David Darais

Adjunct Assistant Professor, Computer Science

David Darais
Alma mater(s)
  • University of Utah, B.S.
  • Harvard University, M.S
  • University of Maryland, Ph.D.

BIO

David is Adjunct Assistant Professor at the University of Vermont and Principal Scientist at Galois, Inc., an R&D lab that specializes in secure software development. David builds new programming languages and analysis tools that help programmers build reliable software for security-sensitive and privacy-sensitive applications. In particular, David's tools focus on symbolic software analysis methods to prove the absence of entire classes of defects, i.e., not just fixing the next bug, but showing the absence of the last bug.

Courses

  • UVM CS 225: Programming Languages / Spring 2020
  • UVM CS 295A: Software Verification / Fall 2019
  • UVM CS 225: Programming Languages / Spring 2019
  • UVM CS 295A: Software Verification / Fall 2018
  • UVM CS 225: Programming Languages / Spring 2018

Publications

Publications located on David Darias's website

Area(s) of expertise

Programming analysis, mechanized proofs, software defined networking, differential privacy, secure multiparty computation.

Bio

David is Adjunct Assistant Professor at the University of Vermont and Principal Scientist at Galois, Inc., an R&D lab that specializes in secure software development. David builds new programming languages and analysis tools that help programmers build reliable software for security-sensitive and privacy-sensitive applications. In particular, David's tools focus on symbolic software analysis methods to prove the absence of entire classes of defects, i.e., not just fixing the next bug, but showing the absence of the last bug.

Courses

  • UVM CS 225: Programming Languages / Spring 2020
  • UVM CS 295A: Software Verification / Fall 2019
  • UVM CS 225: Programming Languages / Spring 2019
  • UVM CS 295A: Software Verification / Fall 2018
  • UVM CS 225: Programming Languages / Spring 2018

Areas of Expertise

Programming analysis, mechanized proofs, software defined networking, differential privacy, secure multiparty computation.