My research spans a number of areas in computer systems, including distributed systems, large-scale/cloud computing and computer networking with emphasis on programmable networks.

At KAUST, I lead the SANDS Lab.


Here is a representative subset of projects I am working on:


A general framework for implementing, studying and evaluating gradient compression techniques for distributed deep learning.


We accelerate distributed deep learning by designing an in-network aggregation primitive using a programmable switch dataplane.

DAIET: Data Aggregation In nETwork

We propose the first in-network aggregation primitive based on programmable network switches.

Past projects

In my past, I have been active in SDN and programmable networks. Major projects included:

Research Group

I am privileged to be working with these very talented individuals:


Research Scientists


Ph.D. students

Research MS students (while at KAUST)


  • Amedeo Sapio (now Software Engineer at Intel)
  • Marco Chiesa (now Assistant Professor at KTH)
  • Thanh Dang Nguyen (now Research Engineer at University of Chicago)

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