Ehsan Kabir Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

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University of Arkansas at Fayetteville

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4 h-index 20 pubs 50 cited

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Biography and Research Information

OverviewAI-generated summary

Ehsan Kabir's research interests lie in the acceleration of machine learning models and dynamic system forecasting. His work has focused on developing efficient computational methods, particularly for time-series signals and high-rate dynamic systems. Kabir has explored the application of Field-Programmable Gate Arrays (FPGAs) for accelerating neural network architectures, including Transformer encoders, convolutional neural networks, and multilayer perceptrons. He has also investigated in-memory computing architectures for FPGAs and advanced AI-memory systems. His publications include studies on programmable accelerators for attention mechanisms and direct die attachment for high-bandwidth AI-memory systems. Kabir's research network includes collaborators such as David Andrews and Miaoqing Huang from the University of Arkansas at Fayetteville, with whom he has co-authored multiple publications. His scholarship metrics include an h-index of 4 with 50 total citations across 20 publications.

Metrics

  • h-index: 4
  • Publications: 20
  • Citations: 50

Selected Publications

  • Optimized Coding and Parameter Selection for Efficient FPGA Design of Attention Mechanisms (2025) DOI
  • Famous: Flexible Accelerator for the Attention Mechanism of Transformer on Ultrascale+ FPGAs (2024) DOI
  • ProTEA: Programmable Transformer Encoder Acceleration on FPGA (2024) DOI
  • FPGA Processor In Memory Architectures (PIMs): Overlay or Overhaul ? (2023) DOI
  • Accelerating LSTM-Based High-Rate Dynamic System Models (2023) DOI
  • FPGA Processor In Memory Architectures (PIMs): Overlay or Overhaul ? (2023) DOI
  • A Runtime Programmable Accelerator for Convolutional and Multilayer Perceptron Neural Networks on FPGA (2022) DOI
  • High-Rate Machine Learning for Forecasting Time-Series Signals (2022) DOI

Collaborators

Researchers in the database who share publications

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