Taylor T Johnson
Scholar

Taylor T Johnson

Google Scholar ID: MdTkXNYAAAAJ
Associate Professor, Computer Science, Vanderbilt University
formal methodshybrid systemsformal verificationsafe AItrustworthy AI
Citations & Impact
All-time
Citations
4,936
 
H-index
37
 
i10-index
77
 
Publications
20
 
Co-authors
55
list available
Publications
20 items
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
  • Published around a hundred papers, with three recognized with best/outstanding paper awards from IEEE and IFIP, and two awarded Best Software Repeatability/Artifact Awards. Recipient of the AFOSR Young Investigator Program (YIP) award in 2016 and 2018, and the NSF CISE Research Initiation Initiative (CRII) in 2015. His research is supported by AFRL, AFOSR, ARO, DARPA, NSA, NSF, NVIDIA, ONR, Toyota, and USDOT.
Research Experience
  • Currently an Associate Professor in the Departments of Computer Science and Electrical and Computer Engineering at Vanderbilt University, where he also serves as the Director of Graduate Studies (CS PhD) and directs the Verification and Validation for Intelligent and Trustworthy Autonomy Laboratory (VeriVITAL). Previously, he was an Assistant Professor of Computer Science and Engineering at the University of Texas at Arlington (September 2013 to August 2016).
Education
  • PhD in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign in 2013, under Prof. Sayan Mitra; MSc in ECE from the same university in 2010; BSEE from Rice University in 2008.
Background
  • Research Interests: Developing formal verification techniques and software tools for cyber-physical systems (CPS), with a focus on autonomous CPS that incorporate AI and ML components. Professional Fields: Computer Science, Electrical and Computer Engineering.
Miscellany
  • Co-founder of the Verification of Neural Networks Competition (VNN-COMP) and the International Competition on Verifying Continuous and Hybrid Systems (ARCH-COMP) category on Artificial Intelligence and Neural Network Control Systems (AINNCS).