Arjun Devraj

Email: adevraj [at] cs [dot] cornell [dot] edu

I'm a third-year PhD student in Computer Science at Cornell University, where I'm advised by Rachee Singh. My research interests are broadly in systems and networking, with a focus on machine learning systems. Recently, I have been working on improving communication bottlenecks to speed up distributed machine learning workloads. I am also interested in traffic engineering for wide-area networks. In my research, I enjoy combining algorithmic techniques with insights from hardware, such as optical interconnects. My work is supported by the NSF Graduate Research Fellowship.

Before graduate school, I spent two years as a software engineer at Meta, where I worked on privacy infrastructure for the ads recommender system. Previously, I received my bachelor's degree in Computer Science, summa cum laude, from Princeton University, where I worked with Jennifer Rexford on network privacy and with Tom Griffiths and Qiong Zhang on computational cognitive science.

Email  /  Google Scholar  /  LinkedIn  /  GitHub

profile photo

Publications

Accelerating AllReduce with a Persistent Straggler
Arjun Devraj, Eric Ding, Abhishek Vijaya Kumar, Robert Kleinberg, Rachee Singh
Preprint
[pdf]    [code]
LUMION: Fast Fault Recovery for ML Jobs Using Programmable Optical Fabrics
Abhishek Vijaya Kumar, Eric Ding, Arjun Devraj, Darius Bunandar, Rachee Singh
Preprint
[pdf]
HEDGE: Mitigating effects of wavelength-specific faults in cloud WANs
Arjun Devraj, Bill Owens, Umesh Krishnaswamy, Ying Zhang, Rachee Singh
USENIX NSDI, 2026
The Reality of Chasing Shannon's Limit in Optical Wide-Area Networks
Arjun Devraj, Bill Owens, Rachee Singh
ACM Internet Measurement Conference (IMC), 2025
Chip-to-chip photonic connectivity in multi-accelerator servers for ML
Abhishek Vijaya Kumar, Arjun Devraj, Darius Bunandar, Rachee Singh
Optical Fiber Communications Conference (OFC), 2025
[pdf]
A case for server-scale photonic connectivity
Abhishek Vijaya Kumar, Arjun Devraj, Darius Bunandar, Rachee Singh
ACM HotNets, 2024
[pdf]
Reconciling categorization and memory via environmental statistics
Arjun Devraj, Thomas L. Griffiths, Qiong Zhang
Psychonomic Bulletin & Review, 2024
[pdf]    [code]
REDACT: Refraction Networking from the Data Center
Arjun Devraj, Liang Wang, Jennifer Rexford
ACM SIGCOMM Computer Communication Review (CCR), 2021
[pdf]
The Dynamics of Exemplar and Prototype Representations Depend on Environmental Statistics
Arjun Devraj, Qiong Zhang, Thomas L. Griffiths
Proceedings of the 43rd Annual Conference of the Cognitive Science Society, 2021
[pdf]

Talks

Accelerating AllReduce with a Persistent Straggler
  • ACE Center for Evolvable Computing (August 2025)
Mitigating effects of wavelength-specific faults in cloud WANs
  • Workshop on Reconfigurable Networks (June 2025)
The Cost of Chasing Shannon's Limit in Optical WANs
  • Cornell Systems Research Seminar (March 2024)

Source code adapted from Jon Barron's website.