PeopleofSuperintelligence

Researcher

J. D. Tygar

Also known as Doug Tygar, J. Doug Tygar, Justin Douglas Tygar

Doug Tygar was a UC Berkeley professor of computer science and of information whose security research reached machine learning. After a B.A. at Berkeley in 1982 and a Ph.D. at Harvard in 1986, he taught at Carnegie Mellon University from 1986 and returned to Berkeley in 1998. His 1999 paper with Alma Whitten, "Why Johnny Can't Encrypt," helped launch usable security and won the 2015 USENIX Security Test of Time Award, and in 2000 he coauthored the TESLA paper on authenticating broadcast streams. In 2004 he co-founded the Secure Machine Learning research group, whose study of how adversaries manipulate learning algorithms culminated in the 2019 book Adversarial Machine Learning, written with Anthony Joseph, Blaine Nelson and Benjamin Rubinstein. He died in 2020.

Born
1962
Died
2020
Badges

Years link to their sources.

Timeline

  1. 1982–1986

    Degrees from Berkeley and Harvard

    He earns a B.A. in mathematics and computer science from UC Berkeley in 1982 and a Ph.D. in computer science from Harvard University in 1986.

  2. 1986–1998

    Faculty at Carnegie Mellon

    In 1986, he joins the faculty of Carnegie Mellon University, where he is tenured faculty in the Computer Science Department. He receives the National Science Foundation's Presidential Young Investigator Award in 1988.

  3. 1998–2020

    Professor at Berkeley

    He returns to Berkeley in 1998 with a joint appointment in the School of Information and the Department of Electrical Engineering and Computer Sciences. Over his career, he designs cryptographic postage standards for the US Postal Service and helps build systems including Strongbox, Dyad, Netbill and Micro-Tesla.

  4. 1999

    Why Johnny Can't Encrypt

    With Alma Whitten, he publishes a usability evaluation of PGP 5.0 at the 8th USENIX Security Symposium in 1999. When test participants have 90 minutes to sign and encrypt a message, the majority cannot do so, and the paper helps launch the field of usable security.

  5. 2000

    The TESLA authentication system

    In 2000, he coauthors "Efficient Authentication and Signing of Multicast Streams over Lossy Channels" with Adrian Perrig, Ran Canetti and Dawn Song. Its core contribution is TESLA, a system for authenticating broadcast messages, also called multicast streams.

  6. 2004–2019

    Secure machine learning research

    He co-founds the Secure Machine Learning research group in 2004, which studies how machine learning algorithms can be dishonestly manipulated and how to make them more robust. In 2006, he coauthors "Can machine learning be secure?" with Barreno, Nelson, Sears and Joseph. In 2019, Cambridge University Press publishes Adversarial Machine Learning, which he coauthors with Anthony D. Joseph, Blaine Nelson and Benjamin I. P. Rubinstein.

  7. 2015

    USENIX Test of Time Award

    He receives the 2015 USENIX Security Test of Time Award for "Why Johnny Can't Encrypt." The paper analyzes the importance of user interface and user experience design for the success of computer security applications.

  8. 2020

    A TESLA award and his death

    He dies unexpectedly on January 16, 2020, and the TESLA paper he coauthored wins a Test-of-Time award at the IEEE Symposium on Security and Privacy in 2020.

Career

  1. From 2004Secure Machine Learning Research GroupCo-founder
  2. 1998–2020University of California, BerkeleyProfessor
  3. 1986–1998Carnegie Mellon UniversityTenured faculty

Education

  1. 1986Harvard UniversityPh.D.
  2. 1982University of California, BerkeleyB.A.

From the biography.

  1. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes University of California, Berkeley. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  2. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes University of California, Berkeley. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  3. The median h-index is 48 at universities and 14 at frontier AI labsIncludes University of California, Berkeley. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  4. Companies supply the most prior-work hires at 7 of the 9 frontier AI labsIncludes University of California, Berkeley. Our estimates of the organizations where 550 people worked directly before joining 9 frontier AI labs across 620 career transitions, comparing the main feeder organizations per lab.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

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  1. Justin Douglas Tygar, In Memoriam, University of California Academic Senate senate.universityofcalifornia.edu. Checked 21 October 2026.
  2. Tygar: Biography people.eecs.berkeley.edu. Checked 21 October 2026.
  3. Why Johnny Can't Encrypt: A Usability Evaluation of PGP 5.0 | USENIX usenix.org. Checked 21 October 2026.
  4. Five CMU Security and Privacy Papers Receive IEEE's Test of Time Award ece.cmu.edu. Checked 21 October 2026.
  5. Four papers authored by EECS faculty win Test-of-Time Awards at 2020 IEEE-SP - EECS at Berkeley eecs.berkeley.edu. Checked 21 October 2026.
  6. Doug Tygar has passed away - EECS at Berkeley eecs.berkeley.edu. Checked 21 October 2026.
  7. Tygar: publications people.eecs.berkeley.edu. Checked 21 October 2026.
  8. Introduction (Chapter 1) - Adversarial Machine Learning cambridge.org. Checked 21 October 2026.
  9. Why Johnny Can't Encrypt: Doug Tygar's Landmark Paper Stands the Test of Time | UC Berkeley School of Information ischool.berkeley.edu. Checked 21 October 2026.