Match tier
Confirmed
Presence
Current · Arkansas
Last published
2026
Sources
OpenAlex · ORCID
Refreshed
2026-08-15
U
Ukash Nakarmi
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Assistant Professor
Also affiliated: University of Massachusetts Dartmouth (2021); Tokyo Institute of Technology (2021); Oklahoma State University (2011–2012); State University of New York (2016–2018); University of Applied Sciences and Arts of Southern Switzerland (2021); Purdue University West Lafayette (2021); Dalle Molle Institute for Artificial Intelligence Research (2021); University of Michigan (2021); Arkansas Department of Agriculture (2025); Geisinger Health System (2021); University at Buffalo, State University of New York (2016–2021); Stanford University (2019–2020)
Faculty Researcher
12 h-index
47 pubs
468 cited
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Dr. Ukash Nakarmi's research agenda centers on developing data-driven solutions for medical imaging, healthcare, and biomedicine through machine learning, computational imaging, and signal processing. He leads the Computational Analytics track within the Data Science Program at the University of Arkansas, Fayetteville, and holds an Assistant Professor position in the Department of Computer Science and Computer Engineering.
His work has focused on areas such as Magnetic Resonance Imaging (MRI) reconstruction, utilizing techniques like graph neural networks for noisy fMRI datasets and deep learning for image reconstruction. He has also investigated kernel regression imputation in dynamic-MRI and explored applications of AI and wearables for remote monitoring in heart failure. Nakarmi's research network includes collaborators such as Ibsa Jalata, Karthik Nayani, Elizabeth Adeogun, and Prateek Verma, with whom he has co-authored multiple publications.
Dr. Nakarmi's academic background includes postdoctoral training at Stanford University and a Ph.D. in Electrical Engineering from the University at Buffalo. His scholarship metrics include an h-index of 12, with 47 publications and 461 citations.
Metrics
- h-index: 12
- Publications: 47
- Citations: 468
Selected Publications
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Adaptive Extensions of Unbiased Risk Estimators for Unsupervised Magnetic Resonance Image Denoising (2026)
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Efficient Back-Projection Technique for Multiple Objects Detection and 2D Imaging Through Photonics-Based LFM Radar (2025)
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From Noise Estimation to Restoration: A Unified Diffusion and Bayesian Risk Approach for Unsupervised Denoising (2025)
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Semi-Supervised Medical Image Segmentation using Puzzlemix Augmentation Technique (2024)
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Cut-Puzzle mix: Scribble Guided Medical Image Segmentation without Segmentation Masks (2024)
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Abstract 4138376: A Machine Learning Approach to Predict Percutaneous Coronary Intervention in Patients with Critical Illness and Signs of Myocardial Injury (2024)
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A liquid crystal-based biomaterial platform for rapid sensing of heat stress using machine learning (2024)
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Learning From Oversampling: A Systematic Exploitation of Oversampling to Address Data Scarcity Issues in Deep Learning- Based Magnetic Resonance Image Reconstruction (2024)
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Multi-Radar Interference Mitigation in Photonics-Based Radar With Sliding Window LSTM Recurrent Neural Network (2024)
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DeepLIR: Attention-Based Approach for Mask-Based Lensless Image Reconstruction (2024)
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When System Model Meets Image Prior: An Unsupervised Deep Learning Architecture for Accelerated Magnetic Resonance Imaging (2023)
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On Training Model Bias of Deep Learning based Super-resolution Frameworks for Magnetic Resonance Imaging (2023)
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Multi-Chirp LFM Waveforms Generation With Reconfigurable Chirp Rates Using Optical Injection in a Semiconductor Laser (2023)
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BrainVGAE: End-to-End Graph Neural Networks for Noisy fMRI Dataset (2022)
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Artificial Intelligence, Wearables and Remote Monitoring for Heart Failure: Current and Future Applications (2022)
Collaboration Network
Top Collaborators
Bikash Nakarmi
Nanjing University of Aeronautics and Astronautics (CN)
5 shared publications
- Photonically Generated Frequency Hopped Linear Frequency Modulated Signal Using a DFB Laser
- Multi-Chirp LFM Waveforms Generation With Reconfigurable Chirp Rates Using Optical Injection in a Semiconductor Laser
- Linear Frequency Modulated Photonics RADAR using Injection Locking in Semiconductor Laser
- Multi-Radar Interference Mitigation in Photonics-Based Radar With Sliding Window LSTM Recurrent Neural Network
- Efficient Back-Projection Technique for Multiple Objects Detection and 2D Imaging Through Photonics-Based LFM Radar
Ikechi Augustine Ukaegbu
University of West Alabama (US)
5 shared publications
- Photonically Generated Frequency Hopped Linear Frequency Modulated Signal Using a DFB Laser
- Multi-Chirp LFM Waveforms Generation With Reconfigurable Chirp Rates Using Optical Injection in a Semiconductor Laser
- Linear Frequency Modulated Photonics RADAR using Injection Locking in Semiconductor Laser
- Multi-Radar Interference Mitigation in Photonics-Based Radar With Sliding Window LSTM Recurrent Neural Network
- Efficient Back-Projection Technique for Multiple Objects Detection and 2D Imaging Through Photonics-Based LFM Radar
Konstantinos Slavakis
Dalle Molle Institute for Artificial Intelligence Research (CH)
4 shared publications
- Kernel Regression Imputation in Manifolds Via Bi-Linear Modeling: The Dynamic-MRI Case
- Kernel Regression Imputation in Manifolds via Bi-Linear Modeling: The Dynamic-MRI Case
- Kernel Regression Imputation in Manifolds via Bi-Linear Modeling: The Dynamic-MRI Case
- Kernel Regression Imputation in Manifolds via Bi-Linear Modeling: The Dynamic-MRI Case
Loris Cannelli
Purdue University West Lafayette (US)
4 shared publications
- Kernel Regression Imputation in Manifolds Via Bi-Linear Modeling: The Dynamic-MRI Case
- Kernel Regression Imputation in Manifolds via Bi-Linear Modeling: The Dynamic-MRI Case
- Kernel Regression Imputation in Manifolds via Bi-Linear Modeling: The Dynamic-MRI Case
- Kernel Regression Imputation in Manifolds via Bi-Linear Modeling: The Dynamic-MRI Case
Gesualdo Scutari
Purdue University West Lafayette (US)
4 shared publications
- Kernel Regression Imputation in Manifolds Via Bi-Linear Modeling: The Dynamic-MRI Case
- Kernel Regression Imputation in Manifolds via Bi-Linear Modeling: The Dynamic-MRI Case
- Kernel Regression Imputation in Manifolds via Bi-Linear Modeling: The Dynamic-MRI Case
- Kernel Regression Imputation in Manifolds via Bi-Linear Modeling: The Dynamic-MRI Case
Leslie Ying
University of Arkansas at Fayetteville (US)
4 shared publications
- Kernel Regression Imputation in Manifolds Via Bi-Linear Modeling: The Dynamic-MRI Case
- Kernel Regression Imputation in Manifolds via Bi-Linear Modeling: The Dynamic-MRI Case
- Kernel Regression Imputation in Manifolds via Bi-Linear Modeling: The Dynamic-MRI Case
- Kernel Regression Imputation in Manifolds via Bi-Linear Modeling: The Dynamic-MRI Case
Shilong Pan
Nanjing University of Aeronautics and Astronautics (CN)
4 shared publications
- Photonically Generated Frequency Hopped Linear Frequency Modulated Signal Using a DFB Laser
- Multi-Chirp LFM Waveforms Generation With Reconfigurable Chirp Rates Using Optical Injection in a Semiconductor Laser
- Linear Frequency Modulated Photonics RADAR using Injection Locking in Semiconductor Laser
- Multi-Radar Interference Mitigation in Photonics-Based Radar With Sliding Window LSTM Recurrent Neural Network
Ibsa Jalata
University of Arkansas at Fayetteville
4 shared publications
In database
- Learning From Oversampling: A Systematic Exploitation of Oversampling to Address Data Scarcity Issues in Deep Learning- Based Magnetic Resonance Image Reconstruction
- When System Model Meets Image Prior: An Unsupervised Deep Learning Architecture for Accelerated Magnetic Resonance Imaging
- Cut-Puzzle mix: Scribble Guided Medical Image Segmentation without Segmentation Masks
- Semi-Supervised Medical Image Segmentation using Puzzlemix Augmentation Technique
Xiangchuan Wang
Nanjing University of Aeronautics and Astronautics (CN)
3 shared publications
- Photonically Generated Frequency Hopped Linear Frequency Modulated Signal Using a DFB Laser
- Multi-Chirp LFM Waveforms Generation With Reconfigurable Chirp Rates Using Optical Injection in a Semiconductor Laser
- Linear Frequency Modulated Photonics RADAR using Injection Locking in Semiconductor Laser
Gaurav Shetty
Geisinger Health System (US)
2 shared publications
- Kernel Regression Imputation in Manifolds Via Bi-Linear Modeling: The Dynamic-MRI Case
- Kernel Regression Imputation in Manifolds via Bi-Linear Modeling: The Dynamic-MRI Case
Bijay Gaudel
Stevens Institute of Technology (US)
2 shared publications
- Linear Frequency Modulated Photonics RADAR using Injection Locking in Semiconductor Laser
- Multi-Radar Interference Mitigation in Photonics-Based Radar With Sliding Window LSTM Recurrent Neural Network
Gaurav Shetty
Geisinger Health System (US)
2 shared publications
- Kernel Regression Imputation in Manifolds via Bi-Linear Modeling: The Dynamic-MRI Case
- Kernel Regression Imputation in Manifolds via Bi-Linear Modeling: The Dynamic-MRI Case
Joshua Mueller
University of Arkansas for Medical Sciences (US)
2 shared publications
- Artificial Intelligence, Wearables and Remote Monitoring for Heart Failure: Current and Future Applications
- Abstract 4138376: A Machine Learning Approach to Predict Percutaneous Coronary Intervention in Patients with Critical Illness and Signs of Myocardial Injury
Subhi J. Al’Aref
University of Arkansas for Medical Sciences
2 shared publications
In database
- Artificial Intelligence, Wearables and Remote Monitoring for Heart Failure: Current and Future Applications
- Abstract 4138376: A Machine Learning Approach to Predict Percutaneous Coronary Intervention in Patients with Critical Illness and Signs of Myocardial Injury
Hum Nath Parajuli
Nazarbayev University (KZ)
2 shared publications
- Multi-Chirp LFM Waveforms Generation With Reconfigurable Chirp Rates Using Optical Injection in a Semiconductor Laser
- Multi-Radar Interference Mitigation in Photonics-Based Radar With Sliding Window LSTM Recurrent Neural Network
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