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

Data proxies, the cognitive layer, and application locality: Enablers of cloud-connected vehicles and next-generation internet of things

PhD Thesis, Massachusetts Institute of Technology, 2016
Siegel, Joshua Eric

Merging safety and cybersecurity analysis in product design

IET Intelligent Transport Systems, 12(9): 1103—1109, 2018
D. Suo and J. E. Siegel and S. E. Sarma

Towards Industrial IoT-AR Systems using Deep Learning-Based Object Pose Estimation

In 2019 IEEE 38th International Performance Computing and Communications Conference (IPCCC), 2019
Sun, Yongbin and Kantareddy, Sai Nithin Reddy and Siegel, Joshua and Armengol-Urpi, Alexandre and Wu, Xiaoyu and Wang, Hongyu and Sarma, Sanjay

List of Publications

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

Explore

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
Research Projects