Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China
Department of Computer Science, City University of Hong Kong, Hong Kong
Email: shishaolong@csj.uestc.edu.cn
Biography
Shaolong Shi received the B.Sc. and M.Sc. degrees in control science and engineering from the Harbin Institute of Technology, Harbin, China, in 2014 and 2016, respectively. He received the Ph.D. degree with the Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China, and Harbin Institute of Technology, Harbin, China. His current research interests include computing-inspired biosensing with application to cancer detection, swarm intelligence, and evolutionary nanorobots.
Research Interests
Computational Nanobiosensing
Swarm Intelligence
Evolutionary Nanorobots
Publications
期刊文章
1. S. Shi, Y. Chen, and X. Yao, “NGA-inspired nanorobots-assisted detection of multifocal cancer,” IEEE Transactions on Cybernetics, vol. 52, no. 5, pp. 2787-2797, May 2022, doi: 10.1109/TCYB.2020.3024868. (一区, TOP, IF：19.118)
2. S. Shi, Y. Chen, and X. Yao, “In vivo computing strategies for tumor sensitization and targeting,” IEEE Transactions on Cybernetics, doi: 10.1109/TCYB.2020.3024868. (一区, TOP, IF：19.118)
3. S. Shi, N. Sharifi, Y. Chen, and X. Yao, “Tension-relaxation in vivo computing principle for tumor sensitization and targeting,” IEEE Transactions on Cybernetics, doi: 10.1109/TCYB.2021.3052731. (一区, TOP, IF：19.118)
4. S. Shi, Y. Chen, J. Ding, Q. Liu and Q. Zhang, "Dynamic In Vivo Computation for Learning-based Nanobiosensing in Time-varying Biological Landscapes," in IEEE Transactions on Evolutionary Computation, 2022, doi: 10.1109/TEVC.2022.3198086. (一区, TOP, IF：16.497)
5. S. Shi, Y. Chen, X. Yao, and Q. Liu, “Exponential evolution mechanism for in vivo computation,” Swarm and Evolutionary Computation, vol. 65, pp. 100931, 2021. (一区, TOP，IF：10.267)
6. S. Shi, Y. Yan, J. Xiong, U K. Cheang, X. Yao, and Y. Chen, “Nanorobots-assisted natural computation for multifocal tumor sensitization and targeting,” IEEE Transactions on Nanobioscience, vol. 20, no. 2, pp. 154-165, 2021. (封面、亮点和热点论文，三区, IF: 3.206)
7. S. Shi, N. Sharifi, U K. Cheang, and Y. Chen, “Perspective: computational nanobiosensing,” IEEE Transactions on Nanobioscience, vol. 19, no. 2, pp. 267-269, 2019. (三区, IF: 3.206)
8. S. Shi, J. Xiong, Y. Zhou, T. Jiang, G. Zhu, X. Yao, U K. Cheang, and Y. Chen, “Microrobots based in vivo evolutionary computation in two-dimensional microchannel network,” IEEE Transactions on Nanotechnology, vol. 19, pp. 71-75, 2019. (三区, IF: 2.967)
9. C. Yan, J. Ding*, H. Zhang, K. Tong, B. Hua, and S. Shi*, “SEResU-Net for multimodal brain tumor segmentation,” IEEE Access, 2022. (二区, IF: 3.476)
10. Y. Chen, S. Shi, X. Yao, and T. Nakano, “Touchable computing: computing-inspired bio-detection,” IEEE Transactions on Nanobioscience, vol. 16, no. 8, pp. 810-821, 2017. (三区, IF: 3.206)
11. Y. Chen, M. Ali, S. Shi, and U K. Cheang, “Biosensing-by-learning direct targeting strategy for enhanced tumor sensitization,” IEEE Transactions on Nanobioscience, vol. 18, no. 3, pp. 498-509, 2019. (三区, IF: 3.206)
会议文章
1. S. Shi, Y. Chen, X. Yao, and M. Zhang, “Lightweight evolution strategies for nanoswimmers-oriented in vivo computation,” 2019 IEEE Congress on Evolutionary Computation (CEC), pp. 866-872, 2019.
2. S. Shi, Y. Chen, and X. Yao, “Computing-inspired detection of multiple cancers,” 2018 IEEE International Conference on Communications (ICC), pp. 1-6, 2018.
3. S. Shi, J. Xiong, M. Ali, Y. Chen, U K. Cheang, M. J. Kim, and X. Yao, “Nanorobots-assisted tumor sensitization and targeting for multifocal tumor,” 2020 IEEE 20th International Conference on Nanotechnology (IEEE-NANO), pp. 362-365, 2020.
4. S. Shi, Y. Chen, Z. Gong, X. Lin, N. Sharifi, and X. Yao, “In vivo computation for tumor sensitization and targeting at different tumor growth stages,” 2020 IEEE Congress on Evolutionary Computation (CEC), pp. 1-6, 2020.
5. S. Shi, J. Xiong, Y. Zhou, Y. Chen, and U K. Cheang, “Experimental verification of guidance and search strategy of nanobots under magnetic field control in grid network,” 2019 IEEE 19th International Conference on Nanotechnology (IEEE-NANO), pp. 526-529, 2019.
6. J. Ding, S. Shi*, and Y. Chen, “A Dynamic in vivo computational strategy for tumor targeting,” 2021 International Conference on UK-China Emerging Technologies (UCET), pp. 282-287, 2021.
7. L. Liu, Y. Sun, S. Shi, and Y. Chen, “Smart tumor targeting by reinforcement learning,” 2021 IEEE 15th International Conference on Nano/Molecular Medicine &Engineering (NANOMED), pp. 81-84, 2021.
8. M. Ali, N. McGrath, S. Shi, M. J. Cree, U K. Cheang, Y. Chen, “Bio-inspired self-regulated in-vivo computation for smart cancer detection,” 2020 IEEE 20th International Conference on Nanotechnology (IEEE-NANO), pp. 304-309, 2020.
9. L. Zhang, K. A. Balushi, Z. Gong, S. Shi, Z. Wu, and Y. Chen, “Search space analysis for in vivo computation for smart tumor targeting,” 2021 IEEE 15th International Conference on Nano/Molecular Medicine & Engineering (NANOMED), pp. 11-14, 2021.
10. S. Shi, Y. Chen, Q. Liu, J. Ding, and Q. Zhang, “Dynamic in vivo computation: nanobiosensing from a dynamic optimization perspective,” IEEE World Congress on Computational Intelligence (WCCI 2022), accepted.
11. S. Shi, Z. Wang, Y. Chen, Q. Liu, and Q. Zhang, “A Full-time-utilization Optimization Approach for Computational Nanobiosensing,” 2022 IEEE 22th International Conference on Nanotechnology (IEEE-NANO), accepted.
12. Z. Jiang, S. Shi, Y. Chen, and S. Yao, “Nanobiosensing from an in vivo multi-objective optimization perspective,” 2022 IEEE 22th International Conference on Nanotechnology (IEEE-NANO), accepted.
13. Y. Chen, M. Wu, and S. Shi, “Analog nanobiosensing of continuous disease state: system models and relationships to fuzzy set theory,” 2022 IEEE 22th International Conference on Nanotechnology (IEEE-NANO), accepted.
专利
名称：一种基于群体智能的自然计算方法
发明人：师少龙、陈意钒、刘强、丁菊容
专利号：202111158377.6
申请人：电子科技大学长三角研究院（衢州），电子科技大学，四川轻化工大学
Reviewer
IEEE Trans. on Molecular, Biological, and Multi-Scale Communications , Swarm and Evolutionary Computation, Computers in Biology and Medicine
Member
IEEE member, ETI-MBMC (Emerging Technologies Initiative for Molecular, Biological and Multi-Scale Communications) member
Contact
Address: 1 Chengdian, Kecheng District, Quzhou City, Zhejiang Province
