Steven Lin
Product Developer at Synology
Taipei, Taiwan
Summary
👤
Senior🎓
Top SchoolSteven Lin is a product developer and cybersecurity master's student at NTU with 10 years of engineering experience and a 4+ year focus on Linux ELF reverse engineering, vulnerability exploitation, and CTF competition as a BambooFox team member. At Synology he builds product-grade solutions while his prior roles—research intern at CyCraft and multiple teaching assistant positions—reflect strong applied research and mentorship in malware analysis, secure programming, and incident response tooling. He pairs hands-on red-team skills with automation and machine learning techniques to streamline detection and analysis workflows, and has contributed QA and test automation to the well-known golearn ML project. Known for quickly adopting new tools and designing practical problem-solving methods, he also brings systems-level experience from maintaining FreeBSD builders and CI/CD pipelines. Based in Taipei, Steven blends academic rigor (NTU GPA 4.17) with real-world product delivery and a penchant for visualizing and scoring process-level threats to increase explainability.
10 years of coding experience
2 years of employment as a software developer
Bachelor's degree, Computer Science, GPA: 4.04, Bachelor's degree, Computer Science, GPA: 4.04 at National Chiao Tung UniversityMaster's degree, Cybersecurity, GPA: 4.17, Master's degree, Cybersecurity, GPA: 4.17 at National Taiwan UniversitySenior High School, 1331 1340, Senior High School, 1331 1340 at HSNU - The Affiliated Senior High School of National Taiwan Normal University
Chinese, English
Github Skills (8)
machine-learning10
go10
test-automation10
testing10
cross-validation9
metric9
evaluation9
pca9
Programming languages (8)
Github contributions (5)
sjwhitworth/golearn
Jun 2018 - Jun 2018
Machine Learning for Go
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:12 commits, 1 PR in 12 days
Contributions summary:Steven primarily contributed to the project by adding and modifying test cases. These tests cover various aspects of the codebase, including PCA, confusion matrices, cross-fold validation, and matrix operations. The commits demonstrate a focus on ensuring the correctness and reliability of the machine learning functionalities implemented in the golearn repository through comprehensive testing.
golangmachine-learningdata-science
ss8651twtw/blog
May 2018 - Jun 2018
Contributions:32 commits, 22 pushes, 5 branches in 1 month
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