Lydia Y. Chen
Papers
1
Total Citations
17
H-Index
1
About
Lydia Y. Chen is a leading researcher at the intersection of distributed systems, machine learning, and resource efficiency, with a particular focus on edge computing and deep neural network (DNN) optimization. Her work tackles the critical challenge of deploying sophisticated AI models on resource-constrained edge devices, where she has pioneered methods to automate the selection and compression of DNN architectures. In her highly cited 2019 paper, "Automating Deep Neural Network Model Selection for Edge Inference" (17 citations), Chen demonstrated how to systematically navigate the trade-off between model accuracy and computational cost, enabling real-time inference on devices that were once thought too limited for such tasks. This contribution has been instrumental in advancing edge AI, making intelligent applications—from autonomous systems to smart IoT—more practical and efficient. Beyond this, Chen's broader portfolio explores workload characterization, resource allocation, and performance modeling in cloud and edge environments, earning her recognition as a thought leader in sustainable and scalable computing. Her work continues to shape how researchers and engineers approach the deployment of AI in the real world.
Research Focus
Key Achievements
Top Papers
- 1Automating Deep Neural Network Model Selection for Edge Inference17 citations · 2019