2013年6月高中毕业于厦门市集美中学，2017年7月本科毕业于厦门大学自动化系，2017年9月进入清华大学自动化系直接攻读博士学位，2021年12月提前通过毕业答辩，2022年1月加入南开大学数学科学学院任副教授，2023年12月入选国家青年人才托举工程。现任南开大学“创新思维人工智能”校企联合研发中心负责人，数学科学学院团委副书记、学风涵养工作室学业导师。 曾获得 4 次国家奖学金、2017年厦门大学文庆奖学金（全校共10名）、2021年清华大学“学术新秀”称号（全校共10名）、清华大学优秀博士学位论文、北京市优秀毕业生等多项奖学金和荣誉。曾在 10 余项省级及以上的科创比赛中获奖。曾指导多名本科生及研究生，其指导成果发表于Nature Machine Intelligence、Nature Communications、Nature Computational Science等期刊，并获评清华大学本科生优秀毕业设计、南开大学本科生优秀毕业设计等。 教育经历 2013.09 - 2017.07 厦门大学自动化系，本科 2017.09 - 2021.12 清华大学自动化系，博士，导师：Prof. Rui Jiang 2020.08 - 2021.08 清华全球私募股权研究院，私募基金综合能力提升项目 工作经历 2019.08 - 2020.01 香港中文大学统计系，研究助理 2022.01 - 南开大学数学科学学院，副教授 科研项目 中国科学技术协会，青年人才托举工程，2024-01至2026-12（主持，30万元） 横向项目，基于大语言模型的***生成系统，2024-01至2026-12（主持，300万元） 国家自然科学基金委员会，青年科学基金项目，2023-01至2025-12（主持，30万元） 中央高校基本科研业务费，2023-01至2024-12（主持，12万元） 南开大学引进人才启动基金，2022-01至2024-12（主持，20万元） 国家自然科学基金委员会，面上项目，2019-01至2022-12（参与，66万元） 开授课程 秋季学期：《计算生物前沿》（本科生）、《统计模型与数据分析》（研究生） 春季学期：《数据挖掘》（本科生）

基于机器学习方法的单细胞组学数据建模与解析。

现任中国自动化学会智能健康与生物信息专委会委员、中国人工智能学会生物信息学与人工生命专委会常务委员、中国计算机学会生物信息学新未来青年学者执委会委员、中国运筹学会计算系统生物学分会青年理事、中国生物工程学会计算生物学与生物信息学专委会委员；Journal of Genetics and Genomics期刊青年编委；Nature Communications、Genome Biology、Nucleic Acids Research、Advanced Science、Bioinformatics、PLOS Computational Biology、Genomics, Proteomics & Bioinformatics等期刊审稿人；BIBM（CCF推荐B类会议）PC Member。

Zhen Li, Xuejian Cui, Xiaoyang Chen, Zijing Gao, Yuyao Liu, Yan Pan, Shengquan Chen, Rui Jiang*. Cross-modality representation and multi-sample integration of spatially resolved omics data. Yuxi Li, Yi Liu, Yuekang Li, Ling Shi, Gelei Deng, Shengquan Chen, Kailong Wang. Lockpicking LLMs: a logit-based jailbreak using token-level manipulation. Heyang Hua†, Wenxin Long†, Yan Pan†, Siyu Li, Jianyu Zhou*, Haixin Wang*, Shengquan Chen*. scCrab: a reference-guided ensemble method for cancer cell identification via Bayesian neural networks. Qiuchen Meng†, Xinze Wu†, Chen Li, Jiaqi Li, Xi Xi, Sijie Chen, Shengquan Chen, Jiaqi Li, Xiaowo Wang, Rui Jiang, Lei Wei*, Xuegong Zhang*. The full set of potential open regions (PORs) in the human genome defined by consensus peaks of ATAC-seq data. Qun Jiang†, Shengquan Chen†, Xiaoyang Chen, Rui Jiang*. scPRAM accurately predicts single-cell gene expression perturbation response based on attention mechanism. Bioinformatics, 2024, btae265. Zijing Gao, Rui Jiang, Shengquan Chen*. OpenAnnotateApi: Python and R packages to efficiently annotate and analyze chromatin accessibility of genomic regions. Bioinformatics Advances, 2024, vbae055. Sijie Li, Yuxi Li, Yu Sun, Yaru Li, Xiaoyang Chen, Songming Tang, Shengquan Chen*. EpiCarousel: memory- and time-efficient identification of metacells for atlas-level single-cell chromatin accessibility data. Bioinformatics, 2024, btae191. Yichuan Cao, Xiamiao Zhao, Songming Tang, Qun Jiang, Sijie Li, Siyu Li, Shengquan Chen*. scButterfly: a versatile single-cell cross-modality translation method via dual-aligned variational autoencoders. Nature Communications, 2024, 15:2973. Editors' Highlights. Xuejian Cui, Xiaoyang Chen, Zhen Li, Zijing Gao, Shengquan Chen*, Rui Jiang*. Discrete latent embedding of single-cell chromatin accessibility sequencing data for uncovering cell heterogeneity. Nature Computational Science, 2024, Online. Yuhang Jia†, Siyu Li†, Rui Jiang, Shengquan Chen*. Accurate annotation for differentiating and imbalanced cell types in single-cell chromatin accessibility data. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2024, Online. Songming Tang, Xuejian Cui, Rongxiang Wang, Sijie Li, Siyu Li, Xin Huang, Shengquan Chen*. scCASE: accurate and interpretable enhancement for single-cell chromatin accessibility sequencing data. Nature Communications, 2024, 15:1629. Editors' Highlights. Haixin Wang†, Yunhan Wang†, Qun Jiang†, Yan Zhang*, Shengquan Chen*. SCREEN: predicting single-cell gene expression perturbation responses via optimal transport. Frontiers of Computer Science, 2024, Online. Keyi Li†, Xiaoyang Chen†, Shuang Song, Lin Hou, Shengquan Chen*, Rui Jiang*. Cofea: correlation-based feature selection for single-cell chromatin accessibility data. Briefings in Bioinformatics, 2024, bbad458. Wenhao Zhang, Rui Jiang, Shengquan Chen*, Ying Wang*. scIBD: a self-supervised iterative-optimizing model for boosting the detection of heterotypic doublets in single-cell chromatin accessibility data. Genome Biology, 2023, 24:225. Zijing Gao†, Xiaoyang Chen†, Zhen Li†, Xuejian Cui†, Qun Jiang, Keyi Li, Shengquan Chen*, Rui Jiang*. scEpiTools: a database to comprehensively interrogate analytic tools for single-cell epigenomic data. Journal of Genetics and Genomics, 2023, Online. Zhen Li, Xiaoyang Chen, Xuegong Zhang, Rui Jiang, Shengquan Chen*. Latent feature extraction with a Prior-based self-Attention framework for Spatial Transcriptomics. Genome Research, 2023, Online. Chen Li†, Xiaoyang Chen†, Shengquan Chen, Rui Jiang*, Xuegong Zhang*. simCAS: an embedding-based method for simulating single-cell chromatin accessibility sequencing data. Bioinformatics, 2023, btad453. Siyu Li, Songming Tang, Yunchang Wang, Sijie Li, Yuhang Jia, Shengquan Chen*. Accurate cell type annotation for single-cell chromatin accessibility data via contrastive learning and reference guidance. Quantitative Biology, 2023, Online. Rui Jiang, Zhen Li, Yuhang Jia, Siyu Li, Shengquan Chen*. SINFONIA: scalable identification of spatially variable genes for deciphering spatial domains. Cells, 2023, 12(4):604. Shengquan Chen*, Rongxiang Wang, Wenxin Long, Rui Jiang*. ASTER: accurately estimating the number of cell types in single-cell chromatin accessibility data. Bioinformatics, 2022, btac842. Zheng Zhang, Shengquan Chen, Zhixiang Lin*. RefTM: reference-guided topic modeling of single-cell chromatin accessibility data. Briefings in Bioinformatics, 2022, bbac540. Xiaoyang Chen†, Shengquan Chen†, Shuang Song, Zijing Gao, Lin Hou, Xuegong Zhang, Hairong Lv, Rui Jiang*. Cell type annotation of single-cell chromatin accessibility data via supervised Bayesian embedding. Nature Machine Intelligence, 2022, 4:116-126. Xi Xi, Haochen Li, Shengquan Chen, Tingting Lv, Tianxing Ma, Rui Jiang, Ping Zhang, Wing Hung Wong*, Xuegong Zhang*. Unfolding the genotype-to-phenotype black box of cardiovascular diseases through cross-scale modeling. iScience, 2022, 25(8):104790. Shengquan Chen†, Guanao Yan†, Wenyu Zhang, Jinzhao Li, Rui Jiang*, Zhixiang Lin*. RA3 is a reference-guided approach for epigenetic characterization of single cells. Nature Communications, 2021, 12:2177. Shengquan Chen, Qiao Liu, Xuejian Cui, Zhanying Feng, Chunquan Li, Xiaowo Wang, Xuegong Zhang, Yong Wang, Rui Jiang*. OpenAnnotate: a web server to annotate the chromatin accessibility of genomic regions. Nucleic Acids Research, 2021, 49(W1):W483-W490. Wanwen Zeng†, Shengquan Chen†, Xuejian Cui†, Xiaoyang Chen, Zijing Gao, Rui Jiang*. SilencerDB: a comprehensive database of silencers. Nucleic Acids Research, 2021, 49(D1):D221-D228. Shengquan Chen, Mingxin Gan, Hairong Lv, Rui Jiang*. DeepCAPE: a deep convolutional neural network for the accurate prediction of enhancers. Genomics, Proteomics & Bioinformatics, 2021, 19(4):565-577. Shengquan Chen, Boheng Zhang, Xiaoyang Chen, Xuegong Zhang, Rui Jiang*. stPlus: a reference-based method for the accurate enhancement of spatial transcriptomics. ISMB/ECCB 2021, Bioinformatics, 2021, 37(S1):i299-i307. Qiao Liu, Shengquan Chen, Rui Jiang*, Wing Hong Wong*. Simultaneous deep generative modeling and clustering of single cell genomic data. Nature Machine Intelligence, 2021, 3:536-544. Xiaoyang Chen, Shengquan Chen, Rui Jiang*. EnClaSC: A novel ensemble approach for accurate and robust cell-type classification of single-cell transcriptomes. BMC Bioinformatics, 2020, 21(13):1-16. Shengquan Chen, Kui Hua, Hongfei Cui, Rui Jiang*. VPAC: Variational projection for accurate clustering of single-cell transcriptomic data. BMC Bioinformatics, 2019, 20(7):139-151. Shaoming Song, Hongfei Cui, Shengquan Chen, Qiao Liu, Rui Jiang*. EpiFIT: functional interpretation of transcription factors based on combination of sequence and epigenetic information. Quantitative Biology, 2019, 7(3):233-243.