Yike Shi
Research Assistant Intern at Carnegie Mellon University
Pittsburgh, Pennsylvania, United States
Summary
👤
Senior🎓
Top SchoolYike Shi is a Carnegie Mellon junior studying Computer Science with a 4.0 GPA who blends strong systems and algorithms coursework with hands-on AI infrastructure and HCI research experience. They have optimized GPU inference kernels (int4/int8) and profiled real-world pipelines to improve latency at DeepLang, and built a web platform that treats requirements as first-class entities to streamline LLM prompt engineering at CMU HCI. Comfortable across systems programming, databases, and web development, Yike also brings a design-minded developer perspective from their GitHub bio, helping craft user-facing tools like visual feedback and interactive validation. Based in Pittsburgh, they pair rigorous academic achievement with practical deployment experience and a knack for turning high-level requirements into verifiable, iterated AI workflows.
10 years of coding experience
1 year of employment as a software developer
Bachelor of Science - BS, Computer Science, 4.0, Bachelor of Science - BS, Computer Science, 4.0 at Carnegie Mellon UniversityHigh School Diploma, High School Diploma at Keystone Academy, BeijingProgramming languages (4)
Github contributions (5)
ecaps1038/yike
Jan 2019 - May 2020
Contributions:5 commits, 80 pushes, 3 branches in 1 year 4 months
ecaps1038/yktime
Apr 2019 - Mar 2020
Contributions:24 pushes, 2 branches in 11 months
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