博士后招聘：

       常年招聘非平衡热力学方向、复杂流体计算方向、大数据人工智能方向的博士后，与美国华盛顿大学西雅图分校钱纮教授联合指导，待遇按照中山大学博士后管理规定从优。

 

研究方向：

        复杂生化反应系统研究，非平衡热力学数学理论及应用，人工智能驱动的科学研究

 

教育经历：

  • 09/2004-06/2009 清华大学周培源应用数学研究中心，理学博士
  • 09/2000-06/2004 北京大学计算机科学与技术系，理学学士
  • 09/2000-06/2004 北京大学数学系, 数学与应用数学第二学位

 

工作经历:

  • 03/2025-至今       中山大学数学学院, 教授
  • 08/2020-03/2025 中山大学数学学院, 副教授
  • 07/2015-07/2016 英国剑桥大学化学系, 访问学者
  • 12/2012-07/2020 清华大学周培源应用数学研究中心, 副研究员
  • 07/2011-12/2012 清华大学周培源应用数学研究中心, 助理研究员
  • 09/2009-09/2010 美国密歇根大学安娜堡分校计算医学与生物信息学中心, 访问学者
  • 07/2009-06/2011 清华大学生物系, 博士后

 

学生指导：

方欣桐、石炴烜（2023-至今，硕士生在读，中山大学）

黎国杰（2022-至今，直博生在读，中山大学）

王梦收（2023-至今，博士生在读，中山大学）

张馨予（2021-至今，直博生在读，中山大学）

邓思为、李疏桐、张艳玲（2022-2024，专业硕士，中山大学）

郝文思、袁典飘（2020-2022，专业硕士，中山大学）

王梦收（2020-2023，学术硕士，中山大学）

周锦娴（2020-2022，专业硕士，中山大学）

杨武岳（2017-2022，理学博士，清华大学，与朱毅教授共同指导）

彭梁榕（2015-2019，理学博士，清华大学）

谭彭振 （2012-2017，理学硕士，清华大学，与雍稳安教授共同指导）

 

课程承担：

非平衡热力学（清华大学，2013年秋、2017年秋）

理论生物学   （清华大学，2014年春，与胡煜成合开）

高等数学      （中山大学，2020年秋、2023年秋）

线性代数      （中山大学，2023年春、2024年春）

概率论-I       （中山大学，2021年秋）

概率统计     （中山大学，2022年春）

实变函数      （中山大学，2021年春、2022年秋、2023年春、2024年春、2025年春）

泛函分析-I    （中山大学，2024年春）

人工智能算法基础(中山大学，2025年春，多人合开)

 

科研项目：

  • 04/2025-12/2026: 广东省动力系统与神经系统交叉研究重点实验室2025年度开放课题. “第一性原理”和数据双驱动的阿尔兹海默症动力学研究(课题负责人).
  • 12/2023-11/2026: 国家重点研发计划–2023YFC2308702. 重大传染病社会数据化治理的智能方法研究与应用示范 (中大子课题负责人).
  • 01/2022-12/2025: 广东基础与应用基础研究基金---2023A1515010157. Aβ多肽聚集诱导神经细胞凋亡的多尺度动力学建模(课题负责人).
  • 01/2019-12/2022: 国家自然科学基金---21877070. 针对蛋白质聚集的抑制剂调控机制的动力学研究 (课题负责人).
  • 01/2017-12/2020: 国家自然科学基金---11671415. 基于液晶理论的生物形态学建模和模拟 (主要参与人).
  • 09/2015-09/2018: 清华大学自主科研项目---20151080424. 非平衡热力学数学基础及应用 (课题负责人).
  • 01/2013-12/2016: 国家自然科学基金---11272169. 造血系统动力学分析与控制策略研究 (主要参与人).
  • 01/2013-12/2015: 国家自然科学基金---11204150. 蛋白质淀粉样纤维形成动力学的建模、分析和预测 (课题负责人).
  • 07/2013-07/2015: 清华大学自主科研项目---20121087902. 复杂流体的数学建模、分析和计算 (主要参与人).

 

发表论文：

人工智能驱动的科学研究：

  1. H.Y. Ma, G.J. Li, H.H. Zhang, F.Y. Li, L. Hong*, Y.W. Zhang*, Q.S. Pu (2025) Rapid and ultra-sensitive detection of foodborne pathogens by deep learning-enhanced microfluidic biosensing. Sensor Actuat. B-Chem. 436: 137646.
  2. Y.X. Shi, W.Y. Yang*, L. Hong* (2025) Extracting interaction kernels for many particle systems by a two-phase approach. Phys. Fluids 37: 033331.
  3. Y.L. Zhang, M.S. Wang, L. Hong* (2024) On solving stiff differential equations in system biology with neural networks. Acta Sci. Nat. Uni. Sun., 63(6): 265-274.
  4. Y. Jiang#, W.Y. Yang#*, Y. Zhu,  L. Hong* (2023) Entropy structure informed learning for solving inverse problems of differential equations. Chaos Sol. Frac. 175: 114057.
  5. P.P. Hu#, W.Y. Yang#, Y. Zhu, L. Hong* (2022) Revealing hidden dynamics from time-series data by ODENet. J. Comp. Phys. 461: 111203.
  6. W.Y. Yang#, L.R. Peng#, Y. Zhu, L. Hong*. (2020) When machine learning meets multiscale modeling in chemical reactions. J. Chem. Phys. 153(9): 094117. (封面文章, 个人推荐)
  7. W.Y. Yang, P.Z. Tan, X.J. Fu, L. Hong*. (2019) Prediction of amyloid aggregation rates by machine learning and feature selection. J. Chem. Phys. 151(8): 084106.

 

非平衡热力学数学理论及应用：

（1）热力学数学理论

  1. X.Y. Zhang, H.Y. Jia, W.Y. Yang, L.R. Peng*, Liu Hong* (2025) Thermodynamics for reduced models of breakable amyloid filaments based on maximum entropy principle. J. Chem. Phys. 162: 164901.
  2. P.L. Rong, L. Hong* (2024) Thermodynamics for reduced models of chemical reactions by PEA and QSSA. Phys. Rev. Res., 6: 013296.
  3. L. Hong*, H. Qian*. (2021) Stochastic dynamics, large deviation principle, and non-equilibrium thermodynamics. Phys. Rev. E. 104: 044113.
  4. L. Hong, H. Qian*. (2020) The statistical foundation of entropy in extended irreversible thermodynamics. J. Phys. A: Stat. Mech. Appl. 53: 425202. (个人推荐)
  5. L. Hong, H. Qian*, L.F. Thompson. (2020) Representations and divergences in the space of probability measures and stochastic thermodynamics. J. Comp. Appl. Math. 376: 112842. 
  6. L.P. Rong, H. Qian*, L. Hong*. (2020) Thermodynamics of Markov processes with non-extensive entropy and free energy. Phys. Rev. E 101(2): 022114.
  7. L.R. Peng, Y. Zhu, L. Hong* (2018) Generalized Onsager's reciprocal relations for the master and Fokker-Planck equations. Phys. Rev. E. 97(6): 062123.
  8. L.R. Peng, Y. Zhu, L. Hong* (2018) The Markov process admits a consistent steady-state thermodynamic formalism. J. Math. Phys. 59(1): 013302.
  9. L. Hong, J. Chen, Y. Zhu, W.A. Yong* (2016) Novel dissipative properties of the master equation. J. Math. Phys. 57(10): 103303.
  10. J.T. Huang, W.A. Yong, L. Hong* (2016) Generalization of the Kullback-Leibler divergence in the Tsallis statistics. J. Math. Anal. Appl. 436(1): 501-512.

（2）复杂流体数学建模

  1. L.P. Rong*, L. Hong*. (2021) Recent advances in conservation-dissipation formalism for irreversible processes. Entropy, 23(11): 1447. (综述)
  2. P.P. Hu, L. Hong, Y. Zhu*. (2020) Linear and nonlinear electromagnetic waves in modulated honeycomb media. Stud. Appl. Math. 144: 18-45.
  3. L.P. Rong, Y.C. Hu, L. Hong*. (2019) Conservation-Dissipation Formalism for soft matter physics: I. Augmentation to Doi's variational approach. Euro. Phys.J. E. 42(6): 73.
  4. L.P. Rong, Y.C. Hu, L. Hong*. (2019) Conservation-Dissipation Formalism for soft matter physics: II. Application to non-isothermal nematic liquid crystals. Euro. Phys. J. E. 42(6): 74.
  5. Y.C. Hu*, L. Hong, W.H. Deng. (2018) Phase transition dynamics and stochastic resonance in topologically confined nematic liquid crystals. Phys. Rev. E. 98(3): 032706.
  6. M. Grmela*, L. Hong, D. Jou, G. Lebon, M. Pavelka (2017) Hamiltonian and Godunov structures of the Grad hierarchy. Phys. Rev. E. 95(3): 033121.
  7. L. Hong*, Z.B. Yang, Y. Zhu, W.A. Yong (2015) A novel construction of thermodynamically compatible models and its correspondence with Boltzmann-equation-based moment-closure hierarchies. J. Non-Equil. Therm. 40(4): 247-256.
  8. Y. Zhu, L. Hong, Z.B. Yang, W.A. Yong* (2015) Conservation-dissipation formalism of irreversible thermodynamics. J. Non-Equil. Therm., 40(2): 67-74. (个人推荐)
  9. L. Hong, C.Y. Wang* (2009) Annular axisymmetric stagnation flow on a moving cylinder. Int. J. Eng. Sci., 47(1): 141-152.
  10. C.Y. Wang*, L. Hong (2006) Similarity solutions of the Navier-Stokes equations. Adv. Mech., 36(1): 31-35.

 

复杂生化反应系统研究：

（1）复杂生化反应动力学

  1. L.R. Peng#, W.Y. Yang#, D.Y. Zhang, C.J. Zhuge*, L. Hong* (2020) Epidemic analysis of COVID-19 in China by dynamical modeling. arXiv:2002.06563. (高引文章)
  2. L.Y. Chen#, Z.Q. Zhang#, Z.H. Wang, L. Hong, H.H. Wang*, J.J. Zhang* (2025) Barrier effects on the kinetics of cohesin-mediated loop extrusion. Biophys. J. 124: 1-16.
  3. D.Y. Zhang#, W.Y. Yang#, W.Q.Wen, L.R. Peng, C.J. Zhuge*, L. Hong* (2024) A datadriven analysis on the mediation effect of compartment models between control measures and COVID-19 epidemics. Heliyon, 10: e33850.
  4. W. Chang, G.Y. He, K. Yan, Z.L. Wang*,  Y.F. Zhang, T.Y. Dong, Y.X. Liu, L.S. Zhang, L. Hong* (2021) Doping control analysis of small peptides in human urine using LC-HRMS with parallel reaction monitoring mode screening and confirmation. Analy. Meth. 13: 5838-5850.
  5. W.Y. Yang#, D.Y. Zhang#, L.R. Peng, C.J. Zhuge*, L. Hong* (2021) Rational evaluation of various epidemic models based on the COVID-19 data of China. Epidemics. 37: 100501.
  6. Y.J. Huang, L. Hong, W.A. Yong* (2015) Partial equilibrium approximations in apoptosis. II. The death-inducing signaling complex subsystem. Math. Biosci. 270: 126-134.

（2）蛋白质聚集及抑制

  1. L. Hong*, C.F. Lee*, Y.J. Huang (2017) Statistical mechanics and kinetics of amyloid fibrillation. Chapter 4, Page 113-186. in Biophysics and Biochemistry of Protein Aggregation, edited by J.M. Yuan & H.X. Zhou, World Scientific Press. (综述)
  2. Y.C. Wang#, S.C. Bai#, X.Y. Hu, J.Y. Lin, W.L. Ye, H.Z. Xie*, L. Hong*, G. Li* (2025) Aβ aggregation inhibition via peptide-conjugated gold nanoclusters: Mechanistic insights and therapeutic potential. Mater. Des. 254: 114032
  3. M.S. Wang, L.R. Peng*, B.G. Jia, Liu Hong*. (2024) Optimal strategy for stabilizing protein folding intermediates. J. Chem. Phys., 161: 164111.
  4. M.S. Wang, G. Li, L.R. Peng, L. Hong*. (2023) Towards optimal control of amyloid fibrillation. Bull. Math. Biol. 85: 99.
  5. L. Dong, H.Z. Xie, L. Jia, L. Hong*, G. Li* (2023) Inhibition of amyloid-β aggregation and cytotoxicity by berbamine hydrochloride. Chem. Eur. J. e202301865.
  6. J.T. Wen, L. Hong, G. Krainer, Q.Q. Yao, T.P.J. Knowles, S. Wu*, S. Perrett*. (2021) Conformational expansion of tau in condensates promotes irreversible aggregation. J. Am. Chem. Soc. 143(33): 13056-13064. (个人推荐)
  7. G. Li*, Y. Zhou, W.Y. Yang, C. Zhang, L. Hong*, L. Jia*. (2021) Inhibitory effects of sulfated polysaccharides from the sea cucumber cucumaria frondosa against Aβ40 aggregation and cytotoxicity. ACS Chem. Neurosci. 12: 1854-1859.
  8. Q.Q. Yao, L. Hong, S. Wu*, S. Perrett*. (2020) Distinct microscopic mechanisms for the accelerated aggregation of pathogenic Tau mutants revealed by kinetic analysis. Phys. Chem. Chem. Phys. 22(14): 7241-7249.
  9. G. Li#, W.Y. Yang#, W.H. Li, Y.Y. Luo, Y.J. Lim, Y. Li, A. Paul, D. Segal, L. Hong*, Y.M. Li* (2020) Rational design of a cocktail of inhibitors against Aβ aggregation. Chem. Eur. J. 26(16): 3499-3503. (热点文章)
  10. Y.J. Lim, W.H. Zhou, G. Li, Z.W. Hu, L. Hong*, X.F. Yu*, Y.M. Li*. (2019) Black phosphorus nanomaterials regulate the aggregation of amyloid-β. ChemNanoMat. 5(5): 606-611.
  11. J.C. Sang, G. Meisl, A.M. Thackray, L. Hong, et al. (2018) Direct observation of murine prion protein replication in vitro. J. Am. Chem. Soc. 140(44): 14789-14798.
  12. G. Li, W.Y. Yang, Y.F. Zhao, Y.X. Chen, L. Hong*, Y.M. Li*. (2018) Differential modulation of the aggregation of N-terminal truncated Aβ using Cucurbiturils. Chem. Eur. J. 24(51): 13647-13653.
  13. F. Kundel, L. Hong, et al. (2018) Measurement of Tau filament fragmentation provides insights into prion-like spreading. ACS Chem. Neurosci. 9(6): 1276-1282.
  14. K. Kamgarparsi, L. Hong, A. Naito, C.L. Brooks III, A. Ramamoorthy* (2017) Growth-incompetent monomers of human calcitonin lead to a noncanonical direct relationship between peptide concentration and aggregation lag time. J. Biol. Chem., 292(36): 14963-14976.
  15. M. Iljina, L. Hong, et al. (2017) Nanobodies raised against monomeric α-synuclein inhibit fibril formation and destabilize toxic oligomeric species. BMC Biol., 15(1): 57.
  16. L. Hong*, Y.J. Huang, W.A. Yong (2015) A kinetic model for cell damage caused by oligomer formation. Biophys. J., 109(7): 1338-1346.
  17. L. Hong*, W.A. Yong (2013) Simple moment-closure model for the self-assembly of breakable amyloid filaments. Biophys. J., 104(3): 533-540. (个人推荐)
  18. P.Z. Tan, L. Hong* (2013) Modeling fibril fragmentation in real-time. J. Chem. Phys., 139: 084904.
  19. X.H. Qi#, L. Hong#, Y. Zhang* (2012) A variational model for oligomer-formation process of GNNQQNY peptide from yeast prion protein Sup35. Biophys. J., 102(3): 597-605.
  20. L. Hong, X.H. Qi, Y. Zhang* (2012) Dissecting the kinetic process of amyloid fiber formation through asymptotic analysis. J. Phys. Chem. B, 116(23): 6611-6617.
  21. L. Hong, X.H. Qi, Y. Zhang* (2011) A lattice-gas model for amyloid fibril aggregation. Europhys. Lett., 94, 68006.

（2）蛋白质结构及动力学

  1. F. Lou#, L. Hong#, S. Wu*, S. Perrett* (2023) Folding pathway and energy landscape of the dimeric multidomain prion protein Ure2 revealed by single molecule analysis. J. Phys. Chem. B.
  2. S. Wu#, L. Hong#, Y.Q. Wang#, Y.J. Qiong, J. Yang, J. Yang, H. Zhang, S. Perrett*. (2020) Kinetics of the conformational cycle of Hsp70 reveals the importance of the dynamic and heterogeneous nature of Hsp70 for its function. Proc. Natl. Acad. Sci. U.S.A. 117(14): 7814-7823. (个人推荐)
  3. Y.W. Zhang, E.V. Yates, L. Hong, et al. (2018) On-chip measurements of protein unfolding from direct observations of micron-scale diffusion. Chem. Sci. 9(14): 3503-3507.
  4. L.L. Kong, K.L. Saar, R. Jacquat, L. Hong et al. (2017) Mechanism of biosurfactant adsorption to oil/water interfaces from millisecond scale tensiometry measurements. Interface Focus, 7(6): 20170013.
  5. L. Hong*, J.Z. Lei (2011) A general shape equation for local regular structure of biomolecular chains. 2011 IEEE Conf. Sys. Biol., 144-148.
  6. L. Hong*, J.Z. Lei* (2009) Scaling law for the radius of gyration of proteins and its dependence on hydrophobicity. J. Poly. Sci. B, 47(2): 207-214. (个人推荐)
  7. L. Hong (2008) A statistical mechanical model for antiparallel beta-sheet/coil equilibrium. J. Chem. Phys., 129(22): 225101.
  8. L. Hong*, J.Z. Lei (2008) Statistical mechanical model for helix-sheet-coil transitions in homopolypeptides. Phys. Rev. E, 78(5): 051904.