Summary
Joshua Tan is a research scientist in security and privacy with 13 years of experience blending data analysis and software engineering, currently conducting applied research at Amazon after a postdoc at Carnegie Mellon’s CyLab. He holds a Ph.D. in Computer Science from Carnegie Mellon and has a track record of moving academic research into practical systems through internships at MIT Lincoln Laboratory and UC Berkeley and engineering experience at Thomson Reuters. Joshua’s work spans threat modeling, privacy-preserving analytics, and secure systems design, with hands-on skills across research, prototyping, and productionization. Based in Greater Boston, he brings a rare combination of rigorous academic training and industry-focused implementation, often translating complex security research into deployable tools and data-driven insights.
13 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at Carnegie Mellon University
Bachelor of Science (B.S.), Computer Science, Bachelor of Science (B.S.), Computer Science at North Dakota State University