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
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Publications
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Accelerating AllReduce with a Persistent Straggler
Arjun Devraj, Eric Ding, Abhishek Vijaya Kumar, Robert Kleinberg, Rachee Singh
Preprint
[pdf]
[code]
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LUMION: Fast Fault Recovery for ML Jobs Using Programmable Optical Fabrics
Abhishek Vijaya Kumar, Eric Ding, Arjun Devraj, Darius Bunandar, Rachee Singh
Preprint
[pdf]
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HEDGE: Mitigating effects of wavelength-specific faults in cloud WANs
Arjun Devraj, Bill Owens, Umesh Krishnaswamy, Ying Zhang, Rachee Singh
USENIX NSDI, 2026
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The Reality of Chasing Shannon's Limit in Optical Wide-Area Networks
Arjun Devraj, Bill Owens, Rachee Singh
ACM Internet Measurement Conference (IMC), 2025
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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]
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A case for server-scale photonic connectivity
Abhishek Vijaya Kumar, Arjun Devraj, Darius Bunandar, Rachee Singh
ACM HotNets, 2024
[pdf]
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Reconciling categorization and memory via environmental statistics
Arjun Devraj, Thomas L. Griffiths, Qiong Zhang
Psychonomic Bulletin & Review, 2024
[pdf]
[code]
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REDACT: Refraction Networking from the Data Center
Arjun Devraj, Liang Wang, Jennifer Rexford
ACM SIGCOMM Computer Communication Review (CCR), 2021
[pdf]
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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]
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Talks
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Accelerating AllReduce with a Persistent Straggler
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ACE Center for Evolvable Computing (August 2025)
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Mitigating effects of wavelength-specific faults in cloud WANs
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Workshop on Reconfigurable Networks (June 2025)
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The Cost of Chasing Shannon's Limit in Optical WANs
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Cornell Systems Research Seminar (March 2024)
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