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Qianjin Guo, Ph.D, Professor and Interdisciplinary Researcher focusing on intelligent systems, AI-driven detection technologies, and biomedical informatics. With a Ph.D. in Mechatronic Engineering from the Chinese Academy of Sciences, he leads research at the intersection of artificial intelligence, advanced instrumentation, and cross-domain applications in energy, biomedicine, and optical imaging.

He serves as an editorial board member for multiple SCI journals, a peer reviewer for leading international publications (including Nature Biomedical Engineering, IEEE, and Chemical Sciences), and an expert committee member for national academic societies. He has led over 20 national research projects, published 100+ papers, and mentored 30+ graduate students, with his team receiving multiple national awards.

• Ph. D. July 2004, Shenyang Institute of Automation (SIA), Chinese Academy of Sciences, PhD in Mechanical and Electronic Engineering, Shenyang, China.
• B.S.  July 1994,  Northeast University of China, Shenyang, China.

 

I. Main Research Areas

1. Artificial Intelligence
2. Intelligent Detection
3. Computational Imaging and Machine Learning
4. Optics and Photonics
5. Physical Chemistry
6. Analytical Chemistry & Photochemistry
7. Ultrafast Spectroscopic Instrument
8. Molecular Imaging
9. Ultrafast Exciton Dynamics

 

II. Awards and Honors

1. Distinguished Mentor for Graduate Students,2024
2. The Institute Excellent Staff Award, 2017
3. The Institute Excellent Young Scientist Scholarship,2016
4. The Institute Excellent Young Scientist Scholarship,2015
5. The Institute Excellent Staff Award, 2013
6. The Institute Excellent Young Scientist Scholarship,2012
7. The Institute Excellent Young Scientist Scholarship, Special recognition award, 2011
8. CAS President Scholarship Award, 2008
9. Excellent graduate students of University of Liaoning, 2008
10. BHBP Biliton-GUCAS scholarship,2008
11. Pacemaker to Merit Student of the Graduate school of Chinese academy of sciences,2006
12. Knowledge Innovation Program Award of the Shenyang Institute of Automation (SIA), Chinese Academy of Sciences, 2006
13. First Class Prizes of The Scientific and Technological Progress Award in Shenyang,2006
14. Pacemaker to Merit Student of the Graduate school of Chinese academy of sciences,2005
15. Knowledge Innovation Program Award of the Shenyang Institute of Automation (SIA), Chinese Academy of Sciences, 2005
16. Postgraduate Direct Scholarship,2005
17. Postgraduate Direct Scholarship,2004
18. Postgraduate Direct Scholarship,2002

 

III. Research Projects

1. The National Natural Science Foundation of China, January 2024–December 2026, Principal Investigator.

2. The National Natural Science Foundation of China: General Program, January 2017–December 2020, Principal Investigator.

3. The National Natural Science Foundation of China: General Program, January 2014–December 2017, Principal Investigator.

4. The National Natural Science Foundation of China: General Program, January 2012–December 2015, Principal Investigator.

5. The Innovation Foundation of Beijing National Laboratory for Molecular Sciences (BNLMS) of the Chinese Academy of Sciences, January 2011–December 2012, Principal Investigator.

6. Major Research Equipment Project of the Chinese Academy of Sciences, January 2008–December 2010, Principal Investigator.

 

IV. Representative Academic Papers

1.Mengqiu Wang , Zhiwei Zhang, Xinxin Zhang, Ruoyan Dai , Zhenghui Wang, Zeyao Chen, Lixin Lei, Zhenxing Li, Qianjin Guo,SpatialFusion: A Unified Model for Integrating Spatial Transcriptomics to Unveil Cell-type Distribution, Interaction, and Functional Heterogeneity in Tissue Microenvironments[J],Journal of Molecular Biology,2026, 438(2):169535.

2. Maoyuan Zhou , Jingjie He, Xingyu Liu, Junmin Huang , Jirui Zhang, Jiaxing Li , Xiaorui Huang, Qianjin Guo,et al. A Semantic Framework for Drug-Target Affinity Prediction Using Mamba and Graph Convolutional Networks for Multimodal Feature Fusion[J]. Chemometrics and Intelligent Laboratory Systems, 2026.

3. Zhenghui Wang, Ruoyan Dai, Kaitai Han, Mengqiu Wang, Lixin Lei, Zhiwei Zhang, Zhenxing Li,Xingyu Liu, jirui Zhang, Han Yan, Qianjin Guo et al. MNiST: A Deep Learning Framework for Multi-Scale Spatial Feature Modeling and Cellular Landscape Decoding in Spatial[J]. Knowledge-Based Systems, 2025,328: 114233.

4. Zhenxing Li, Kaitai Han,Zijun Wang, Lixin Lei, Zhenghui Wang, Ruoyan Dai, Mengqiu Wang,Zhiwei Zhang, Qianjin Guo et al. Enhanced inhibitor–kinase affinity prediction via integrated multimodal analysis of drug molecule and protein sequence features[J]. International Journal of Biological Macromolecules, 2025, 309: 142871.

5.Zhiwei Zhang , Mengqiu Wang , Xinxin Zhang , Ruoyan Dai , Zhenghui Wang , Lixin Lei , Zhenxing Li, Kaitai Han, Zijun Wang, Chaojing Shi , Qianjin Guo. SpaOmicsVAE: A Deep Learning Framework for Integrative Analysis of Spatial Multi-omics Data[J]. Computer Methods and Programs in Biomedicine, 2025,271: 109032.

6.Zijun Wang, Xi Liu, Kaitai Han, Lixin Lei, Chaojing Shi, Wu Liu, Qianjin Guo. Multimodal deep learning for immunotherapy response prediction and biomarker discovery in non-small cell lung cancer[J]. Journal of the American Medical Informatics Association, 2025,32(11):1641-1653.

7.Mengqiu Wang, Zhiwei Zhang, Xinxin Zhang, Zhenghui Wang, Ruoyan Dai, Zeyao Chen,  Lixin Lei, Zhenxing Li, Qianjin Guo. STELLA: A spatial transcriptomics framework for microenvironment decoding using dynamic graph neural networks[J]. SCIENCE CHINA Life Sciences,2025,doi:10.1007/s11427-025-3126-7.

8.Maoyuan Zhou , Jingjie He, Xingyu Liu, Junmin Huang , Jirui Zhang, Jiaxing Li , Xiaorui Huang , Qianjin Guo. Affinity prediction of inhibitor-kinase based on mixture of experts enhanced by multimodal feature semantic analysis[J]. International Journal of Biological Macromolecules, 2025, 321(2):146324.

9.Mengqiu Wang , Zhiwei Zhang , Lixin Lei , Kaitai Han , Zhenghui Wang , Ruoyan Dai , Zijun Wang , Chaojing Shi , Xudong Zhao , Qianjin Guo. VARGG: A Deep Learning Framework Advancing Precise Spatial Domain Identification and Cellular Heterogeneity Analysis in Spatial Transcriptomics[J]. Briefings in Functional Genomics,2025,24: elaf018.

10.Lixin Lei, Qianjin Guo,Wu Liu, Zijun Wang, Kaitai Han, Chaojing Shi, Zhenxing Li, Sichao Lu, Mengqiu Wang, Zhiwei Zhang, Ruoyan Dai, Zhenghui Wang, Xingyu Liu. A novel deep learning framework for predicting protein-ligand interaction fingerprints from sequence data: integrating graph inductive bias transformer with Kolmogorov-Arnold networks[J]. Computational Toxicology, 2025: 100386.

11.Zhenghui Wang, Ruoyan Dai, Mengqiu Wang, Lixin Lei, Zhiwei Zhang, Kaitai Han, Zijun Wang, Qianjin Guo. KanCell: dissecting cellular heterogeneity in biological tissues through integrated single-cell and spatial transcriptomics[J]. Journal of Genetics and Genomics, 2025,52(5):689-705.

12.Ruoyan Dai, Zhenghui Wang, Zhiwei Zhang, Lixin Lei, Mengqiu Wang, Kaitai Han, Zijun Wang, Zhenxing Li, Jirui Zhang, Qianjin Guo. GraphCellNet: A deep learning method for integrated single?cell and spatial transcriptomic analysis with applications in development and disease[J].Journal of Molecular Medicine, 2025, 103(9): 1087-1111.

13.Shitou Liu, Guocheng Sun, Xi Liu, Qianjin Guo. Architectural order identification across label-free living cell imaging with a swin transformer-conditional GAN[J]. Biomedical Physics & Engineering Express, 2025, 11(3): 035001.

14.Zhiwei Zhang, Mengqiu Wang, Ruoyan Dai, Zhenghui Wang, Lixin Lei, Xudong Zhao, Kaitai Han, Chaojing Shi, Qianjin Guo. GraphCVAE: Uncovering cell heterogeneity and therapeutic target discovery through residual and contrastive learning[J]. Life Sciences, 2024, 359: 123208.

15.Mengyuan Huang, Kaitai Han, Wu Liu, Zijun Wang, Xi Liu, Qianjin Guo, et al. Advancing microplastic surveillance through photoacoustic imaging and deep learning techniques[J]. Journal of Hazardous Materials, 2024, 470: 134188

16.Kaitai Han, Chaojing Shi, Zijun Wang, Wu Liu, Zhenxing Li, Zhenghui Wang, Lixin Lei, Ruoyan Dai, Mengqiu Wang, Zhiwei Zhang, Qianjin Guo. Innovative Mamba and graph transformer framework for superior protein-ligand affinity prediction[J]. Microchemical Journal, 2024, 206: 111444.

17.Kaitai Han, Mengyuan Huang, Zhenghui Wang, Chaojing Shi, Zijun Wang,Wu Liu, Lixin Lei, Qianjin Guo et al. Innovative methods for microplastic characterization and detection: Deep learning supported by photoacoustic imaging and automated pre-processing data[J]. Journal of Environmental Management, 2024, 359: 120954.

18.Zijun Wang , Kaitai Han, Wu Liu, Zhenghui Wang, Chaojing Shi, Xi Liu, Mengyuan Huang, Guocheng Sun, Shitou Liu, Qianjin Guo. Fast real-time brain tumor detection based on stimulated raman histology and self-supervised deep learning model[J]. Journal of Imaging Informatics in Medicine, 2024, 37(3): 1160-1176.

19.Kaitai Han, Xi Liu , Guocheng Sun, Zijun Wang , Chaojing Shi, Wu Liu, Mengyuan Huang, Shitou Liu, Qianjin Guo. Enhancing subcellular protein localization mapping analysis using Sc2promap utilizing attention mechanisms[J]. Biochimica et Biophysica Acta (BBA)-General Subjects, 2024, 1868(6): 130601.

20.Lixin Lei , Kaitai Han, Zijun Wang , Chaojing Shi, Zhenghui Wang, Ruoyan Dai, Zhiwei Zhang, Mengqiu Wang, Qianjin Guo. Attention-guided variational graph autoencoders reveal heterogeneity in spatial transcriptomics[J]. Briefings in Bioinformatics, 2024, 25(3): bbae173.2023.

21.Chaojing Shi, Guocheng Sun, Kaitai Han, Mengyuan Huang, Wu Liu, Xi Liu, Zijun Wang, Qianjin Guo. Reconstructing 3D Biomedical Architectural Order at Multiple Spatial Scales with Multimodal Stack Input[J]. Journal of Bionic Engineering, 2024, 21(5): 2587-2601.

22.Xudong Zhao, Shuguo Hu , Zhiwei Zhang, Mengqiu Wang, Ruoyan Dai, Lixin Lei, Zhenghui Wang, Chaojun Niu, Qianjin Guo. Multi-scale wavelet network for high-quality sparse photoacoustic imaging[C],Second International Academic Conference on Optics and Photonics (IACOP 2024). SPIE, 2025, 13541: 1354102.

23.Mengyuan Huang, Wu Liu, Guocheng Sun, Chaojing Shi, Xi Liu, Kaitai Han, Shitou Liu, Zijun Wang, Zhennian Xie, Qianjin Guo. Unveiling precision: a data-driven approach to enhance photoacoustic imaging with sparse data[J]. Biomedical Optics Express, 2024, 15(1): 28-43.

24.Shitou Liu, Guocheng Sun, Yanbing Chen, Mengyuan Huang, Kaitai Han, Li Li, Qianjin Guo. Swin Transformer Based Neural Network for Protein Subcellular Localization Prediction from Quantitative Label-Free Imaging with Phase and Polarization (QLIPP) in Unlabeled Live Cells and Tissue Slices[C]//BIBE 2024; The 7th International Conference on Biological Information and Biomedical Engineering. VDE, 2024: 202-211.

25.Guocheng Sun, Shitou Liu, Chaojing Shi, Xi Liu, Qianjin Guo. 3DCNAS: A universal method for predicting the location of fluorescent organelles in living cells in three-dimensional space[J].Experimental Cell Research.2023,113807.  

 

V. Admissions Information

Currently recruiting Master's students in:

• Control Science and Engineering (0811, Academic Degree)
• Electronic Information (0854, Professional Degree)

Students with backgrounds in artificial intelligence, computer science and technology, bioinformatics, mechatronics, optoelectronics, precision instruments, energy and environmental engineering, or related disciplines are warmly welcomed to apply.

Contact:  guoqianjin@bipt.edu.cn