Research

• Projects
  • GRACE
  • SwitchML
  • DAIET: Data Aggregation In nETwork
  • Past projects
• Research Group
  • Students
  • Postdocs
  • Research Staff
  • Alumni

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. My current focus is on designing better systems support for AI/ML and providing practical implementations deployable in the real world.

At KAUST, I lead the SANDS Lab.

Projects

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

GRACE

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

SwitchML

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:

• Dynam-IX: Dynamic Interconnection eXchange
• SIXPACK: Securing Internet eXchange Points Against Curious onlooKers
• ENDEAVOUR
• NetPaxos: Network support for consensus protocols
• Frenetic
• Software Transactional Networking
• Panopticon: Incremental SDN Deployment in Enterprise Networks
• NICE

Research Group

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

Students

• Achref Rebai
• Boris Radovic (co-advised with Veljko Pejovic)
• Jianghui Wang (co-advised with Francesco Orabona)
• Jihao Xin
• Kaihua Liang
• Mohammed K. Aljahdali
• Norah Alballa
• Salma Kharrat
• Tian Lyu (co-advised with David Keyes)
• Tongzhou Gu
• Yangzhixin Luo (co-advised with Jian Weng)
• Yixi Chen (co-advised with Suhaib Fahmy)

Postdocs

• Alessandro Cornacchia
• Mubarak Ojewale

Research Staff

• Amandio Faustino

Alumni

Check out our alumni!