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D-Index & Metrics

Computer Science

D-Index
44
Citations
6729
World Ranking
7669
National Ranking
3318

Overview

Mohsen Imani is affiliated with the University of California, San Diego in the United States. Their research primarily spans the fields of Engineering and Computer Science, with a significant focus on Electrical and Electronic Engineering, Artificial Intelligence, and Computer Networks and Communications. The main topics covered in their work include Ferroelectric and Negative Capacitance Devices, Advanced Memory and Neural Computing, Neural Networks and Reservoir Computing, Stochastic Gradient Optimization Techniques, Network Security and Intrusion Detection, Semiconductor Materials and Devices, and Ferroelectric and Piezoelectric Materials.

Imani's published papers appear in a range of academic venues. Frequent publication outlets include arXiv (Cornell University), IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Proceedings of the 59th ACM/IEEE Design Automation Conference, Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design, and Frontiers in Artificial Intelligence.

Notable recent papers authored or coauthored by Imani encompass:

  • GrapHD: Graph-Based Hyperdimensional Memorization for Brain-Like Cognitive Learning (2022) in Frontiers in Neuroscience
  • Accelerating Hyperdimensional Computing on FPGAs by Exploiting Computational Reuse (2020) in IEEE Transactions on Computers
  • PAM: A Piecewise-Linearly-Approximated Floating-Point Multiplier With Unbiasedness and Configurability (2021) in IEEE Transactions on Computers
  • Achieving software-equivalent accuracy for hyperdimensional computing with ferroelectric-based in-memory computing (2022) in Scientific Reports
  • An Ultracompact Single-Ferroelectric Field-Effect Transistor Binary and Multibit Associative Search Engine (2023) in Advanced Intelligent Systems

Frequent coauthors collaborating with Mohsen Imani include Sanggeon Yun, Zhuowen Zou, Xunzhao Yin, Hanning Chen, and Yang Ni. These collaborations span multiple publications, indicating ongoing research relationships.

Best Publications

  • Deep Fingerprinting: Undermining Website Fingerprinting Defenses with Deep Learning

    Payap Sirinam;Mohsen Imani;Marc Juarez;Matthew Wright

  • Toward an Efficient Website Fingerprinting Defense

    Marc Juarez;Mohsen Imani;Mike Perry;Claudia Diaz

  • VoiceHD: Hyperdimensional Computing for Efficient Speech Recognition

    Mohsen Imani;Deqian Kong;Abbas Rahimi;Tajana Rosing

  • Exploring Hyperdimensional Associative Memory

    Mohsen Imani;Abbas Rahimi;Deqian Kong;Tajana Rosing

  • FloatPIM: in-memory acceleration of deep neural network training with high precision

    Mohsen Imani;Saransh Gupta;Yeseong Kim;Tajana Rosing

  • FELIX: fast and energy-efficient logic in memory

    Saransh Gupta;Mohsen Imani;Tajana Rosing

  • Resistive configurable associative memory for approximate computing

    Mohsen Imani;Abbas Rahimi;Tajana S. Rosing

  • OnlineHD: Robust, Efficient, and Single-Pass Online Learning Using Hyperdimensional System

    Alejandro Hernandez-Cane;Namiko Matsumoto;Eric Ping;Mohsen Imani

  • Ultra-Efficient Processing In-Memory for Data Intensive Applications

    Mohsen Imani;Saransh Gupta;Tajana Rosing

  • Efficient human activity recognition using hyperdimensional computing

    Yeseong Kim;Mohsen Imani;Tajana S. Rosing

  • LookNN: Neural network with no multiplication

    Mohammad Samragh Razlighi;Mohsen Imani;Farinaz Koushanfar;Tajana Rosing

  • Mockingbird : Defending Against Deep-Learning-Based Website Fingerprinting Attacks With Adversarial Traces

    Mohammad Saidur Rahman;Mohsen Imani;Nate Mathews;Matthew Wright

  • GenieHD: efficient DNA pattern matching accelerator using hyperdimensional computing

    Yeseong Kim;Mohsen Imani;Niema Moshiri;Tajana Rosing

  • A Framework for Collaborative Learning in Secure High-Dimensional Space

    Mohsen Imani;Yeseong Kim;Sadegh Riazi;John Messerly

  • QuantHD: A Quantization Framework for Hyperdimensional Computing

    Mohsen Imani;Samuel Bosch;Sohum Datta;Sharadhi Ramakrishna

  • MPIM: Multi-purpose in-memory processing using configurable resistive memory

    Mohsen Imani;Yeseong Kim;Tajana Rosing

  • BioHD: an efficient genome sequence search platform using HyperDimensional memorization

    Unknown

  • DUAL: Acceleration of Clustering Algorithms using Digital-based Processing In-Memory

    Mohsen Imani;Saikishan Pampana;Saransh Gupta;Minxuan Zhou

  • F5-HD: Fast Flexible FPGA-based Framework for Refreshing Hyperdimensional Computing

    Sahand Salamat;Mohsen Imani;Behnam Khaleghi;Tajana Rosing

  • A Scalable Design of Multi-Bit Ferroelectric Content Addressable Memory for Data-Centric Computing

    Chao Li;Franz Muller;Tarek Ali;Ricardo Olivo

  • CFPU: Configurable Floating Point Multiplier for Energy-Efficient Computing

    Mohsen Imani;Daniel Peroni;Tajana Rosing

  • Approximate Computing Using Multiple-Access Single-Charge Associative Memory

    Mohsen Imani;Shruti Patil;Tajana Simunic Rosing

  • Hierarchical hyperdimensional computing for energy efficient classification

    Mohsen Imani;Chenyu Huang;Deqian Kong;Tajana Rosing

  • BRIC: Locality-based Encoding for Energy-Efficient Brain-Inspired Hyperdimensional Computing

    Mohsen Imani;Justin Morris;John Messerly;Helen Shu

Frequent Co-Authors

Tajana Rosing
Tajana Rosing University of California, San Diego
Abbas Rahimi
Abbas Rahimi IBM (United States)
Farinaz Koushanfar
Farinaz Koushanfar University of California, San Diego
Claudia Diaz
Claudia Diaz KU Leuven
Michael Niemier
Michael Niemier University of Notre Dame
Nikil Dutt
Nikil Dutt University of California, Irvine
Xiaobo Sharon Hu
Xiaobo Sharon Hu University of Notre Dame
Jan M. Rabaey
Jan M. Rabaey University of California, Berkeley
Ulf Schlichtmann
Ulf Schlichtmann Technical University of Munich
Luca Benini
Luca Benini ETH Zurich

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