Bin Liu*. ProtDec-LTR 2.0: An improved method for protein re-mote homology detection by combining pseudo protein and supervised Learning to Rank, Bioinformatics 2017, 33(21):3473-3476. (SCI，影响因子：5.61，JCR：Q1，h-index：335) in Liu*, Junjie Chen, Mingyue Guo, and Xiaolong Wang. Protein remote homology detection and fold recognition based on Sequence-Order Frequency Matrix. IEEE-ACM Transactions on Computational Biology and Bioinformatics. 2017, 16(1):292-300. (SCI，影响因子：3.015，JCR：Q1，h-index：59) Junjie Chen, Bingquan Liu*, and Dong Huang. Protein remote homology detection based on an ensemble learning approach. BioMed Research International 2016, 2016: 5813645. (SCI，影响因子：2.276，JCR：Q3， h-index：94) Bin Liu*, Junjie Chen, Xiaolong Wang, Application of learning to rank to protein remote homology detection. Bioinformatics 2015, 31(21):3492-3498. (SCI，影响因子：5.61，JCR：Q1，h-index：335，ESI热点论文) Bin Liu*, Junjie Chen, Xiaolong Wang, Protein remote homology detection by combining Chou’s distance-pair pseudo amino acid composition and principal component analysis. Molecular Genetics and Genomics 2015, 290(5):1919-1931. (SCI，影响因子：2.797，JCR：Q3， h-index：111) Bin Liu*, Junjie Chen and Shanyi Wang, Protein remote homology detction by combining pseudo dimer composition with an ensemble learning method, Current Proteomics, 2016, 13(2):86-91. (SCI，影响因子：0.680，JCR：Q4， h-index：20) Shumin Li, Junjie Chen, and Bin Liu*. Protein remote homology detection based on bidirectional long short-term memory. BMC bioinformatics 2017, 18: 443. (SCI，影响因子：3.242，JCR：Q1， h-index：183) Bin Liu*, Fule Liu, Xiaolong Wang, Junjie Chen, Longyun Fang, and Kuo-Chen Chou*: Pse-in-One: a web server for generating various modes of pseudo components of DNA, RNA, and protein sequences. Nucleic Acids Research, 2015, 43(W1), W65-W71. (SCI，影响因子：11.501，JCR：Q1， h-index：452，ESI热点论文) Bin Liu*, Longyun Fang, Junjie Chen, Fule Liu, and Xiaolong Wang. miRNA-dis: microRNA precursor identification based on distance structure status pairs, Molecular BioSystems 2015, 11:1194-1204. (SCI，影响因子：3.336，JCR：Q2，h-index：82，ESI热点论文) 会议论文 Junjie Chen, Wendy Hui Wang, Hongchang Gao and Xinghua Shi. PAR-GAN: Improving the Generalization of Generative Adversarial Networks Against Membership Inference Attacks. In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, pp. 127-137. 2021. Junjie Chen, Wendy Hui Wang and Xinghua Shi. Differential Privacy Protection Against Membership Inference Attack on Machine Learning for Genomic Data. Pacific Symposium on Biocomputing (PSB). The Virtual Big Island of Hawaii. January 5-7, 2021. Junjie Chen, Mohammad Mowlaei and Xinghua Shi. Population-scale Genomic Data Augmentation Based on Conditional Generative Adversarial Networks. Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB). Virtual Event, USA. Sep. 21-24, 2020. Junjie Chen and Xinghua Shi. A Sparse Convolutional Predictor with Denoising Autoencoders for Phenotype Prediction. Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB). Niagara Falls, NY, USA. Sep. 7-10, 2019. Junjie Chen, Mingyue Guo, Xiaolong Wang, Bin Liu*. SOFM-Top: protein remote homology detection and fold recognition based on Sequence-Order Frequency Matrix. International Conference on Intelligent Computing (ICIC). Liverpool, UK. August 7-10, 2017. (Best Paper) 书籍 eQTL Analysis: Methods and Protocols. (Responsible for Chapter 7: Statistical and Machine Learning Methods for eQTL Analysis.), Springer US. 2019.