Mariofanna Milanova Source Confirmed

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

Federal Grant PI High Impact

Professor

University of Arkansas at Little Rock

faculty

20 h-index 208 pubs 6,277 cited

Research Areas

Advanced Neural Network Applications Computer Vision Applications Deep Learning Model Optimization AI in Cancer Detection Behavioral and Psychological Studies Medical Imaging Techniques and Applications Financial Markets and Investment Strategies EEG and Brain-Computer Interfaces

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ORCID Research Group

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OverviewAI-generated summary

Mariofanna Milanova's research group at the University of Arkansas at Little Rock focuses on the application of advanced computational methods, particularly deep learning, across diverse domains. Recent work includes the development of LSTM–Transformer-based hybrid deep learning models for financial time series forecasting and deep learning-based identification and tracking of railway bogie parts. Milanova also investigates model-compression techniques for audio classification on edge devices and explores deep learning for multimodal image retrieval combining image and text data.

Further research extends to computer vision applications, such as a comparative study of object detection models for optimized eye-gaze writing and the creation of markerless 3D virtual glasses try-on systems. Milanova has received a $50,000 NSF I-Corps grant for a project focused on a computer vision-based intelligent service recommendation system. Her work has resulted in 208 publications and garnered over 6,277 citations, with an h-index of 20. She has also collaborated with Afsana Mou, Md Imran Sarker, Md Rizwanul Kabir, and Ehsan Nasiri on multiple shared publications.

Metrics

h-index: 20
Publications: 208
Citations: 6,277

Selected Publications

Federated Learning-Based Road Defect Detection with Transformer Models for Real-Time Monitoring (2025) DOI
Parsing Requirements for Automatic Prompting of Large Language Models for Requirements Validation (2025) DOI
Entity Resolution Using Transformers for Synthetic Datasets (2025) DOI
Deep Neural Network with RIS-Powered Wireless Communication Systems for Channel Modeling (2025) DOI
Semantic Entity Resolution on Synthetic Datasets: A Transformer-Centric Approach (2025) DOI
Unveiling Alzheimer’s Progression: AI-Driven Models for Classifying Stages of Cognitive Impairment Through Medical Imaging (2025) DOI
Large Language Models for Classification of Functional and Nonfunctional Requirements (2025) DOI
Towards Smarter Road Maintenance: YOLOv7-Seg for Real-Time Detection of Surface Defects (2025) DOI
A Comparative Study of YOLO, SSD, Faster R-CNN, and More for Optimized Eye-Gaze Writing (2025) DOI
LSTM–Transformer-Based Robust Hybrid Deep Learning Model for Financial Time Series Forecasting (2025) DOI
Novel EEG feature selection based on hellinger distance for epileptic seizure detection (2025) DOI
Novel EEG Classification Based on Hellinger Distance for Seizure Epilepsy Detection (2024) DOI
Deep learning based identification and tracking of railway bogie parts (2024) DOI
Blockchain as a Service (2024) DOI
Performance Analysis of Deep Learning Model-Compression Techniques for Audio Classification on Edge Devices (2024) DOI