World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
8136
World Ranking
7574
National Ranking
3287

Research.com Recognitions

  • 2009 - ACM Senior Member

Overview

Murali Annavaram is affiliated with the University of Southern California in the United States and has contributed extensively to the field of computer science, particularly focusing on topics related to federated learning, privacy-preserving technologies, and advanced machine learning techniques.

The scientist's research spans multiple main fields and specialized subfields, including:

  • Computer Science
  • Artificial Intelligence
  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Information Systems
  • Hardware and Architecture

The key topics covered in their work include:

  • Privacy-Preserving Technologies in Data
  • Stochastic Gradient Optimization Techniques
  • Cryptography and Data Security
  • Advanced Graph Neural Networks
  • Advanced Data Storage Technologies
  • Adversarial Robustness in Machine Learning
  • Ferroelectric and Negative Capacitance Devices

A selection of recent publications by Murali Annavaram highlights contributions on federated learning systems, graph neural networks, and related benchmarks. These papers include:

  • "FedML: A Research Library and Benchmark for Federated Machine Learning" (2020, arXiv - Cornell University)
  • "Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge" (2020, arXiv - Cornell University)
  • "FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks" (2021, arXiv - Cornell University)
  • "SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data" (2022, Proceedings of the AAAI Conference on Artificial Intelligence)
  • "Towards Non-I.I.D. and Invisible Data with FedNAS: Federated Deep Learning via Neural Architecture Search" (2020, arXiv - Cornell University)

Frequent coauthors associated with Murali Annavaram's research include:

  • Salman Avestimehr
  • Yongqin Wang
  • Hanieh Hashemi
  • Keshav Balasubramanian
  • Chaoyang He

The scientist has published predominantly in venues such as:

  • arXiv (Cornell University)
  • Proceedings on Privacy Enhancing Technologies
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Murali Annavaram has been recognized as an ACM Senior Member since 2009, reflecting their ongoing contributions to the academic and research community in computing and related disciplines.

Best Publications

  • Die Stacking (3D) Microarchitecture

    Bryan Black;Murali Annavaram;Ned Brekelbaum;John DeVale

  • A framework of energy efficient mobile sensing for automatic user state recognition

    Yi Wang;Jialiu Lin;Murali Annavaram;Quinn A. Jacobson

  • Virtual trip lines for distributed privacy-preserving traffic monitoring

    Baik Hoh;Marco Gruteser;Ryan Herring;Jeff Ban

  • FedML: A Research Library and Benchmark for Federated Machine Learning

    Chaoyang He;Songze Li;Jinhyun So;Mi Zhang

  • Mitigating Amdahl's Law through EPI Throttling

    Murali Annavaram;Ed Grochowski;John Shen

  • Data prefetching by dependence graph precomputation

    Murali Annavaram;Jignesh M. Patel;Edward S. Davidson

  • Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge

    Chaoyang He;Murali Annavaram;Salman Avestimehr

  • Method and apparatus for varying energy per instruction according to the amount of available parallelism

    Edward Grochowski;John Shen;Hong Wang;Doron Orenstein

  • Multimodal Physical Activity Recognition by Fusing Temporal and Cepstral Information

    Ming Li;Viktor Rozgić;Gautam Thatte;Sangwon Lee

  • Warped register file: A power efficient register file for GPGPUs

    M. Abdel-Majeed;M. Annavaram

  • KnightShift: Scaling the Energy Proportionality Wall through Server-Level Heterogeneity

    Daniel Wong;Murali Annavaram

  • Warped-compression: enabling power efficient GPUs through register compression

    Sangpil Lee;Keunsoo Kim;Gunjae Koo;Hyeran Jeon

  • Summarizer: trading communication with computing near storage

    Gunjae Koo;Kiran Kumar Matam;Te I;H. V. Krishna Giri Narra

  • Innovations in the Use of Interactive Technology to Support Weight Management

    D. Spruijt-Metz;C. K. F. Wen;G. O’Reilly;M. Li;M. Li

  • Warped-slicer: efficient intra-SM slicing through dynamic resource partitioning for GPU multiprogramming

    Qiumin Xu;Hyeran Jeon;Keunsoo Kim;Won Woo Ro

  • SlackSim: a platform for parallel simulations of CMPs on CMPs

    Jianwei Chen;Murali Annavaram;Michel Dubois

  • GPU register file virtualization

    Hyeran Jeon;Gokul Subramanian Ravi;Nam Sung Kim;Murali Annavaram

  • Enhancing Privacy and Accuracy in Probe Vehicle-Based Traffic Monitoring via Virtual Trip Lines

    B. Hoh;T. Iwuchukwu;Q. Jacobson;D. Work

  • Graph processing on GPUs: Where are the bottlenecks?

    Qiumin Xu;Hyeran Jeon;Murali Annavaram

  • KNOWME: a case study in wireless body area sensor network design

    U. Mitra;B. A. Emken;Sangwon Lee;Ming Li

  • A case for guarded power gating for multi-core processors

    Niti Madan;Alper Buyuktosunoglu;Pradip Bose;Murali Annavaram

Frequent Co-Authors

A. Salman Avestimehr
A. Salman Avestimehr University of Southern California
Nam Sung Kim
Nam Sung Kim University of Illinois at Urbana-Champaign
Urbashi Mitra
Urbashi Mitra University of Southern California
Donna Spruijt-Metz
Donna Spruijt-Metz University of Southern California
Bhaskar Krishnamachari
Bhaskar Krishnamachari University of Southern California
Shrikanth S. Narayanan
Shrikanth S. Narayanan University of Southern California
Per Stenström
Per Stenström Chalmers University of Technology
John Paul Shen
John Paul Shen Carnegie Mellon University
Hong Wang
Hong Wang Intel (United States)
Massoud Pedram
Massoud Pedram University of Southern California

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