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  • 姓名:Andrei Alekseevich Korobeinikov
  • 性别:Male
  • 职称:Professor
  • 职务:
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性别 Male 职称 Professor
职务 邮箱
工作室

基本情况

  • 1、Educational Experience:

  • University of Auckland, Mathematics, PhD,2001.

  • 2、Work Experience:

  • Tomsk State University, Russia, 1987-1996.

  • Peter Read Consultancy Ltd., New Zealand, 2001.

  • Centre for Mathematical Biology, Mathematical Institute, the University of Oxford, UK, 2002-2004

  • Research Institute for Electronic Science, Hokkaido University, Japan, 2004-2007

  • Mathematics Applications Consortium for Science and Industry,University of Limerick, Ireland, 2007-2012

  • Centre de Recerca Matemàtica, Barcelona, Spain, 2012-2020

代表性学术论文

  • 1. Stability of a stochastically perturbed model of intracellular single-stranded RNA virus replication, Journal of Biological Systems 27, 2019, L. Shaikhet, S.F. Elena and A. Korobeinikov*

  • 2. Singularly Perturbed Systems, Multiscale Phenomena and Hysteresis: Theory and Applications, Trends in Mathematics vol. 11, Springer-Birkhäuser, Basel, 2019 ,A. Korobeinikov*, M. Caubergh, T. Lázaro and J. Sardanyés, (Editors)

  • 3. Immune response and within-host viral evolution: immune response can accelerate evolution, J. Theor. Biol. 456 doi: 10.1016/j.jtbi.2018.08.003, 2018, A. Korobeinikov*

  • 4. Optimal controls for an SEIR epidemic model with nonlinear incidence rate, Studies in Applied Mathematics 141, 2018, E.V. Grigorieva, E.N. Khailov and A. Korobeinikov*

  • 5. mathematical model of marine bacteriophage evolution, R. Soc. open sci. 5: 171661, 2018, S. Pagliarini and A. Korobeinikov*

  • 6. Slow-Fast Systems and Hysteresis: Theory and Applications, Trends in Mathematics vol. 10, Springer-Birkhäuser, Basel, 2018, A. Korobeinikov (Editor)

  • 7. Memory and adaptive behavior and in population dynamics: Anti-predator behavior as a case study, J. Math. Biol. 74(6), 1533-1559, 2017, A. Pimenov, T.C. Kelly, A. Korobeinikov, M.J.A. O'Callaghan, D. Rachinskii*

  • 8. Paradox of enrichment and system order reduction: bacteriophages dynamics as case study, Math. Med. Biol. 33, 359-369, 2016, A. Korobeinikov*, E. Shchepakina and V. Sobolev

  • 9. Optimal control for a SIR epidemic model with nonlinear incidence rate, Math. Model. Nat. Phenom. 11 (4), 89-104, 2016, E.V. Grigorieva, E.N. Khailov and A. Korobeinikov*

  • 10. Stability of a stochastic model for HIV-1 dynamics within a host, Applicable Analysis 95 (6), 1228-1238 , 2016, L. Shaikhet and A. Korobeinikov*

  • 11. Order reduction for an RNA virus evolution model, Math. Biosci. Eng. 12 (5), 1007-1016 , 2015, A. Korobeinikov*, A. Archibasov and V. Sobolev

  • 12. Adaptive behaviour and multiple equilibrium states in a predator-prey model, Theoretical Population Biology 101, 24-30, 2015, A. Pimenov, T.C. Kelly, A. Korobeinikov*, M.J.A. O'Callaghan and D. Rachinskii

  • 13. Virus Dynamics and Evolution, Trends in Mathematics vol. 4, Springer-Birkhäuser, Basel,2015, A. Korobeinikov (Editor)

  • 14. Age-dependency in host-vector models:the global analysis, Appl. Math. Comput. 243, 969-981 , 2014,  C. Vargas-De-León*, L. Esteva and A. Korobeinikov

  • 15. A continuous phenotype space model of RNA virus evolution within a host, Math. Biosci. Eng. 11(4), 919-927, 2014, A. Korobeinikov* and C. Dempsey

  • 16. Emergence, Spread and Control of Infectious Diseases, Trends in Mathematics vol.2, Springer-Birkhäuser, Base, 2014, A. Korobeinikov (Editor)

  • 17. HIV evolution and progression of the infection to AIDS. , J. Theor. Biol. 307 149-159, 2012, G. Huang*, Y. Takeuchi and A. Korobeinikov

  • 18, Global asymptotic properties of staged models with multiple progression pathways for infectious diseases, Mathematical Biosciences & Engineering, 8(4), 1019-1034, 2011, A.V. Melnik and A. Korobeinikov*

Field of Expertise:

  • 1、The research field is mathematical modeling in life science, nature and engineering, and analysis of differential equations (PDE and ODE). Currently, the most interesting areas include:

  • 1.1.Mathematical Modeling in Evolutionary Biology (Especially Virus Evolution and Cancer Evolution).

  • 1.2.The application of optimal control theory in biological processes, especially in the control of infectious diseases (especially antiviral and cancer treatment) of groups and individuals in biological processes.

  • 1.3.Nonlinear dynamic systems (non-linear PDE and ODE): global qualitative analysis, especially in the fields of stability of solutions; Lyapunov method; bifurcation theory; singular perturbation control systems (slow-fast and multi-scale), and the existence of solutions with special properties and stability mainly applied to mathematical biology.

  • 1.4.Mathematical epidemiology, including the emergence and transmission of pathogens; evolution of pathogens; persistence of pathogens and stability of host microsatellite systems; immune response and control of infectious diseases.

  • 1.5.Mathematical medicine and other fields of biology, such as population dynamics, systems biology and ecology, pest control.

  • 1.6.Bioengineering, biotechnology and chemical kinetics.

  • 2、Research directions include the following aspects:

  • 2.1.The main research directions and interests are the mathematical models of viral and microbial evolution and cancer evolution. The motivation for choosing viruses as case studies lies in their obvious practical relevance, because evolution is the most important factor leading to the emergence of new pathogens and the development of existing drug resistance. In addition, because of its simplicity, viruses are an excellent experimental model in evolutionary biology. In the future, as the possibilities of mathematical modeling and the correlation of results in evolutionary biology become more and more well known in the wider mathematical community, interest in this field will explode. The research directions are Santiago Elena (Evolutionary Systems Virology Group, Institute de Biologfa Molecular y Celular de Plan_tas, Valencia), Jianhong Wu (Director of the Laboratory for Industry and Applied Mathematics at York University), Vladimir Sobolev and Elena Shchepakina (the Samara State). Airspace University, Russia, and Graeme Wake (Massey University, New Zealand).

  • 2.2.The second research direction is to study the optimal control of infectious diseases and cancer control (optimal treatment) at the level of a single population and a single host. The purpose of this study is to use the toolbox of optimal control theory to help develop a timely (in a sense) antiviral and anticancer therapy and a reasonable strategy for controlling infectious diseases. The research direction is in collaboration with Dr. Ramon Alemany (Catalan Institute of Oncol_ogy), Dr. Alena Gros (Vall d'Hebron Institute of Oncology, Barcelona), Professor Ellina Grigorieva (Texas Woman University) and Professor Evgeni Khilov (the Moscow State).

  • 2.3.The third research direction is to study the stability and persistence of pathogens in population and host, the stability and persistence of biological system, and the persistence of immune response. Collaborations in this direction include Cruz Vargas-de Leon and Dr. Lourdes Esteva (Departamento de Matematicas, UN AM, Distrito Federal, Mexico), Dr. Dolors Vaque, Dr. Elena Lara and Dr. Elisabet SA (Departament de Biologia Marina I Oceanografia, Institut de Ciencies del Mar-CMIMA, CSIC, Barona), Dr. Michael O'Callaghan and Dr. Tom Kelly (University College Cork), Professor Dmitry Rachinskiy (University of Texas at Dallas), and Dr. Alexander Pimenov (Weierstrass Institute, Berlin).

  • 2.4.The development of AIDS and the failure of its immune response. Working with IMIM and Hospital del Mar, Professor Jose Miguel Lopez Botet of Barcelona, Professor Yasuhiro Takeuchi of Aoyama Gakuin University and Professor Leonid Shaikhet of Tel Aviv University and Israel.

  • 3、Achievements:

  • 3.1.Established the international network and reputation of mathematical biology. Joining MASCI in 2007, as an important member of MASCI, has made an important contribution to MASCI becoming a successful international research center. In 2012, he joined CRM to establish and lead the Mathematical Epidemiology Research Group.

  • 3.2.With rich experience in multidisciplinary and interdisciplinary cooperation, he has led many research projects and research groups, and is the main organizer and participant of many academic seminars.

  • 3.3.Published more than 120 articles, of which more than 100 have been published since 2000.

  • 3.4.In MACSI, he was responsible for supervising doctoral and post-doctoral programs, and trained many successful doctoral and post-doctoral programs.

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