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Computer Science

D-Index
42
Citations
11396
World Ranking
8200
National Ranking
3514

Overview

Minlan Yu is a researcher affiliated with Harvard University in the United States. Their work primarily lies within the field of Computer Science, with a strong focus on Computer Networks and Communications, Artificial Intelligence, Electrical and Electronic Engineering, Information Systems, and Signal Processing.

The scientist has published extensively in several venues, notably with nineteen publications in arXiv (Cornell University), two in IEEE Network, two in Zenodo (CERN European Organization for Nuclear Research), one in the Virtual Community of Pathological Anatomy (University of Castilla La Mancha), and one at the IEEE INFOCOM 2022 - IEEE Conference on Computer Communications.

Frequent research topics addressed by Minlan Yu include:

  • Software-Defined Networks and 5G
  • Caching and Content Delivery
  • Network Security and Intrusion Detection
  • Advanced Optical Network Technologies
  • Advanced Malware Detection Techniques
  • Interconnection Networks and Systems
  • Network Traffic and Congestion Control

Recent academic papers authored or coauthored by Minlan Yu include:

  • "Automating Botnet Detection with Graph Neural Networks" (2020, arXiv (Cornell University))
  • "PINT: Probabilistic In-band Network Telemetry" (2020, arXiv (Cornell University))
  • "Zero-CPU Collection with Direct Telemetry Access" (2021, Virtual Community of Pathological Anatomy (University of Castilla La Mancha))
  • "Optimal Oblivious Routing for Structured Networks" (2022, IEEE INFOCOM 2022 - IEEE Conference on Computer Communications)
  • "Network Digital Twin" (2024, IEEE Network)

Minlan Yu has collaborated frequently with several coauthors, including:

  • Ran Ben Basat
  • Michael Mitzenmacher
  • Jiawei Zhou
  • Alexander M. Rush
  • Gianni Antichi

Best Publications

  • Rethinking virtual network embedding: substrate support for path splitting and migration

    Minlan Yu;Yung Yi;Jennifer Rexford;Mung Chiang

  • Scalable flow-based networking with DIFANE

    Minlan Yu;Jennifer Rexford;Michael J. Freedman;Jia Wang

  • SIMPLE-fying middlebox policy enforcement using SDN

    Zafar Ayyub Qazi;Cheng-Chun Tu;Luis Chiang;Rui Miao

  • Software defined traffic measurement with OpenSketch

    Minlan Yu;Lavanya Jose;Rui Miao

  • HPCC: high precision congestion control

    Yuliang Li;Rui Miao;Hongqiang Harry Liu;Yan Zhuang

  • SilkRoad: Making Stateful Layer-4 Load Balancing Fast and Cheap Using Switching ASICs

    Rui Miao;Hongyi Zeng;Changhoon Kim;Jeongkeun Lee

  • Cherrypick: adaptively unearthing the best cloud configurations for big data analytics

    Omid Alipourfard;Hongqiang Harry Liu;Jianshu Chen;Shivaram Venkataraman

  • Enforcing network-wide policies in the presence of dynamic middlebox actions using flowtags

    Seyed Kaveh Fayazbakhsh;Luis Chiang;Vyas Sekar;Minlan Yu

  • FlowRadar: a better NetFlow for data centers

    Yuliang Li;Rui Miao;Changhoon Kim;Minlan Yu

  • VideoEdge: Processing Camera Streams using Hierarchical Clusters

    Chien-Chun Hung;Ganesh Ananthanarayanan;Peter Bodik;Leana Golubchik

  • FlowTags: enforcing network-wide policies in the presence of dynamic middlebox actions

    Seyed Kaveh Fayazbakhsh;Vyas Sekar;Minlan Yu;Jeffrey C. Mogul

  • DREAM: dynamic resource allocation for software-defined measurement

    Masoud Moshref;Minlan Yu;Ramesh Govindan;Amin Vahdat

  • PINT: Probabilistic In-band Network Telemetry

    Ran Ben Basat;Sivaramakrishnan Ramanathan;Yuliang Li;Gianni Antichi

  • Rapier: Integrating routing and scheduling for coflow-aware data center networks

    Yangming Zhao;Kai Chen;Wei Bai;Minlan Yu

  • Online measurement of large traffic aggregates on commodity switches

    Lavanya Jose;Minlan Yu;Jennifer Rexford

  • GRASS: trimming stragglers in approximation analytics

    Ganesh Ananthanarayanan;Michael Chien-Chun Hung;Xiaoqi Ren;Ion Stoica

  • Flow-level state transition as a new switch primitive for SDN

    Masoud Moshref;Apoorv Bhargava;Adhip Gupta;Minlan Yu

  • Scheduling jobs across geo-distributed datacenters

    Chien-Chun Hung;Leana Golubchik;Minlan Yu

  • Trumpet: Timely and Precise Triggers in Data Centers

    Masoud Moshref;Minlan Yu;Ramesh Govindan;Amin Vahdat

  • Hopper: Decentralized Speculation-aware Cluster Scheduling at Scale

    Xiaoqi Ren;Ganesh Ananthanarayanan;Adam Wierman;Minlan Yu

Frequent Co-Authors

Jennifer Rexford
Jennifer Rexford Princeton University
Ramesh Govindan
Ramesh Govindan University of Southern California
Ethan Katz-Bassett
Ethan Katz-Bassett Columbia University
Changhoon Kim
Changhoon Kim Intel (United States)
Amin Vahdat
Amin Vahdat Google (United States)
Ganesh Ananthanarayanan
Ganesh Ananthanarayanan Microsoft (United States)
Vyas Sekar
Vyas Sekar Carnegie Mellon University
Adam Wierman
Adam Wierman California Institute of Technology
Leana Golubchik
Leana Golubchik University of Southern California
Nick Feamster
Nick Feamster University of Chicago

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