World's Best Scientists 2026 revealed!
Mohammad Alizadeh

Mohammad Alizadeh

D-Index & Metrics

Computer Science

D-Index
56
Citations
16619
World Ranking
3993
National Ranking
1900

Research.com Recognitions

  • 2017 - Fellow of Alfred P. Sloan Foundation

Overview

Mohammad Alizadeh is affiliated with MIT in the United States and has contributed extensively to the field of computer science. Their research spans multiple areas, including computer networks and communications, artificial intelligence, signal processing, information systems, and computer vision and pattern recognition.

The scientist's work has been disseminated through various publication venues. Frequent venues include arXiv (Cornell University) with 15 publications, Proceedings of the VLDB Endowment with 3 publications, Scientific Reports with 3 publications, Proceedings of the ACM on Management of Data with 1 publication, and ACM SIGMOD Record with 1 publication.

From their recent papers, notable works include:

  • "Tsunami" (2020), published in Proceedings of the VLDB Endowment
  • "Flow-loss" (2021), published in Proceedings of the VLDB Endowment
  • "Robust Query Driven Cardinality Estimation under Changing Workloads" (2023), published in Proceedings of the VLDB Endowment
  • "Real-world Video Adaptation with Reinforcement Learning" (2020), published in arXiv (Cornell University)
  • "FactorJoin: A New Cardinality Estimation Framework for Join Queries" (2023), published in Proceedings of the ACM on Management of Data

Frequent coauthors collaborating with Mohammad Alizadeh include Tim Kraska, Parimarjan Negi, Ryan Marcus, Hongzi Mao, and Nesime Tatbul. These collaborations reflect ongoing partnerships in various subfields within computer science.

Research topics addressed in their work encompass:

  • Data Management and Algorithms
  • Data Stream Mining Techniques
  • Distributed Systems and Fault Tolerance
  • Blockchain Technology Applications and Security
  • Interconnection Networks and Systems
  • Advanced Database Systems and Queries
  • Cloud Computing and Resource Management

Mohammad Alizadeh's contributions are primarily situated within the following fields and subfields:

  • Computer Science
  • Computer Networks and Communications
  • Artificial Intelligence
  • Signal Processing
  • Information Systems
  • Computer Vision and Pattern Recognition

In recognition of their work, they have been awarded the Fellow of the Alfred P. Sloan Foundation in 2017.

Best Publications

  • Data center TCP (DCTCP)

    Mohammad Alizadeh;Albert Greenberg;David A. Maltz;Jitendra Padhye

  • Neural Adaptive Video Streaming with Pensieve

    Hongzi Mao;Ravi Netravali;Mohammad Alizadeh

  • Resource Management with Deep Reinforcement Learning

    Hongzi Mao;Mohammad Alizadeh;Ishai Menache;Srikanth Kandula

  • CONGA: distributed congestion-aware load balancing for datacenters

    Mohammad Alizadeh;Tom Edsall;Sarang Dharmapurikar;Ramanan Vaidyanathan

  • pFabric: minimal near-optimal datacenter transport

    Mohammad Alizadeh;Shuang Yang;Milad Sharif;Sachin Katti

  • Learning scheduling algorithms for data processing clusters

    Hongzi Mao;Malte Schwarzkopf;Shaileshh Bojja Venkatakrishnan;Zili Meng

  • Less is more: trading a little bandwidth for ultra-low latency in the data center

    Mohammad Alizadeh;Abdul Kabbani;Tom Edsall;Balaji Prabhakar

  • HPCC: high precision congestion control

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

  • RoadTracer: Automatic Extraction of Road Networks from Aerial Images

    Favyen Bastani;Songtao He;Sofiane Abbar;Mohammad Alizadeh

  • Homa: a receiver-driven low-latency transport protocol using network priorities

    Behnam Montazeri;Yilong Li;Mohammad Alizadeh;John Ousterhout

  • Neo: a learned query optimizer

    Ryan Marcus;Parimarjan Negi;Hongzi Mao;Chi Zhang

  • EyeQ: practical network performance isolation at the edge

    Vimalkumar Jeyakumar;Mohammad Alizadeh;David Mazières;Balaji Prabhakar

  • Programmable Packet Scheduling at Line Rate

    Anirudh Sivaraman;Suvinay Subramanian;Mohammad Alizadeh;Sharad Chole

  • Learning Multi-Dimensional Indexes

    Vikram Nathan;Jialin Ding;Mohammad Alizadeh;Tim Kraska

  • Language-Directed Hardware Design for Network Performance Monitoring

    Srinivas Narayana;Anirudh Sivaraman;Vikram Nathan;Prateesh Goyal

  • Packet Transactions: High-Level Programming for Line-Rate Switches

    Anirudh Sivaraman;Alvin Cheung;Mihai Budiu;Changhoon Kim

  • Homa: A Receiver-Driven Low-Latency Transport Protocol Using Network Priorities (Complete Version)

    Behnam Montazeri;Yilong Li;Mohammad Alizadeh;John Ousterhout

  • Adaptive Neural Signal Detection for Massive MIMO

    Mehrdad Khani;Mohammad Alizadeh;Jakob Hoydis;Phil Fleming

  • Let It Flow: Resilient Asymmetric Load Balancing with Flowlet Switching

    Erico Vanini;Rong Pan;Mohammad Alizadeh;Parvin Taheri

  • Analysis of DCTCP: stability, convergence, and fairness

    Mohammad Alizadeh;Adel Javanmard;Balaji Prabhakar

  • Millions of little minions: using packets for low latency network programming and visibility

    Vimalkumar Jeyakumar;Mohammad Alizadeh;Yilong Geng;Changhoon Kim

  • SageDB: A Learned Database System

    Tim Kraska;Mohammad Alizadeh;Alex Beutel;Ed H. Chi

  • Packet Transactions: High-level Programming for Line-Rate Switches

    Anirudh Sivaraman;Mihai Budiu;Alvin Cheung;Changhoon Kim

Frequent Co-Authors

Balaji Prabhakar
Balaji Prabhakar Stanford University
Sachin Katti
Sachin Katti Stanford University
Changhoon Kim
Changhoon Kim Intel (United States)
Nick McKeown
Nick McKeown Stanford University
Pramod Viswanath
Pramod Viswanath Princeton University
David Mazières
David Mazières Stanford University
George Varghese
George Varghese University of California, Los Angeles

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