Shawn Xiao is a Machine Learning Engineer based in Cupertino with 7 years of experience building multimodal AI that improves consumer-facing experiences, from generative Vision Pro research to advancing Siri’s natural intelligence. He blends production ML at Apple with rigorous academic research at Carnegie Mellon, where he explored learnable tool memories for multimodal agents and improved multimodal QA performance. Comfortable across systems and languages, Shawn is a Rust and OCaml enthusiast who also codes in Java, Scala, C, Dart, and contributed algorithm and math libraries to popular open-source repositories. His background spans end-to-end systems—robotics and mesh-networked USV swarms, VR intelligent tutoring, and deployed Vision applications—showing a knack for applied research that ships. He brings a rare mix of low-level algorithmic craftsmanship (fixing and optimizing C/Java algorithm implementations) and high-level generative model work, making him effective at both prototyping and production. Based in Silicon Valley with cross-disciplinary training from CMU, UC Berkeley, and SUSTech, he thrives on building AI that feels human.
7 years of coding experience
2 years of employment as a software developer
Visiting Student, Electrical Engneering and Computer Science, 4.0/4.0, Visiting Student, Electrical Engneering and Computer Science, 4.0/4.0 at University of California, Berkeley
Bachelor of Engineering - BE, Industrial Design - Computer Engineering, Bachelor of Engineering - BE, Industrial Design - Computer Engineering at South University of Science and Technology of China
Master of Science - MS, Computer Systems, Master of Science - MS, Computer Systems at Carnegie Mellon University
Contributions:8 reviews, 108 commits, 43 PRs in 3 years 4 months
Contributions summary:Shawn primarily contributed to implementing various algorithms and data structures in Dart. They added implementations for sorting algorithms like shellSort, quickSort, selectSort, bubbleSort, insertSort, and heapSort. Furthermore, the user developed search algorithms, including linearSearch, jumpSearch, binarySearch, ternarySearch, and fibonacciSearch. They also introduced code for other utility functions like GCD and LCM, along with demonstrating the use of HashMap data structure.
Collection of various algorithms in mathematics, machine learning, computer science, physics, etc implemented in C for educational purposes.
Role in this project:
Back-end Developer
Contributions:32 reviews, 38 commits, 34 PRs in 9 months
Contributions summary:Shawn primarily contributed to the C implementations of algorithms and data structures, as indicated by their code changes within the `thealgorithms/c` repository. They fixed bugs in existing code, added return values to functions, and removed unnecessary whitespace. Their contributions involved modifying and improving the sorting algorithms, and data structures like queues and heaps, enhancing the functionality and potentially the readability of the code.
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