doi.bio/daniel_guo

Zhaohan Daniel Guo

Zhaohan Daniel Guo is a researcher and scientist with a background in computer science, software engineering, and security. He is currently working as an Applied Scientist at Amazon Web Services (AWS) Proactive Security, focusing on cloud-scale application security.

Education

Guo received his Bachelor of Science (B.S.) and Master of Science (M.S.) degrees in Software Engineering from Wuhan University. He then obtained his Ph.D. from the Department of Electrical and Computer Engineering (ECE) at Virginia Tech, under the guidance of Dr. Chao Wang and Dr. Michael Hsiao.

Career

Before joining Amazon, Guo worked as a Security Researcher at Baidu Research Silicon Valley. He has also held positions at the University of Toronto and the Government of Canada, where he gained experience in data analysis and developed skills in programming languages such as Python, R, and SQL.

Research Interests and Publications

Guo's research interests include program analysis, software security, and cloud security. He has had several papers accepted and published in renowned conferences and journals, including:

"Mitigating Silent Data Corruptions in HPC Applications across Multiple Program Inputs" (SC' 22)
"Disclosing the Pringles Syndrome in Tesla FSD Vehicles" (AutoSec' 2022)
"A System-Driven Evaluation Platform for Auto-driving Safety and Security" (AutoSec' 2022)
"Challenging Machine Learning-based Clone Detectors via Semantic-preserving Code Transformations" (TSE)
"A Survey on Automated Driving System Testing: Landscapes and Trends" (TOSEM)

Guo has also contributed to research in reinforcement learning and self-supervised learning, with publications such as "Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning" and "Understanding Self-Predictive Learning for Reinforcement Learning."

Zhaohan Daniel Guo

Overview

Zhaohan Daniel Guo is a researcher and data analyst with a background in computer science, mathematics, and statistics. His work focuses on machine learning, reinforcement learning, and data security.

Education

Guo received his Bachelor's degree in Mathematics and Statistics from the University of Toronto. He then went on to pursue graduate studies in Computer Science at Stanford University, where he is currently a Master's student. Guo also holds a Ph.D. from the ECE Department of Virginia Tech, as well as B.S. and M.S. degrees in Software Engineering from Wuhan University.

Professional Experience

Currently, Guo is an Applied Scientist at Amazon Web Services (AWS) Proactive Security, a position he has held since 2022. Prior to joining Amazon, he worked as a Security Researcher with Baidu Research Silicon Valley.

Research Interests and Publications

Guo's research interests include program analysis, software security, and cloud security. He has published several papers in renowned conferences and journals, including the ACM SIGSOFT Distinguished Paper Award-winning work on "Fine-Grained Search in WSAM Symbolic Execution." He has also presented at workshops and conferences, including the Amazon FReE Workshop and AutoSec, where his work on "Disclosing the Pringles Syndrome in Tesla FSD Vehicles" received the "Best Demo Award."

Conclusion

Zhaohan Daniel Guo is a rising researcher and scientist in the fields of computer science and data analysis, with a particular focus on machine learning and data security. His contributions to the field have been recognized through awards and publications, and he actively continues his research endeavors with Amazon Web Services.