Dr. Jana Gevertz                        
Associate Professor 
The College of New Jersey
Department of Mathematics and Statistics
Science Complex P247
Phone: 609-771-3314
Email: gevertz {at} tcnj {dot} edu

Curriculum Vitae

About Me

My research interests are primarily in the field of mathematical oncology.  This is a subfield of mathematical biology in which tools from applied and computational mathematics are used to understand cancer initiation, progression and treatment.  I also have a strong interest in deeply engaging undergraduate mathematical biology experiences, both in the classroom and in intensive rese
arch experiences.  

I received my undergraduate degree in Mathematics with a minor in Biology from Rutgers University.  My Ph.D. in Applied and Computational Mathematics was done under the supervision of Dr. Salvatore Torquato at Princeton University.


  1. J.L. Gevertz, 2016. Microenvironment-Mediated Modeling of Tumor Response to Vascular-Targeting Drugs, chapter X of Systems Biology of Tumor Microenvironment: Quantitative Modeling and Simulations, (ed. K.A. Rejniak), Springer, pp. 191-208.
  2. J. Perez-Velazquez, J.L. Gevertz, A. Karolak and K.A. Rejniak, 2016. Microenvironmental Niches and Sanctuaries: A Route to Acquired Resistance, chapter VIII of Systems Biology of Tumor Microenvironment: Quantitative Modeling and Simulations, (ed. K.A. Rejniak), Springer, pp. 149-164.
  3. A.B. Shah, K.A. Rejniak and J.L. Gevertz, 2016. Limiting the development of anti-cancer drug resistance in a spatial model of micrometastases. Mathem. Biosci. Eng.  13: 1185-1206.
  4. J.L. Gevertz, P.S. Kim and J.R. Wares. Mentoring undergraduate interdisciplinary mathematics research students: junior faculty experiences. In press at Problems, Resources, and Issues in Mathematics Undergraduate Studies (accepted May 2016).
  5. J.L. Gevertz and C. Wang, 2016. Finding causative genes from high-dimensional data: an appraisal of statistical and machine learning approaches. Stat. Appl. Genet. Mol. Biol. 15: 321-347.
  6. J.R. Wares, J.J. Crivelli, C.O. Yun, I.K. Choi, J.L. Gevertz and P.S. Kim, 2015. Treatment strategies for combining immunostimulatory oncolytic virus therapeutics with dendritic cell injections. Mathem. Biosci. Eng. 12: 1237-1256.
  7. J.L. Gevertz, Z. Aminzare, K. Norton, J. Perez-Velazquez, A. Volkening and K.A. Rejniak, 2015. Emergence of anti-cancer drug resistance: Exploring the importance of the microenvironmental niche and tumor heterogeneity through a spatial model. In "Applications of Dynamical Systems in Biology and Medicine”, IMA Volumes in Mathematics and its Applications, vol 158, Springer-Verlag, A. Radunskaya and T. Jackson (Eds.).
  8. J.C. Beier, J.L. Gevertz and K.E. Howard, 2015. Building context with tumor growth modeling projects in differential equations. PRIMUS 25: 297-325.
    (If you don't have access to PRIMUS, clicking here will get the first 50 individuals a free copy of the paper)
  9. J.L. Gevertz, 2012.  Optimization of vascular-targeting drugs in a computational model of tumor growthPhys. Rev. E 85: 041914. 
  10. J. L.  Gevertz, 2011.  Computational modeling of tumor response to vascular-targeting therapies: I. Validation Comp. Math. Meth. Med. 2011: 830515.
  11. J.L. Gevertz and S. Torquato, 2009.  Growing heterogeneous tumors in silicoPhys. Rev. E 80: 051910.   
  12. J.L. Gevertz and S. Torquato, 2009.  Mean survival times of absorbing triply periodic minimal surfacesPhys. Rev. E 80: 011102.
  13. J.L. Gevertz, G. Gillies and S. Torquato, 2008.  Simulating tumor growth in confined heterogeneous environmentsPhys. Biol. 5: 036010.
  14. J.L. Gevertz and S. Torquato, 2008.  A novel three-phase model of brain tissue microstructurePLoS Comput. Biol. 4: e1000152.
  15. J.L. Gevertz and S. Torquato, 2006.  Modeling the effects of vasculature evolution on early brain tumor growthJ. Theor. Biol. 243: 517-531.
  16. J.L. Gevertz, S. Dunn and C.M. Roth, 2005. Mathematical models of real-time PCR kineticsBiotech. Bioeng. 92: 346-355.
  17. J. Gevertz, H.H. Gan and T. Schlick, 2005.  In vitro RNA random pools are not structurally diverse: a computational analysisRNA 11: 853-863.

Conferences & Workshops I've attended or will be attending


Links for Students