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Amin Zollanvari

Assistant Professor

Utah Valley University

United States

Research Interests

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About

Amin Zollanvari is an Assistant Professor at Utah Valley University, USA. His research interests encompass Bayesian regression, active learning, and machine learning applications in healthcare and engineering. Recent publications include advancements in deep learning methodologies for EEG classification and innovative algorithms for mechanical fault identification.

Articles (15)

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2026

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2023

Collaborators (5)

Siamac Fazli

Associate Professor

Nazarbayev University

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Reza Sameni

Associate Professor

Emory University

UNITED STATES

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Mehdi Bagheri

Professor

Nazarbayev University

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Wilfried Blanc

CNRS Délégation Côte d'Azur

FRANCE

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Berdakh Abibullaev

Associate Professor

Nazarbayev University

View details

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Amin Zollanvari

Research Interests

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About

Articles (15)

Intelligent Distributed Optical Fiber Pressure Sensing for Dental Bite-Force Analysis

Vibration-based distribution transformer fault prognosis using recurrent neural networks with self-attention

YOLO-Based Detection and Classification of High-Voltage Insulator Surface Contamination

Leveraging Multihead Self‐Attention Mechanism in Convolutional Neural Networks for Enhanced Vibration‐Based Prediction of Transformer Fault

A Comparative Study of CNN, Multi-Head Self-Attention, and Hybrid CNN-MHSA Models for Supply-Voltage Prediction Using Motor Vibration Signals

Optimal Bayesian regression with a non-informative prior: Order-recursive and incremental learning

AdaBoost.SDM: Similarity and dissimilarity-based manifold regularized adaptive boosting algorithm

Efficient active learning using recursive estimation of error reduction

A Systematic YOLO‐Specific Model Selection for Mechanical Fault Identification in High‐Voltage Insulators

One-year mortality prediction of patients with hepatitis in Kazakhstan based on administrative health data: A machine learning approach

SRPM-ST: Sequential retraining and pseudo-labeling in mini-batches for self-training

Optimal Bayesian Regression With Vector Autoregressive Data Dependency

A Jackknife-Inspired Deep Learning Approach to Subject-Independent Classification of EEG

A Wireless Charging System Based on a DR-IPT to Power a UAV From Distribution Poles

Deep Learning in EEG-Based BCIs: A Comprehensive Review of Transformer Models, Advantages, Challenges, and Applications

Collaborators (5)

Siamac Fazli

Reza Sameni

Mehdi Bagheri

Wilfried Blanc

Berdakh Abibullaev

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