World's Best Scientists 2026 revealed!
Margaret Martonosi

Margaret Martonosi

D-Index & Metrics

Computer Science

D-Index
83
Citations
33064
World Ranking
891
National Ranking
486

Electronics and Electrical Engineering

D-Index
70
Citations
28970
World Ranking
891
National Ranking
374

Research.com Recognitions

  • 2020 - Fellow of the American Academy of Arts and Sciences
  • 2018 - Edward J. McCluskey Technical Achievement Award, IEEE Computer Society For contributions to power-aware computing and energy-constrained mobile sensor networks.
  • 2010 - IEEE Fellow For contributions to power-efficient computer architecture and systems design
  • 2009 - ACM Fellow For contributions in power-aware computing.

Overview

Margaret Martonosi is affiliated with Princeton University in the United States and has contributed extensively to the field of computer science, with a focus on various subfields and topics related to computing systems and quantum technologies.

The primary fields of their research include:

  • Computer Science

Within computer science, they specialize in several subfields:

  • Artificial Intelligence
  • Hardware and Architecture
  • Computer Networks and Communications
  • Atomic and Molecular Physics, and Optics
  • Electrical and Electronic Engineering

The main topics covered in their work are:

  • Quantum Computing Algorithms and Architecture
  • Parallel Computing and Optimization Techniques
  • Quantum Information and Cryptography
  • Distributed and Parallel Computing Systems
  • Quantum and electron transport phenomena
  • Cloud Computing and Resource Management
  • Quantum Mechanics and Applications

Margaret Martonosi has authored numerous scholarly articles, some of the recent ones include:

  • "$O(N^3)$ Measurement Cost for Variational Quantum Eigensolver on Molecular Hamiltonians," published in 2020 in DOAJ (DOAJ: Directory of Open Access Journals)
  • "Quantum-centric supercomputing for materials science: A perspective on challenges and future directions," published in 2024 in Future Generation Computer Systems
  • "Resource-Efficient Quantum Computing by Breaking Abstractions," published in 2020 in Proceedings of the IEEE
  • "ARQUIN: Architectures for Multinode Superconducting Quantum Computers," published in 2024 in ACM Transactions on Quantum Computing
  • "Architectures for Multinode Superconducting Quantum Computers," published in 2022 in arXiv (Cornell University)

The frequent venues where Margaret Martonosi's research is published include:

  • arXiv (Cornell University)
  • IEEE Micro
  • Communications of the ACM
  • ACM Transactions on Architecture and Code Optimization
  • Proceedings of the ACM on Programming Languages

Throughout their research career, Margaret Martonosi has collaborated with multiple coauthors, among whom the most frequent are:

  • Esin Türeci
  • Teague Tomesh
  • Pranav Gokhale
  • Frederic T. Chong
  • Marcelo Orenes-Vera

Margaret Martonosi has received several awards and recognitions, such as:

  • Fellow of the American Academy of Arts and Sciences, 2020
  • Edward J. McCluskey Technical Achievement Award, IEEE Computer Society, 2018, for contributions to power-aware computing and energy-constrained mobile sensor networks
  • IEEE Fellow, 2010, for contributions to power-efficient computer architecture and systems design
  • ACM Fellow, 2009, for contributions in power-aware computing

Best Publications

  • Wattch: a framework for architectural-level power analysis and optimizations

    David Brooks;Vivek Tiwari;Margaret Martonosi

  • Energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with ZebraNet

    Philo Juang;Hidekazu Oki;Yong Wang;Margaret Martonosi

  • Dynamic thermal management for high-performance microprocessors

    D. Brooks;M. Martonosi

  • Cache decay: exploiting generational behavior to reduce cache leakage power

    Stefanos Kaxiras;Zhigang Hu;Margaret Martonosi

  • Hardware design experiences in ZebraNet

    Pei Zhang;Christopher M. Sadler;Stephen A. Lyon;Margaret Martonosi

  • An Analysis of Efficient Multi-Core Global Power Management Policies: Maximizing Performance for a Given Power Budget

    C. Isci;A. Buyuktosunoglu;C.-Y. Chen;P. Bose

  • Runtime power monitoring in high-end processors: methodology and empirical data

    Canturk Isci;Margaret Martonosi

  • Techniques for Multicore Thermal Management: Classification and New Exploration

    James Donald;Margaret Martonosi

  • Impala: a middleware system for managing autonomic, parallel sensor systems

    Ting Liu;Margaret Martonosi

  • Erasure-coding based routing for opportunistic networks

    Yong Wang;Sushant Jain;Margaret Martonosi;Kevin Fall

  • Data compression algorithms for energy-constrained devices in delay tolerant networks

    Christopher M. Sadler;Margaret Martonosi

  • Identifying important places in people's lives from cellular network data

    Sibren Isaacman;Richard Becker;Ramón Cáceres;Stephen Kobourov

  • Power prediction for Intel XScale/spl reg/ processors using performance monitoring unit events

    Gilberto Contreras;Margaret Martonosi

  • Demo: SignalGuru: leveraging mobile phones for collaborative traffic signal schedule advisory

    Emmanouil Koukoumidis;Li-Shiuan Peh;Margaret Rose Martonosi

  • Live, Runtime Phase Monitoring and Prediction on Real Systems with Application to Dynamic Power Management

    Canturk Isci;Gilberto Contreras;Margaret Martonosi

  • Dynamically exploiting narrow width operands to improve processor power and performance

    D. Brooks;M. Martonosi

  • Cache miss equations: a compiler framework for analyzing and tuning memory behavior

    Somnath Ghosh;Margaret Martonosi;Sharad Malik

  • Run-time power estimation in high performance microprocessors

    Russ Joseph;Margaret Martonosi

  • Human mobility characterization from cellular network data

    Richard Becker;Ramón Cáceres;Karrie Hanson;Sibren Isaacman

  • Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers

    Prakash Murali;Jonathan M. Baker;Ali Javadi-Abhari;Frederic T. Chong

  • SignalGuru: Leveraging mobile phones for collaborative traffic signal schedule advisory

    Emmanouil Koukoumidis;Li-Shiuan Peh;Margaret Rose Martonosi

Frequent Co-Authors

Sharad Malik
Sharad Malik Princeton University
Douglas W. Clark
Douglas W. Clark Princeton University
Li-Shiuan Peh
Li-Shiuan Peh National University of Singapore
Frederic T. Chong
Frederic T. Chong University of Chicago
David Brooks
David Brooks Harvard University
Stefanos Kaxiras
Stefanos Kaxiras Uppsala University
Kevin Skadron
Kevin Skadron University of Virginia
Pranav Ashar
Pranav Ashar NEC (United States)
Carole-Jean Wu
Carole-Jean Wu Meta Platforms, Inc.
Ramón Cáceres
Ramón Cáceres Google (United States)

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