Short Biography

Josh Siegel is an Assistant Professor in Computer Science and Engineering at Michigan State University and the lead instructor for the Massachusetts Institute of Technology’s Internet of Things and DeepTech Bootcamps. He received Ph.D., S.M. and S.B. degrees in Mechanical Engineering from MIT.

Josh and his automotive companies have been recognized with accolades including the Lemelson-MIT Student Prize and the MassIT Government Innovation Prize. He has multiple issued patents, published in top scholarly venues, and been featured in popular media. Dr. Siegel’s ongoing research develops architectures for secure and efficient connectivity, applications for pervasive sensing, and new approaches to autonomous driving.

Academic Positions

  • 2019 - Present Assistant Professor

    Michigan State University
    Computer Science and Engineering

  • 2017-2018 Research Scientist

    Massachusetts Institute of Technology
    Department of Mechanical Engineering

  • 2016-2017 Postdoctoral Associate

    Massachusetts Institute of Technology
    Department of Mechanical Engineering

Selected Awards

  • 2018 ICAT-EGVE Best Demo Award
  • 2018 SCF AIMS Best Paper Award
  • 2015 Lemelson-MIT National Collegiate Student Prize Competition “Drive It” Winner
  • 2015 MassIT Government Innovation Competition Winner (CarKnow LLC)
  • 2008 MIT Institute for Soldier Nanotechnologies Soldier Design Competition “Boeing” Prize Winner

Randomly-Selected Publications

This section shows three publications selected from the Publications page at random. It changes with every page reload.

More Publications

“Smartphone-Based Vehicular Tire Pressure and Condition Monitoring”

In "Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016", "2018"
"Siegel, Joshua

Value in vehicles: economic assessment of automotive data

Digital Policy, Regulation and Governance, 20(6): 513—527, 2018
Alexander M. Soley and Joshua E. Siegel and Dajiang Suo and Sanjay E. Sarma

List of Publications

Click here to see the full list of Professor Siegel's publications, with BibTex entries.

Research Projects

  • Cognitive Protection Systems (CPS)
    Generalizable AI-enhanced cybersecurity for constrained IoT devices
  • Pervasive Automotive Sensing Systems (PASS)
    Automotive subsystem fault detection using data from mobile phone sensors
  • Scalable Universal Diagnostic System (SUDS)
    Repurposing “data exhaust” to develop generalized algorithms for monitoring physical, electrical, and chemical systems
  • Physically-Adversarial Intelligent Networks (PAIN)
    Improving autonomous system performance through intentional, real-world adversarial engagement
  • Embedded Intelligence (EI)
    Architecting AI implementation for use on constrained systems