Scholar
Scott Coull
Google Scholar ID: l4WN96YAAAAJ
Google
Citations & Impact
Citations
1,969
H-index
17
i10-index
23
Publications
20
Co-authors
35
list available
Publications
Resume (English only)
Academic Achievements
- Published multiple journal articles and book chapters, such as 'Solving Domain-Specific Problems Using LLMs' and 'Traffic Analysis'; involved in various research projects including automating security operations, detecting malicious Windows binaries, and circumventing Internet censorship.
Research Experience
- Currently leads the Google Cloud Security Data Science Research group; previously a senior research scientist at RedJack; also worked as a researcher at Mandiant.
Education
- Ph.D. in Computer Science from Johns Hopkins University, advised by Prof. Fabian Monrose; M.Sc. and B.Sc. from Rensselaer Polytechnic Institute, advised by Prof. Boleslaw Szymanski; NSF/CRA Computing Innovation Fellow at the University of North Carolina - Chapel Hill, mentored by Prof. Michael Reiter.
Background
- Research interests focus on the use of data mining, machine learning, and cryptography to protect users from a variety of attacks and violations of their privacy. Recently, he has been working on understanding how machine learning, particularly deep learning, can be used to detect attacks and the practical limitations of that technology when attackers try to evade detection.
Miscellany
- As an applied research scientist, he not only develops privacy-enhancing technologies and cutting-edge security tools but also breaks existing systems to understand their weaknesses and ultimately improve their security.
