DENOS Lab, University of Calgary ← Back to team
Zainab Saad

Zainab Saad

Master Student in Electrical and Software Engineering, University of Calgary

Large Language Model Application, Federated Learning

Biography

Zainab Saad is a Master’s student at DENOS Lab working on large language model applications and federated learning. Her research builds a federated learning framework for carbon-aware container orchestration, predicting workload energy consumption while keeping sensitive operational data inside each enterprise, and she also contributes to the lab’s privacy-preserving federated analysis of clinical trial data.

Projects

  • Carbon-aware container orchestration

    Federated prediction of workload energy consumption so orchestration platforms such as Kubernetes can schedule for carbon without centralizing operational data.

Publications

  • IEEE SWC2025

    Towards Carbon-Aware Container Orchestration: Predicting Workload Energy Consumption with Federated Learning

    Zainab Saad, Jialin Yang, Henry Leung, and Steve Drew

    paper

  • arXiv2025

    A Survey on Task Scheduling in Carbon-aware Container Orchestration

    Jialin Yang, Zainab Saad, Jiajun Wu, Xiaoguang Niu, Henry Leung, and Steve Drew

    paper

  • SSRN

    Privacy-Preserving Federated Analysis Reproduces Non-Inferiority Results from the AcT Multicentre Stroke Trial

    Yunkai Bao, Zainab Saad, K. Duarte, Farhan Abbas, T. Sajobi, Jessalyn K. Holodinsky, Bijoy K. Menon, et al.

← All team members