Dr. Lin Lin is an Associate Professor and Ph.D. Supervisor at the Southern University of Science and Technology (SUSTech). She received her Ph.D. degree from the Department of Mechanical Engineering at The University of Hong Kong. During her doctoral studies, she worked as a visiting research student at the University of Adelaide (Australia), King's College London (UK), and Hokkaido University (Japan). She subsequently held postdoctoral fellow positions at City University of Hong Kong, The University of Hong Kong, and the Multi-Scale Medical Robotics Center.

Her primary research interests include swarm intelligence networks, fully actuated system methods, lightweight control, and medical robotics. She has published over 20 papers as the first author in prestigious international journals such as IEEE Transactions, Automatica, and SICON. Dr. Lin was a receipt of the Excellent Young Scholarship of the National Natural Science of Foundation of China (Overseas), the Humboldt Research Fellowship, IETI PhD Fellowship Award, and Hong Kong Young Scientist Award (Honorable mention in Engineering Science). She currently serves as a secretariat member of International Engineering and Technology Institute, and a Reviewer for Mathematical Reviews (American Mathematical Society) and several journals, including IEEE TRO, TAC, TIFS, TCYB, TNNLS, and TIE. 

Education Background

2021.09 to 2024.04，The University of Hong Kong，Control Engineering，PhD

2018.09 to 2021.06，Southeast University，Applied Mathematics，MSc

2014.09 to 2018.06，Zhejiang Normal University，Applied Mathematics，BSc

Working Experience

2026.02-now，Southern University of Science and Technology，Associate Professor

2025.05 to 2026.02，Multi-Scale Medical Robotics Center，Postdoctoral Fellow

2024.08 to 2025.04，The University of Hong Kong，Postdoctoral Fellow

2024.04 to 2024.08，City University of Hong Kong，Postdoctoral Fellow

Research Area

· Swarm Intelligence Networks

· Fully Actuated System Methods and Applications

· Lightweight Control

· Surgical Robotics

Publications

[1] Lin Lin, James Lam, Peng Shi, Michael K. Ng, and Hak-Keung Lam, “Learning probabilistic logical control networks: From data to controllability and observability,” IEEE Transactions on Automatic Control, 70(6):3889-3904, 2025. (长文)

[2] Lin Lin, Min Meng, Zhan Shu, Zhiyi Zhong, and James Lam, “Algorithms enhancement for optimal triggering control in logical dynamic systems: Leveraging data structure storage,” Automatica, 177:112290, 2025.

[3] Changxi Li, Lin Lin*, Wenjun Xiong, James Lam, and Ka-Wai Kwok, “Continuous-time Markov networks: From merging rules to synchronizing control,” IEEE Transactions on Automatic Control, 70(12):7923-7938, 2025. (长文)

[4] Lin Lin, Jinde Cao, James Lam, Leszek Rutkowski, Georgi Marko Dimirovski, and Shiyong Zhu, “A bisimulation-based foundation for scale reductions of continuous-time Markov chains,” IEEE Transactions on Automatic Control, 69(9):5743-5758, 2024. (长文)

[5] Lin Lin, Jinde Cao, James Lam, Shiyong Zhu, Shun-ichi Azuma, and Leszek Rutkowski, “Leader-follower consensus over finite fields,” IEEE Transactions on Automatic Control, 69(7):4718-4725, 2024.

[6] Lin Lin, James Lam, Min Meng, Xiaochen Xie, Panshuo Li, Daotong Zhang, and Peng Shi, “Stabilization of continuous-time probabilistic logical networks under sampling dwell time constraints,” SIAM Journal on Control and Optimization, 62(2):1006-1033, 2024.

[7] Lin Lin, Jinde Cao, Jianquan Lu, and Leszek Rutkowski, “Set stabilization of large-scale stochastic Boolean networks: A distributed control strategy,” IEEE/CAA Journal of Automatica Sinica, 11(3):806-808, 2024.

[8] Lin Lin, Zhihan Jiang, Hong Lin, Edith C. H. Ngai, and James Lam, “On quotients of stochastic networks over finite fields,” IEEE Transactions on Control of Network Systems, 11(2):878-889, 2024.

[9] Lin Lin and James Lam, “Observability categorization for Boolean control networks,” IEEE Transactions on Network Science and Engineering, 11(1):1374-1386, 2024.

[10] Lin Lin, Jinde Cao, Shiyong Zhu, and Peng Shi, “Synchronization analysis for stochastic networks through finite fields,” IEEE Transactions on Automatic Control, 67(2):1016-1022, 2022. 

Awards

· 2024 Hong Kong Young Scientist Award (Honorable mention in Engineering Science), Hong Kong Institution of Science

· 2024 IETI PhD Fellowship Award, International Engineering and Technology Institute (IETI)

· 2024 Top 10 Technological Advances in Industries, Jiangsu Province, China

· Lotfi Zadeh Best Paper Finalist Award, The 22nd International Conference on Machine Learning and Cybernetics (ICMLC 2023, Australia)

· HKU Outstanding Engineering Thesis Award

· 2023 Outstanding Master Degree Thesis Award, Chinese Institute of Electronics