Damu Ding (丁大牧)
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Address: 601 108th Ave NE #1580, Bellevue, WA 98004 Email:
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Biography
Damu Ding is a Senior Software Development Engineer at ByteDance Inc., Seattle, US. He received the B.Sc. degree in Telecommunications engineering from the Politecnico di Torino, Italy, the M.Sc. degree in Telecommunications engineering from the University of Trento, Italy, and the Ph.D. degree in Electronics, Telecommunications and Information Technologies Engineering from the University of Bologna, Italy. His Ph.D. research activities were mostly carried out in Fondazione Bruno Kessler (FBK) Research Center, Trento, Italy. His Ph.D. supervisor was Dr. Domenico Siracusa, and co-superviosrs were Dr. Marco Savi and Dr. Federico Pederzolli.
Prior to joining ByteDance Inc., he was a postdoctoral research assistant at the University of Oxford, under supervision of Prof. Noa Zilberman.
Research interests
Sustainable computing in data center networks
Hardware architecture in programmable network devices
Compact data structure in computer networking
Network monitoring in P4-enabled programmable data planes
[04/2024] I joined ByteDance Inc. (Seattle, US) as a Senior Software Development Engineer.
[12/2023] “In-Network Machine Learning Using Programmable Network Devices: A Survey” has been accpted by IEEE Communications Surveys and Tutorials (Impact factor=35.6).
[12/2023] “CARBINE: Exploring Additional Properties of HyperLogLog for Secure and Robust Flow Cardinality Estimation” has been accepted by INFOCOM 2024 as a full paper (Acceptance ratio = 256/1307=19.6%).
[11/2022] Our paper “Estimating Logarithmic and Exponential Functions to Track Network Traffic Entropy in P4” published at NOMS 2020 has been awarded IEEE CNOM Best paper award 2022!
[07/2022] Awarded Chinese government award for outstanding self-financed students abroad 2021.
[07/2022] Awarded Travel Grant to SIGCOMM 2022.
[05/2022] Hackathon proposal “P4Pi Hackathon: P4 on Raspberry PI for Networking Education” has been accepted by SIGCOMM 2022.
[02/2022] Tutorial proposal “P4PI: P4 on Raspberry PI for Research and Education” has been accepted by NetSoft 2022.
[01/2022] “Design and Development of Network Monitoring Strategies in P4-enabled Programmable Switches” has been accepted by NOMS 2022 as a dissertation digest paper.
[09/2021] I will serve as the publicity chair of EuroP4 2021. Please consider submitting your latest work to our workshop!
[09/2021] “Tracking Normalized Network Traffic Entropy to Detect DDoS Attacks in P4” has been accepted by IEEE Transactions on Dependable and Secure Computing
[09/2021] I joined the University of Oxford as a postdoctoral research assistant.
[05/2021] I defended my Ph.D. at the University of Bologna, and I will be in the job market starting from July.
[04/2021] “In-Network Volumetric DDoS Victim Identification Using Programmable Commodity Switches” has been accepted by IEEE Transactions on Network and Service Management, Special issue on Latest Developments for Security Management of Networks and Services
[04/2021] “INVEST: Flow-Based Traffic Volume Estimation in Data-Plane Programmable Networks” has been accepted by IFIP Networking 2021 as a full paper.
[02/2020] I have been awarded Student Travel Grant for NOMS 2020
[01/2020] “An incrementally-deployable P4-enabled architecture for network-wide heavy-hitter detection” has been accepted by IEEE Transactions on Network and Service Management, Special issue on Cybersecurity Techniques for Managing Networked Systems (Acceptance ratio of this special issue = 8/44 = 18.18%)
[11/2019] “Estimating Logarithmic and Exponential Functions to Track Network Traffic Entropy in P4” has been accepted by NOMS 2020 as a full paper.
[11/2019] Attended and completed Barefoot Acadamy course “BA102: INTRODUCTION TO DATA AND CONTROL PLANE DEVELOPMENT WITH P4_16, TOFINO ASIC AND P4STUDIO SDE” in Amsterdam
[08/2019] “Estimation of logarithmic and exponential functions entirely in P4-programmable data planes” has been accepted by EuroP4 as a non-proceeding paper
[01/2019] “Incremental Deployment of Programmable Switches for Network-wide Heavy-Hitter Detection” has been accepted by NetSoft2019 as a full paper (acceptance rate 19.3%)