Christopher Canel
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Christopher Canel

 

I am a sixth-year PhD student in the Computer Science Department at Carnegie Mellon Universityadvised by Professor Srinivasan Seshan

office:  GHC 9009, 5000 Forbes Avenue, Pittsburgh, PA 15213 USA
email:  ccanel@cmu.edu

CV

I build networked systems. My current research focuses on mitigating unfair network flows and preventing incast traffic bursts in a datacenter, from the receiver's point of view. Previously, I architected transport protocols for hybrid packet/circuit networks, built machine learning systems for processing streaming video data at the edge, and developed new software architectures for big data analytics that put performance clarity first.

Summer 2022: I will return to Meta as an intern on the Systems & Infrastructure, Host Networking team.

Fall 2021: I was a full instructor (with Professor Peter Steenkiste) for CMU's 15-441/641 Networking and the Internet course. 

Summer 2021: I worked on microburst congestion control for datacenters with Meta's Systems & Infrastructure, Host Networking team.

From 2016-2019, I managed a student team in the Intel Science and Technology Center for Visual Cloud Systems, where we built systems for machine learning on edge devices under the guidance of Professor Dave Andersen and Michael KaminskyFrom 2014-2016, I built big data analytics systems with Kay Ousterhout and Professors Sylvia Ratnasamy and Scott Shenker in the NetSys Lab. I earned a B.S. in Electrical Engineering and Computer Science from UC Berkeley in 2015 and an M.S. in Computer Science from CMU in 2021.

 

I am from San Diego, CA.

Publications   Google Scholar

2020

Adapting TCP for reconfigurable datacenter networks NSDI 2020

Matthew K. Mukerjee, Christopher Canel, Weiyang Wang, Daehyeok Kim, Srinivasan Seshan, Alex C. Snoeren

paper, bibtex, slides, video

2019

Scaling video analytics on constrained edge nodes SysML 2019

Christopher Canel, Thomas Kim, Giulio Zhou, Conglong Li, Hyeontaek Lim, David G. Andersen, Michael Kaminsky, 

Subramanya R. Dulloor

paper, bibtexextended paper, poster, slides, video

2018

Mainstream: Dynamic stem-sharing for multi-tenant video processing USENIX ATC 2018

Angela Jiang, Daniel L.-K. Wong, Christopher Canel, Lilia Tang, Ishan Misra, Michael Kaminsky,

Michael A. Kozuch, Padmanabhan Pillai, David G. Andersen, Gregory R. Ganger

paper, bibtex, audio

2017

Monotasks: Architecting for performance clarity in data analytics frameworks SOSP 2017

Kay Ousterhout, Christopher Canel, Sylvia Ratnasamy, Scott Shenker

paper, bibtex

Performance clarity as a first-class design principle HotOS 2017

Kay Ousterhout, Christopher Canel, Max Wolffe, Sylvia Ratnasamy, Scott Shenker

paper, bibtex