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Michael Kane is an Assistant Professor of Civil and Environmental Engineering at Northeastern University where his research and teaching focus on human-in-the-loop control of civil infrastructure. Prior to joining Northeastern, he served as a Fellow at the U.S. Department of Energy’s (DoE) Advanced Research Project Agency - Energy (ARPA-E) where he identified new technology development opportunities for control of civil energy infrastructure, primarily in the areas of transportation, buildings, and distributed energy resources. In 2014, he finished a PhD at the University of Michigan where he pursued novel ways of embedding computational intelligence into civil systems in the Laboratory for Intelligent Systems and Technology (LIST). Outside the office and lab, he enjoys cycling, games of ultimate, skiing, and backpacking.


  • PhD, Civil and Environmental Engineering, University of Michigan, 2014
  • MS, Electrical Engineering, University of Michigan, 2011
  • MS, Civil Engineering, Drexel University, 2009
  • BS, Architectural Engineering, Drexel University, 2009

Research & Scholarship Interests

model predictive control; wireless control systems; automatic control of complex infrastructure systems
Affiliated With

Department Research Areas

Professional Affiliations

  • American Society of Civil Engineers (ASCE)
  • Institute of Electrical and Electronics Engineers (IEEE)

Selected Publications

  • M.B. Kane, L.P. Jerome, J. Scruggs, Development of a Scalable Distributed Model Predictive Control System for Hydronic Networks with Bilinear and Hybrid Dynamics, Journal of Computing in Civil Engineering, 32(5), 2018, 04018038
  • M. B. Kane, Modeling Human-in-the-Loop Behavior and Interactions with HVAC Systems, American Control Conference (ACC), IEEE, 2018, 6
  • M.B. Kane, C. Peckens, “Digital Control Systems”, Chapter in Marks’ Standard Handbook for Mechanical Engineers, McGraw-Hill Professional, 2017, 1257-1265
  • M.W. Häckell, R. Rolfes, M.B. Kane, J.P. Lynch, Three-Tier Modular Structural Health Monitoring Framework Using Environmental and Operational Condition Clustering for Data Normalization: Validation on an Operational Wind Turbine System, Proceedings of the IEEE, 108(8), 2016, 1-15
  • M.B. Kane, J. Scruggs, J.P. Lynch, Model-predictive Control Techniques for Hydronic Systems Implemented on Wireless Sensor and Actuator Networks, 2014 American Control Conference, 2014, 3542-3547
See Google Scholar Profile for all publications »

Related News

January 20, 2017

Michael Kane joins the Civl & Environmental Engineering department in January 2017 as an Assistant Professor.