Portrait of Amar Phanishayee

Amar Phanishayee



Hi! I am a Researcher Scientist at Microsoft Research in Redmond.

The goal of my research is to enable the creation of high-performance and efficient systems for large-scale data-intensive computing. To this end, my work follows two broad approaches:

1. Radically rethinking cluster architecture

Energy-efficient clusters for data intensive computing – FAWN
Freespace optics for datacenter networks – ProjecToR

2. Build robust clustered systems and protocols

First to analyse and solve TCP throughput collapse and latency insensitivity for clustered systems – TCP Incast
Distributed KV systems – FAWN-KV, Flex-KV (and the underlying Ouroborous protocol)
Reliable and scalable multicast – Ricochet, Plato
Compositional reasoning for systematically testing distributed systems
Efficient distributed deep learning – Fiddle

I have also occasionally looked at addressing issues in geo-distributed systems:

High-perf multi-hop wireless transfers using opportunistic caching – Ditto
Scalable one-hop overlay routing – NuRON
Systems/abstractions for connected devices – Bolt (storage) and Beam (programming framework and runtime)

As a graduate student at Carnegie Mellon University I worked with Dave Andersen and some stellar collaborators on FAWN, Incast, and Ditto.



Research Awards

  • 2012 CMU’s Allen Newell Award for Research Excellence for our work on “Energy-efficient Data Intensive Computing”
  • Best Paper Award, SOSP 2009 for FAWN


Program Committee Service

  • NSDI 2014 Poster Chair
  • HotStorage 2016
  • SOCC 2017
  • NSDI 2018 (“heavy”)
  • HotCloud 2018
  • NSDI 2019 (“heavy”)