Research

Summary

My research is focused on analyzing the dynamics of extreme events and their consequences on the environment. For this task I am using a particular Machine Learning family of models, called Reservoir Computing. More broadly, my interests vary from applications of Machine Learning, to Dynamical Systems and Self Organization. I like every thing computational, and odds are if something has to do with programming I am going to enjoy it.

Pubblications

  • ReservoirComputing.jl: An Efficient and Modular Library for Reservoir Computing Models [arXiv] [pdf],
    Martinuzzi, F., Rackauckas, C., AbdelRehim, A., Mahecha, M. D. and Mora, K.
    Journal of Machine Learning Research (2022)

  • Composable and Reusable Neural Surrogates to Predict System Response of Causal Model Components [pdf]
    Anantharaman, R., AbdelRehim, A., Martinuzzi, F., Yalburgi, S., Fischer, K., Hertz, G., de Vos, P., Laughman, C., Ma, Y., Shah, V., Edelman, A. and Rackauckas, C.
    AAAI 2022 Workshop on AI for Design and Manufacturing (ADAM), (2022)

  • Composing Modeling and Simulation with Machine Learning in Julia [arXiv]
    Rackauckas, C., Anantharaman, R., Edelman, A., Gowda, S., Gwozdz, M., Jain, A., Laughman, C., Ma, Y., Martinuzzi, F., Pal, A., Rajput, U., Saba, E. and Shah, V. B.
    14th Modelica Conference 2021, (2021)

Talks

  • Chaotic time series predictions with ReservoirComputing.jl. [Video]
    JuliaCon 2021, (2021)

Notable Software

  • ReservoirComputing.jl: Julia implementation of a vast range of different Reservoir Computing algorithms.
  • CellularAutomata.jl: lightweight Julia implementation of Cellular Automata, both one dimensional and two dimensional.

Conferences and Summer Schools