Chen Wang

Chen Wang is a Research Staff Member at the IBM T.J. Watson Research Center. Her research interests lie in Kubernetes, Container Cloud Resource Management, data-driven resource management, user experience-driven container management, Cloud Native AI platforms, and applying AI in Cloud management. She is an open-source advocate, a Kubernetes contributor, an Open Source Summit speaker, and a KubeCon speaker.

She obtained dual Ph.D. degrees from Carnegie Mellon University (CMU) and Faculdade de Engenharia da Universidade do Porto (FEUP) through ICTI Program. She was advised by Prof. Hyong Kim at CMU and Prof. Ricardo Morla at FEUP. 

Her talks in Open Source Communities include：

• Lightning Talk: Best Practices for LLM Serving with DRA, Cloud Native AI Day, colocated with KubeCon 2024 EU, Paris, France
• Trimaran: Load-Aware Scheduling for Power Efficiency and Performance Stability, KubeCon 2024 EU, Paris, France
• Tutorial: Cloud Native Sustainable LLM Inference in Action, KubeCon 2024 EU, Paris, France
• 5 Steps to Deploy Cloud Native Sustainable Foundation AI Models, Open Source Summit 2023 NA, Vancouver, Canada
• SIG Autoscaling Updates and Feature Highlights, KubeCon 2023 EU, Amsterdam, Netherlands
• On Data Locality in Kubernetes, Open Source Summit 2022 Japan, Yokohama, Japan
• On Data Locality in Kubernetes, Kubernetes AI Day at KubeCon 2022 NA, Detroit, MI, US
• Unleash the Full Potential of Kubernetes Scheduler: Configuration, Extension and Operation in Production, KubeCon 2022 NA, Detroit, MI, US
• Sustainability Research the Cloud Native Way, KubeCon 2022 NA, Detroit, MI, US
• Sustainability the Cloud Native Way, Open Source Summit 2022 NA, Austin, Texas, US
• Trimaran: Real Load Aware Scheduling in Kubernetes, KubeCon 2021 NA, Los Angeles, CA, US