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D-Index & Metrics

Computer Science

D-Index
60
Citations
14637
World Ranking
3233
National Ranking
1571

Overview

A. Salman Avestimehr is affiliated with the University of Southern California in the United States. Their research primarily spans the field of Computer Science, with a strong focus on subfields such as Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Computer Science Applications, and Computational Mechanics.

The scientist's work extensively covers several main topics, including Privacy-Preserving Technologies in Data, Cryptography and Data Security, Stochastic Gradient Optimization Techniques, Domain Adaptation and Few-Shot Learning, Error Correcting Code Techniques, Adversarial Robustness in Machine Learning, and Mobile Crowdsensing and Crowdsourcing.

Frequent collaboration is evident in their research output, with regular co-authors including Başak Güler, Jinhyun So, Mahdi Soleymani, Hessam Mahdavifar, and Ramy E. Ali. These collaborations contribute to a diverse and interdisciplinary approach to their research areas.

Avestimehr has contributed numerous papers published in several venues, with a notable presence in arXiv (Cornell University), IEEE Journal on Selected Areas in Information Theory, Proceedings of the AAAI Conference on Artificial Intelligence, IEEE Transactions on Communications, and IEEE Transactions on Information Forensics and Security.

Key recent publications include:

  • "Federated Learning for the Internet of Things: Applications, Challenges, and Opportunities" (2022), IEEE Internet of Things Magazine
  • "Turbo-Aggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning" (2021), IEEE Journal on Selected Areas in Information Theory
  • "Byzantine-Resilient Secure Federated Learning" (2020), IEEE Journal on Selected Areas in Communications
  • "FairFed: Enabling Group Fairness in Federated Learning" (2023), Proceedings of the AAAI Conference on Artificial Intelligence
  • "HeteroSAg: Secure Aggregation With Heterogeneous Quantization in Federated Learning" (2022), IEEE Transactions on Communications

Best Publications

  • Wireless Network Information Flow: A Deterministic Approach

    A S Avestimehr;S N Diggavi;D N C Tse

  • Wireless Network Information Flow: A Deterministic Approach

    Salman Avestimehr;Suhas Diggavi;David Tse

  • The Exact Rate-Memory Tradeoff for Caching With Uncoded Prefetching

    Qian Yu;Mohammad Ali Maddah-Ali;A. Salman Avestimehr

  • A Fundamental Tradeoff Between Computation and Communication in Distributed Computing

    Songze Li;Mohammad Ali Maddah-Ali;Qian Yu;A. Salman Avestimehr

  • Straggler Mitigation in Distributed Matrix Multiplication: Fundamental Limits and Optimal Coding

    Qian Yu;Mohammad Ali Maddah-Ali;A. Salman Avestimehr

  • Polynomial codes: an optimal design for high-dimensional coded matrix multiplication

    Qian Yu;Mohammad Ali Maddah-Ali;A. Salman Avestimehr

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

    Chaoyang He;Songze Li;Jinhyun So;Mi Zhang

  • Federated Learning for Internet of Things: Applications, Challenges, and Opportunities

    Tuo Zhang;Lei Gao;Chaoyang He;Mi Zhang

  • Turbo-Aggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning

    Jinhyun So;Basak Guler;A. Salman Avestimehr

  • Byzantine-Resilient Secure Federated Learning

    Jinhyun So;Basak Guler;A. Salman Avestimehr

  • Fundamental Limits of Cache-Aided Interference Management

    Navid Naderializadeh;Mohammad Ali Maddah-Ali;Amir Salman Avestimehr

  • Weighted ℓ 1 minimization for sparse recovery with prior information

    M. Amin Khajehnejad;Weiyu Xu;A. Salman Avestimehr;Babak Hassibi

  • LAGRANGE CODED COMPUTING: OPTIMAL DESIGN FOR RESILIENCY, SECURITY, AND PRIVACY

    Salman Avestimehr;Mohammadreza Mousavi Kalan;Netanel Raviv;Mahdi Soltanolkotabi

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

    Chaoyang He;Murali Annavaram;Salman Avestimehr

  • A Unified Coding Framework for Distributed Computing with Straggling Servers

    Songze Li;Mohammad Ali Maddah-Ali;A. Salman Avestimehr

  • On the Optimality of Treating Interference as Noise

    Chunhua Geng;Navid Naderializadeh;Amir Salman Avestimehr;Syed A. Jafar

  • Characterizing the Rate-Memory Tradeoff in Cache Networks Within a Factor of 2

    Qian Yu;Mohammad Ali Maddah-Ali;A. Salman Avestimehr

  • Coded computation over heterogeneous clusters

    Amirhossein Reisizadeh;Saurav Prakash;Ramtin Pedarsani;Salman Avestimehr

  • A Field Guide to Federated Optimization

    Jianyu Wang;Zachary Charles;Zheng Xu;Gauri Joshi

  • ITLinQ: A new approach for spectrum sharing in device-to-device communication systems

    Navid Naderializadeh;A. Salman Avestimehr

  • Lagrange Coded Computing: Optimal Design for Resiliency, Security and Privacy

    Qian Yu;Songze Li;Netanel Raviv;Seyed Mohammadreza Mousavi Kalan

Frequent Co-Authors

Mohammad Ali Maddah-Ali
Mohammad Ali Maddah-Ali University of Minnesota
Murali Annavaram
Murali Annavaram University of Southern California
Mahdi Soltanolkotabi
Mahdi Soltanolkotabi University of Southern California
Babak Hassibi
Babak Hassibi California Institute of Technology
Ashutosh Sabharwal
Ashutosh Sabharwal Rice University
Weiyu Xu
Weiyu Xu University of Iowa
Vaneet Aggarwal
Vaneet Aggarwal Purdue University West Lafayette
Aydin Sezgin
Aydin Sezgin Ruhr University Bochum
Pramod Viswanath
Pramod Viswanath Princeton University
Michelle Effros
Michelle Effros California Institute of Technology

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