I am a Professor of Physics at Lycoming College. My research focuses on nonlinear and complex systems.

Research Interests

  • Nonlinear Time Series Analysis
    • Ordinal Symbolization (Bandt-Pompe Methodology)
    • Ordinal Transition Networks
    • Distinguishing between different dynamical behaviors
  • Machine Learning
    • Using ML for time series characterization and prediction
    • Using ML to solve problems in the natural and social sciences
  • Complex Systems
    • Using ML to design intelligent agent-based models
    • Dynamics on networks
  • Economics
    • the effect of taxation and redistribution on the distribution of wealth

Recent Publications

  1. C. W. Kulp and V. Pagonis, Classical Mechanics: A Computational Approach, CRC Press (2020).
  2. C. W. Kulp, M. Kurtz, N. Wilston, and L. Quigley, The effect of various tax and redistribution models on the Gini coefficient of simple exchange games, Chaos 29, 083118 (2019).
  3. A. N. Pisarchik, G. Heurtas, and C. W. Kulp, Statistical analysis of symbolic dynamics in weakly coupled chaotic oscillators, Communications in Nonlinear Science and Numerical Simulation 62, 134–145 (2018). 
  4. C. W. Kulp, L. Zunino, T. Osborne, and B. Zawadzki, Using missing ordinal patterns to detect nonlinearity in time series data, Physical Review E 96 022218 (2017).
  5. L. Zunino and C. W. Kulp, Detecting nonlinearity in short and noisy time series using the permutation entropy, Physics Letters A 381, 3627–3635 (2017).