Sachit Butail, Ph.D.

Title: Associate Professor
Department: Mechanical Engineering
Office Location: EB 148
Office Phone: 815-753-9987


  • Ph.D. in Aerospace Engineering, University of Maryland (2012)
  • M. Eng. in Systems Engineering, Cornell University (2005)
  • B.E. in Mechanical Engineering, Delhi University, New Delhi, India (2000)

Research Interests

  • Dynamical systems
  • Robotics
  • Complex systems
  • Collective behavior
  • Bioinspired autonomy
  • Pattern recognition

Selected Projects

  • Human-assisted robotic sampling of aquatic microorganisms, funded by Illinois-Indiana Sea Grant
  • Cues and actions for efficient nonverbal human-robot communication, funded by National Science Foundation
  • Agent-based Modeling Toward Effective Testing and Contact-tracing During the COVID-19 Pandemic, funded by National Science Foundation

Selected Publications

  • Krzysiak and S. Butail. Information based control of robots in search and rescue missions with human prior knowledge. IEEE Transactions on Human-Machine Systems, 52(1), 52-63, 2022
  • Truszkowska, M. Thakore, L. Zino, S. Butail, E. Caroppo, Z.-P. Jiang, A. Rizzo, and M. Porfiri. Designing the safe reopening of US towns through high-resolution agent-based modeling. Advanced Theory and Simulations, 4(9), 202100157, 2021
  • Sathish, M. Norrlof, M. Orkisz, and S. Butail. A Transfer Entropy Based Approach for Fault Isolation in Industrial Robots. ASME Letters in Dynamic Systems and Control, 2(1), 011009, 2021.
  • Sathish, M. Orkisz, M. Norrlof, and S. Butail. Data-driven gearbox failure detection in industrial robots. IEEE Transactions on Industrial Informatics, 16(1), 193-201, 2020.
  • Butail and M. Porfiri. Detecting switching leadership in collective motion. Chaos: An Interdisciplinary Journal of Nonlinear Science 29, 011102, 2019
  • Roy, K. Howes, R. Muller, S. Butail and N. Abaid. Extracting interactions between flying bat pairs using model-free methods. Entropy, 21(1), 2019
  • M. Jorjafki, B. J. Sagarin, and S. Butail. Drawing power of virtual crowds. Journal of the Royal Society Interface, 15 (145), 2018
  • Mwaffo, S. Butail, and M. Porfiri. Analysis of pairwise interactions in a maximum likelihood sense to identify leaders in a group. Frontiers in Robotics and AI, 4, 2017
  • Macri, D. Neri, T. Ruberto, S. Butail, V. Mwaffo and M. Porfiri. Three-dimensional scoring of zebrafish behavior unveils biological phenomena hidden by two-dimensional analyses. Scientific Reports 7(1), 2017
  • Mwaffo, S. Butail, and M. Porfiri. In-silico experiments of zebrafish behaviour: modelling swimming in three dimensions. Scientific Reports 4(39877), 2017
  • Butail, V. Mwaffo, and M. Porfiri. Model-free information-theoretic approach to infer leadership in pairs of zebrafish. Physical Review E, 93(4) 042411, 2016

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