Ehsan Kabir
This is a likely match — the affiliation was inferred from OpenAlex, ORCID, and web sources but has not been fully confirmed. Treat with appropriate caution.
Postdoctoral Research Associate, UT-Battelle
Also affiliated: Micron (United States) (2025); Bangladesh University of Engineering and Technology (2017–2021)
Formerly Arkansas Research Assistant, University of Arkansas through 2025; now Postdoctoral Research Associate, UT-Battelle.
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Ehsan Kabir's research has focused on the application of surface plasmon resonance biosensors for disease detection and the development of high-performance computing architectures. His work includes a theoretical model for optimizing metal thickness in Kretschmann configuration-based surface plasmon resonance biosensors and their application in detecting DNA mutations, urinary diseases, and blood diseases. Kabir has also investigated accelerating machine learning models for time-series forecasting and dynamic system modeling, specifically focusing on Long Short-Term Memory (LSTM) networks.
His recent publications explore hardware acceleration for transformer models and neural networks on Field-Programmable Gate Arrays (FPGAs), including work on programmable accelerators for convolutional and multilayer perceptron networks, and attention mechanisms in transformer models. Kabir has collaborated extensively with David Andrews and Miaoqing Huang at the University of Arkansas at Fayetteville, with whom he shares 13 publications. His research contributions are reflected in an h-index of 5 and 58 citations across 23 publications.
Metrics
- h-index: 6
- Publications: 16
- Citations: 133
Positions
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Postdoctoral Research Associate 2025–presentUT-Battelle DAQ Hardware, Neutron Technology, Oak Ridge National Lab ORCID
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Lecturer 2025Texas A&M University – Texarkana Computer Engineering ORCID
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Research Assistant 2020–2025University of Arkansas at Fayetteville Electrical Engineering and Computer Science ORCID
Selected Publications
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A runtime-adaptive transformer neural network accelerator on FPGAs (2025)
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Optimized Coding and Parameter Selection for Efficient FPGA Design of Attention Mechanisms (2025)
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Famous: Flexible Accelerator for the Attention Mechanism of Transformer on Ultrascale+ FPGAs (2024)
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ProTEA: Programmable Transformer Encoder Acceleration on FPGA (2024)
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FPGA Processor In Memory Architectures (PIMs): Overlay or Overhaul ? (2023)
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Accelerating LSTM-Based High-Rate Dynamic System Models (2023)
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FPGA Processor In Memory Architectures (PIMs): Overlay or Overhaul ? (2023)
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A Runtime Programmable Accelerator for Convolutional and Multilayer Perceptron Neural Networks on FPGA (2022)
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High-Rate Machine Learning for Forecasting Time-Series Signals (2022)
Collaboration Network
Top Collaborators
- High-Rate Machine Learning for Forecasting Time-Series Signals
- Accelerating LSTM-Based High-Rate Dynamic System Models
- FPGA Processor In Memory Architectures (PIMs): Overlay or Overhaul ?
- Famous: Flexible Accelerator for the Attention Mechanism of Transformer on Ultrascale+ FPGAs
- A Runtime Programmable Accelerator for Convolutional and Multilayer Perceptron Neural Networks on FPGA
Showing 5 of 9 shared publications
- High-Rate Machine Learning for Forecasting Time-Series Signals
- Accelerating LSTM-Based High-Rate Dynamic System Models
- FPGA Processor In Memory Architectures (PIMs): Overlay or Overhaul ?
- Famous: Flexible Accelerator for the Attention Mechanism of Transformer on Ultrascale+ FPGAs
- ProTEA: Programmable Transformer Encoder Acceleration on FPGA
Showing 5 of 8 shared publications
- High-Rate Machine Learning for Forecasting Time-Series Signals
- Accelerating LSTM-Based High-Rate Dynamic System Models
- FPGA Processor In Memory Architectures (PIMs): Overlay or Overhaul ?
- Famous: Flexible Accelerator for the Attention Mechanism of Transformer on Ultrascale+ FPGAs
- A Runtime Programmable Accelerator for Convolutional and Multilayer Perceptron Neural Networks on FPGA
Showing 5 of 6 shared publications
- High-Rate Machine Learning for Forecasting Time-Series Signals
- Accelerating LSTM-Based High-Rate Dynamic System Models
- Famous: Flexible Accelerator for the Attention Mechanism of Transformer on Ultrascale+ FPGAs
- Optimized Coding and Parameter Selection for Efficient FPGA Design of Attention Mechanisms
- High-Rate Machine Learning for Forecasting Time-Series Signals
- FPGA Processor In Memory Architectures (PIMs): Overlay or Overhaul ?
- FPGA Processor In Memory Architectures (PIMs): Overlay or Overhaul ?
- FPGA Processor In Memory Architectures (PIMs): Overlay or Overhaul ?
- Famous: Flexible Accelerator for the Attention Mechanism of Transformer on Ultrascale+ FPGAs
- FPGA Processor In Memory Architectures (PIMs): Overlay or Overhaul ?
- ProTEA: Programmable Transformer Encoder Acceleration on FPGA
- Optimized Coding and Parameter Selection for Efficient FPGA Design of Attention Mechanisms
- A runtime-adaptive transformer neural network accelerator on FPGAs
- FPGA Processor In Memory Architectures (PIMs): Overlay or Overhaul ?
- FPGA Processor In Memory Architectures (PIMs): Overlay or Overhaul ?
- FPGA Processor In Memory Architectures (PIMs): Overlay or Overhaul ?
- FPGA Processor In Memory Architectures (PIMs): Overlay or Overhaul ?
- A Runtime Programmable Accelerator for Convolutional and Multilayer Perceptron Neural Networks on FPGA
- A Runtime Programmable Accelerator for Convolutional and Multilayer Perceptron Neural Networks on FPGA
- Accelerating LSTM-Based High-Rate Dynamic System Models
- Accelerating LSTM-Based High-Rate Dynamic System Models
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