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. 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.
  2. 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).
  3. 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.
  4. 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.
  5. 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.).
  6. 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)
  7. J.L. Gevertz, 2012.  Optimization of vascular-targeting drugs in a computational model of tumor growthPhys. Rev. E 85: 041914. 
  8. J. L.  Gevertz, 2011.  Computational modeling of tumor response to vascular-targeting therapies: I. Validation Comp. Math. Meth. Med. 2011: 830515.
  9. J.L. Gevertz and S. Torquato, 2009.  Growing heterogeneous tumors in silicoPhys. Rev. E 80: 051910.   
  10. J.L. Gevertz and S. Torquato, 2009.  Mean survival times of absorbing triply periodic minimal surfacesPhys. Rev. E 80: 011102.
  11. J.L. Gevertz, G. Gillies and S. Torquato, 2008.  Simulating tumor growth in confined heterogeneous environmentsPhys. Biol. 5: 036010.
  12. J.L. Gevertz and S. Torquato, 2008.  A novel three-phase model of brain tissue microstructurePLoS Comput. Biol. 4: e1000152.
  13. J.L. Gevertz and S. Torquato, 2006.  Modeling the effects of vasculature evolution on early brain tumor growthJ. Theor. Biol. 243: 517-531.
  14. J.L. Gevertz, S. Dunn and C.M. Roth, 2005. Mathematical models of real-time PCR kineticsBiotech. Bioeng. 92: 346-355.
  15. 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