Peter Cao is a PhD precandidate in Computer Science and Engineering at the University of Michigan who builds hardware-software co-design systems for efficient ML workloads, combining compiler work with computer architecture research. He graduated from Cornell with a dual background in CS and Applied Physics, and brings eight years of engineering and research experience across industry internships (Google, Apple) and multiple university labs. His work spans from implementing ECMAScript features in the widely used Google Closure Compiler to designing Halide-like scheduling languages and performance tooling for ML compilers and simulators. At Michigan he collaborates with national labs to optimize indirect memory accesses, reflecting a pragmatic focus on systems that bridge theory and deployable performance. A long-time educator and course staffer, he also has deep teaching experience in algorithms, systems, and ML coursework for large undergraduate classes. He is motivated by making STEM education accessible while accelerating ML and quantum workloads through co-designed hardware and compiler innovation.
8 years of coding experience
2 years of employment as a software developer
High School Diploma General Studies, High School Diploma General Studies at Center High School
Physics and CS, Physics and CS at Mission College
Doctor of Philosophy - PhD Computer Science and Engineering, Doctor of Philosophy - PhD Computer Science and Engineering at University of Michigan
Mathematics and Computer Science, Mathematics and Computer Science at Sierra College
Bachelor of Science - BS Computer Science and Physics, Bachelor of Science - BS Computer Science and Physics at Cornell University
Spanish, English, Vietnamese, French
Github Skills (6)
closure10
google-closure-compiler10
javascript10
optimization10
testing9
type-checking9
Programming languages (8)
TypeScriptJavaOCamlJavaScriptHTMLJupyter NotebookRich Text FormatPython
Contributions summary:Peter primarily contributed to the Closure Compiler project by implementing and refining core JavaScript language features. Their work involved adding support for ES2022 features, specifically the `cause` property for `Error` objects and supporting class static blocks. The commits included modifications to existing files, such as the `externs/es3.js` to extend the `Error` prototype, and the creation of unit tests, ensuring the implemented features worked as intended. This included the addition of new test cases and refactoring existing ones to test features like static block support.
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