Current Professional Societies

1. Executive member of the Block-chain Commission, Executive Member of the Data Governance Development Commission, and outstanding member of China Computer Federation;

2. Member of the Federal Data and Federal Intelligence Committee of the Chinese Society of Automation；

3. Executive director of the Disability Statistics Branch of National Statistical Society of China;

4. Executive Director of the Disability Statistics Branch of the Chinese Statistical Society;

5. Senior member of the Chinese Institute of Electronics;

6. Vice President of Beijing Information and Telecommunication Association;

7. Board member of Beijing Institute of Bigdata;

8. Member of Editorial Board of Journal of Artificial Intelligence for Medical Sciences.

Research Areas

1. Smart city spatial-temporal bigdata;

2. Bigdata computing & data intelligence

3. Blockchain and data govenance;

4. Internet of things (IoT) & intellisense.

Honors

1. The first prize in the Innovation Group of the 6th PIESAT & Huawei Cloud Cup PIE System Development Competition, awarded by the Chinese Society of Surveying and Mapping in 2023.

2. Gold Award in the First National Postdoctoral Innovation and Entrepreneurship Competition Leading Question Competition awarded by the Ministry of Human Resources and Social Security in 2021.

3. The third prize of Science and Technology Award of Beijing Municipality in 2010;

4. The second prize of Geographic Information Science and Technology Progress Award in 2010，awarded by National  Administration of Surveying, Mapping and Geoinformation of China and CAGIS (China Association for Geographic Information Society);

5. The honorary title of "advanced individual of Beijing Olympic Games and Paralympic Games" by Beijing Municipal Committee and government in 2008;

6. The honorary title of "advanced individual of fighting against SARS" by Beijing Municipal Committee and government in 2003;

7. The first prize of Construction Achievements of State Economic Information System, awarded by State Information Center in 1997.

Major Publications in Recent 5 years

1. Lin, S., Yang, Y., Liu, X., Tian, L., 2025. DSFA-SwinNet: A Multi-Scale Attention Fusion Network for Photovoltaic Areas Detection. Remote Sensing, 17(2), 332.

2. Lin, S., Zhou, S., jiao, H.et al. CDR-Detector: achronic disease risk prediction modelcombining pre-trainingwith deepreinforcementlearning. Complex Intell. Syst. 11,104(2025).

3. Lin, S.; Yan, H.; Zhou, S.; Qiao, Z.; Chen, J. HRP-OG: Online Learning with Generative Feature Replay for Hypertension Risk Prediction in a Nonstationary Environment. Sensors 2024, 24, 5033.

4. Lin, S.; Zhang, Y.; Liu, X.; Mei, Q.; Zhi, X.; Fei, X. Incorporating the Third Law of Geography with Spatial Attention Module–Convolutional Neural Network–Transformer for Fine-Grained Non-Stationary Air Quality Predictive Learning. Mathematics 2024, 12, 1457.

5. Lin, S.; Zhang, Y.; Fei, X.; Liu, X.; Mei, Q. ConvFormer-KDE: A Long-Term Point–Interval Prediction Framework for PM2.5 Based on Multi-Source Spatial and Temporal Data. Toxics 2024, 12, 554.

6. Huang, L., Lin, S., Liu, X., Wang, S., Chen, G., Mei, Q., & Fu, Z. (2024). The Cost of Urban Renewal: Annual Construction Waste Estimation via Multi-Scale Target Information Extraction and Attention-Enhanced Networks in Changping District, Beijing. Remote Sensing, 16(11), 1889.

7. Lin, S., Huang, L., Liu, X., Chen, G., & Fu, Z. (2024). A construction waste landfill dataset of two districts in Beijing, China from high resolution satellite images. Scientific Data, 11(1), 388.

8. Lin, S.; Yao, X.; Liu, X.; Wang, S.; Chen, H.-M.; Ding, L.; Zhang, J.; Chen, G.; Mei, Q. MS-AGAN: Road Extraction via Multi-Scale Information Fusion and Asymmetric Generative Adversarial Networks from High-Resolution Remote Sensing Images under Complex Backgrounds. Remote Sensing. 2023, 15, 3367.

9. Zhao, X., Hua-Min, C., Lin, S., Li, H., & Chen, T. (2024). A Novel Design for Joint Collaborative NOMA Transmission with a Two–Hop Multi–Path UE Aggregation Mechanism. Symmetry (Basel), 16(8), 1052.

10. Lin, S., Zhang, C., Ding, L., Zhang, J., Liu, X., Chen, G., Wang, S. and Chai, J., 2022. Accurate Recognition of Building Rooftops and Assessment of Long-Term Carbon Emission Reduction from Rooftop Solar Photovoltaic Systems Fusing GF-2 and Multi-Source Data. Remote Sensing, 14(13), p.3144.

11. Lin, S., Fang, W., Wu, X., Chen, Y. and Huang, Z., 2018. A spark-based high performance computational approach for simulating typhoon wind fields. IEEE Access, 6, pp.39072-39085.

12. Zhang, J., Lin, S., Ding, L. and Bruzzone, L., 2020. Multi-scale context aggregation for semantic segmentation of remote sensing images. Remote Sensing, 12(4), p.701.

13. Ding, L., Lin, D., Lin, S., Zhang, J., Cui, X., Wang, Y., Tang, H. and Bruzzone, L., Looking outside the window: Wide-context transformer for the semantic segmentation of high-resolution remote sensing images. arXiv 2021. arXiv preprint arXiv:2106.15754.

14. Lin, S., Zhao, J., Li, J., Liu, X., Zhang, Y., Wang, S., Mei, Q., Chen, Z. and Gao, Y., 2022. A Spatial–Temporal Causal Convolution Network Framework for Accurate and Fine-Grained PM2. 5 Concentration Prediction. Entropy, 24(8), p.1125.

15. Liu, X., Zhao, J., Lin, S., Li, J., Wang, S., Zhang, Y., Gao, Y. and Chai, J., 2022. Fine-Grained Individual Air Quality Index (IAQI) Prediction Based on Spatial-Temporal Causal Convolution Network: A Case Study of Shanghai. Atmosphere, 13(6), p.959.

16. Wu, Y., Lin, S., Peng, F. and Li, Q., 2019. Methods and application of archeological cloud platform for grand sites based on spatio-temporal big data. ISPRS International journal of geo-information, 8(9), p.377.

17. Lin, S., Xu, Z., Sheng, Y., Chen, L. and Chen, J., 2022. AT-NeuroEAE: A Joint Extraction Model of Events With Attributes for Research Sharing-Oriented Neuroimaging Provenance Construction. Frontiers in Neuroscience, 15, p.1863.

18. Lin, S., Fu, Y., Jia, X., Ding, S., Wu, Y. and Huang, Z., 2020. Discovering correlations between the COVID-19 epidemic spread and climate. International Journal of Environmental Research and Public Health, 17(21), p.7958.

19. Fu, Y., Lin, S. and Xu, Z., 2022. Research on Quantitative Analysis of Multiple Factors Affecting COVID-19 Spread. International Journal of Environmental Research and Public Health, 19(6), p.3187.

20. Lin, S., Shi, C. and Chen, J., 2022. GeneralizedDTA: combining pre-training and multi-task learning to predict drug-target binding affinity for unknown drug discovery. BMC bioinformatics, 23(1), pp.1-17.

21. Lin, S., Wang, M., Shi, C., Xu, Z., Chen, L., Gao, Q. and Chen, J., 2022. MR-KPA: medication recommendation by combining knowledge-enhanced pre-training with a deep adversarial network. BMC bioinformatics, 23(1), pp.1-19.

22. Guo, C., Lin, S., Huang, Z. and Yao, Y., 2022. Analysis of sentiment changes in online messages of depression patients before and during the COVID-19 epidemic based on BERT+ BiLSTM. Health information science and systems, 10(1), p.15.

23. Lin, S., Gao, J., Zhang, S., He, X., Sheng, Y. and Chen, J., 2020. A continuous learning method for recognizing named entities by integrating domain contextual relevance measurement and Web farming mode of Web intelligence. World Wide Web, 23, pp.1769-1790.

24. Sheng, Y., Chen, J., He, X., Xu, Z., Gao, J. and Lin, S., 2020. A topic learning pipeline for curating brain cognitive researches. IEEE Access, 8, pp.191758-191774.

25. Chen, H.M., Huang, S., Wang, P., Chen, T., Fang, C., Lin, S. and Li, F., 2022. A Joint Positioning Algorithm in Industrial IoT Environments with mm-Wave Communications. Symmetry, 14(7), p.1335.

26. Chen, H.M., Wang, S.F., Wang, P., Lin, S. and Fang, C., 2022. Deep Q-learning for intelligent band coordination in 5g heterogeneous network supporting v2x communication. Wireless Communications and Mobile Computing, 2022.

27. Siyu, Q.I., Shuopeng, L.I., Shaofu, L.I.N., Saidi, M.Y. and Ken, C.H.E.N., 2021, September. Energy-efficient VNF deployment for graph-structured SFC based on graph neural network and constrained deep reinforcement learning. In 2021 22nd Asia-Pacific Network Operations and Management Symposium (APNOMS) (pp. 348-353). IEEE.

28. Yao, Y., Lin, S., Huang, Z., Li, S., Guo, C. and Wu, Y., 2022, October. Research on the Construction of Psychological Crisis Intervention Strategy Service System. In Health Information Science: 11th International Conference, HIS 2022, Virtual Event, October 28–30, 2022, Proceedings (pp. 209-216). Cham: Springer Nature Switzerland.

29. Jing, X., Lin, S. and Huang, Z., 2021. Research on Suicide Identification Method Based on Microblog “Tree Hole” Crowd. In Health Information Science: 10th International Conference, HIS 2021, Melbourne, VIC, Australia, October 25–28, 2021, Proceedings 10 (pp. 141-149). Springer International Publishing.

30. Wang, M., Chen, J. and Lin, S., 2021, December. Medication recommendation based on a knowledge-enhanced pre-training model. In IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (pp. 290-294).

31. Chang, X., Lin, S. and Liu, X., 2022, September. TISM-CAE: A Fast Unsupervised Learning Method for Trajectory Similarity Measure via Convolutional Auto-Encoder. In Proceedings of the 7th International Conference on Cyber Security and Information Engineering (pp. 140-148).

32. Lin, S., Li, Y., Chen, H., Li, J. and Jia, X., 2021, November. Personal Trajectory Verification Based on Blockchain and Zero-knowledge Proof. In 2021 2nd International Conference on Computer Science and Management Technology (ICCSMT) (pp. 493-497). IEEE.

33. Zhao, J., Lin, S., Liu, X., Chen, J., Zhang, Y. and Mei, Q., 2021, November. ST-CCN-PM2. 5: Fine-grained PM2. 5 concentration prediction via spatial-temporal causal convolution network. In Proceedings of the 4th ACM SIGSPATIAL International Workshop on Advances in Resilient and Intelligent Cities (pp. 48-55).

34. Jing, X., Lin, S. and Huang, Z., 2020. Research on the behavior pattern of microblog “tree hole” users with their temporal characteristics. In Health Information Science: 9th International Conference, HIS 2020, Amsterdam, The Netherlands, October 20–23, 2020, Proceedings 9 (pp. 25-34). Springer International Publishing.

35. Lin, S., Li, J. and Liang, W., 2020, June. Research on strong supervision algorithm model based on blockchain in e-government. In 2020 IEEE 5th Information Technology and Mechatronics Engineering Conference (ITOEC) (pp. 345-349). IEEE.

Personal statement

Shaofu Lin, professor, doctoral and master supervisor at Computer College, Beijing University of Technology. He ever held the posts of executive vice dean of Beijing Institute of Smart City and executive director of Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology. He has ever participated in the construction of smart Beijing and played a major role in the activities of anti-SARS and the Beijing Olympic Games and so on. He has presided over and participated in 4 projects of 863 Plan and 8 projects of Beijing Science and Technology Plan. He has also presided over more than 30 related research projects of the topics such as smart city of the sub center of Beijing city, smart venues for 2022 Beijing Winter Olympic Games, green smart village, AI for mental health and etc. He has presided over the establishment of 3 local standards and participated in the setting of 9 national and local standards. He has won 3 provincial and ministerial first-level prizes, 2 second-level prizes and 1 third-level prize. He has published more than 90 papers on international academic journals, conferences and Chinese core journals. He has obtained over 20 authorized international patents and national invention patents.