Yulun Yao
Graduate Research Assistant
City of Ithaca, New York, United States
Summary
👤
Senior🎓
Top SchoolYulun Yao is a PhD student and graduate research assistant at Cornell University specializing in designing programming languages for secure, verifiable hardware under Prof. Andrew C. Myers. With eight years of experience across research and industry, he has worked on machine learning compilers and hardware accelerators at AWS, UIUC, and UW, bringing a systems-minded approach to language-based security. His work sits at the intersection of PL, computer architecture, and security, translating formal ideas into practical tools for hardware assurance. Based in Ithaca, he combines deep academic rigor with production-facing engineering experience, having contributed to ML compiler and accelerator projects during internships and research. Notably, his focus on language-driven security for hardware highlights a less obvious but critical angle: preventing vulnerabilities at the design level rather than solely through later verification.
8 years of coding experience
3 years of employment as a software developer
High School Diploma, High School Diploma at High School Affiliated to Shanghai Jiao Tong UniversityDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Cornell UniversityBachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at University of Illinois Urbana-Champaign
English, Chinese
Github Skills (40)
tvm10
opencl10
vulkan10
javascript10
cpu10
gpu-programming10
machine-learning10
metal10
deep-learning10
gpu10
spirv9
intermediate9
compiler-construction9
compiler9
gpu-acceleration8
Programming languages (8)
Github contributions (5)
yy665/PDL
Sep 2021 - Oct 2023
A Hardware Pipeline Description Language
Contributions:18 pushes, 2 branches in 2 years
language-descriptionhardwarepipeline
yuluny2/tvm
Jul 2019 - Jan 2020
Open deep learning compiler stack for cpu, gpu and specialized accelerators
Contributions:32 pushes, 7 branches in 5 months
cpugpu-programminggpu-accelerationtvmdeep-learning
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