Chris Wu is a Senior Software Engineer based in Taipei with 10 years of experience building high-throughput backend systems and scalable product features across companies like Booking.com and Yahoo. He has driven revenue-impacting services—such as ad servers handling billions of calls and an RSS-to-ads product generating substantial daily income—while working across Java, Scala, Python and cloud platforms. Comfortable switching stacks quickly, he’s delivered logging and migration systems, automated deployments, and production-grade image and ad processing pipelines. An active Python enthusiast, he curates a LeetCode Python repo focused on algorithmic solutions and interview prep, reflecting a strong foundation in data structures and algorithm design. Trained in supervised machine learning at Stanford Engineering and with a biomedical engineering background, he brings a data-informed, pragmatic approach to system design and optimization. Colleagues know him for simplifying complex problems—true to his “simple is better than complex” ethos—while shipping reliable, cost-effective infrastructure.
10 years of coding experience
6 years of employment as a software developer
Course Certificate, Supervised Machine Learning: Regression and Classification, Course Certificate, Supervised Machine Learning: Regression and Classification at Stanford University School of Engineering
學士, Biomedical Engineering and Environmental Sciences., 學士, Biomedical Engineering and Environmental Sciences. at 國立清華大學
Leetcode Python Solution and Explanation. Also a Guide to Prepare for Software Engineer Interview.
Role in this project:
Back-end Developer
Contributions:51 commits, 225 pushes, 1 branch in 8 months
Contributions summary:Chris primarily contributed to solving LeetCode problems in Python, focusing on algorithms and data structures. Their work involved implementing solutions for various problems, including those related to dynamic programming, graph algorithms, and binary search trees. The commits demonstrate a strong understanding of data structures and algorithm design, as well as Python programming skills. They also included explanations of code in comments, showing a focus on interview preparation.
Contributions:36 commits, 46 PRs, 49 pushes in 1 month
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