Kaiyi Liu
Software Engineer at Red Hat
Canada
Summary
🤩
Rockstar🎓
Top SchoolKaiyi Liu is a Software Engineer based in Canada with seven years of experience building full-stack and cloud-native systems, currently contributing at Red Hat. They bridge software development and machine learning, having implemented energy-prediction ML models for the Kepler project using eBPF and Prometheus metrics. Kaiyi has spoken at multiple international conferences and co-authored patents and a sustainability-focused blog, demonstrating a blend of technical depth and thought leadership. Past roles span healthcare tech, enterprise survey systems, and web platforms where they improved performance and UX across stacks. Comfortable across Python, JavaScript, C#, and Kubernetes ecosystems, they focus on practical ML integration and efficiency at scale. Outside core engineering, Kaiyi’s background includes hands-on community roles and teaching experience that reinforce clear communication and collaboration.
7 years of coding experience
4 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at University of TorontoInternational Baccalaureate Diploma Programme, International Baccalaureate Diploma Programme at Bayview Secondary School
Chinese, English, French
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (9)
machine-learning10
go10
ebpf9
kubernetes-pods9
prometheus9
json9
kubernetes9
cloud-native8
prometheus-exporter7
Programming languages (5)
Github contributions (5)
sustainable-computing-io/kepler
Sep 2022 - Sep 2022
Kepler (Kubernetes-based Efficient Power Level Exporter) uses eBPF to probe performance counters and other system stats, use ML models to estimate workload energy consumption based on these stats, and exports them as Prometheus metrics
Role in this project:
ML Engineer
ML EngineerContributions:57 reviews, 10 commits, 25 PRs in 12 days
Contributions summary:Kaiyi's commits primarily involve implementing and refining energy prediction models within the Kepler project, specifically focusing on retrieving and integrating coefficients from a model server. They've introduced structures for handling coefficients and energy predictions, including features for CPU architecture, CPU metrics, and memory usage. The user also implemented functions for retrieving coefficients, calculating energy consumption based on the models, and addressing linting issues.
energy-consumptionprobeexportsprometheus-metricsenergy-monitor
KaiyiLiu1234/kepler-operator-1
Sep 2022 - Mar 2025
Kepler Operator
Contributions:11 PRs, 52 pushes, 8 branches in 2 years 7 months
kuberneteskepleroperator
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