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Evan Haskell, Ph.D.

Dept. of Mathematics
(954) 262-8164


  • Ph.D. Mathematics, New York University (2000)
  • B.S. Mathematics, New York University (1995)

Research Interest(s):

  • Complex Systems
  • Modeling and Simulation
  • Computational Science  & Scientific computing
  • Applied identifiability analysis and model selection
  • Applied mathematics

Courses Taught:

  • Calculus I & II
  • Mathematics and Biology
  • Ordinary Differential Equations
  • Numerical Methods

My research is in analysis, modeling, simulation, and model analysis for complex systems with a focus on those arising from natural, engineered, and social systems.

Selected Peer-reviewed publications:

  1.  A.R. Arenas, N. B. Thackar, and E.C. Haskell, The logistic growth model as an approximating model for viral load measurements of influenza A virus, Mathematics and Computers in Simulation, 133:206-222, 2017.

  2. O.R. Bracho, C. Manchery, E.C. Haskell, C.A. Blanar, and R.P. Smith, Circumvention of learning increases intoxication efficacy of nematicidal engineered bacteria, ACS synthetic biology, 5:241-249, 2016.

  3. E. C. Haskell, A social interaction model for crime hot spots, Proceedings  European Council on Modeling and Simulation,  28:745-751, 2014.

  4. R. P. Smith and E. C. Haskell, Connecting mathematics and biology in the classroom: exploring the hero’s journey through ecological relationships, Proceedings Biomathematics and Ecology, Education and Research,1:122-135, 2014.

  5. E. Haskell, D.Q. Nykamp, and D. Tranchina, Population Density Methods for Large-Scale Modeling of Neuronal Networks with Realistic Synaptic Kinetics: Cutting the Dimension Down to Size Network: Computation in Neural Systems,12:141-174, 2001.

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