PROJECTSI lead Scalable Adaptive Yet Efficient Distributed (SAYED) Systems Group where we perform systems-focused research by exploring existing problems of mainstream Networked and Distributed Systems and finding solutions by designing and prototyping scalable adaptive yet efficient systems of the future. We are broadly interested in Systems for ML, ML for Systems, Distributed and Federated Learning, Computer Networks, Fog/Cloud Computing, SDN and Programmable Networks. My projects involves working with or supervising students, academics, researchers, and industry partners and include a wide range of applications.
Current Research Projects
Improving the Performance, Scalability and Interpretability of Distributed Machine LearningIn this project, We focus on tackling challenging problems related mainly to improve the performance and understanding of machine learning systems and their usage for optimizing and automating computer and network systems. Improving the Performance of TCP Applications in Public Cloud NetworksIn this project, we developed scalable, efficient, readily-deployable mechanisms to significantly improve the performance of TCP Applications in Cloud Networks. Past Research Projects
Useful Tools
Past Project and FYP Supervision
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