Golrokh Mirzaei
Neuroscience · The Ohio State University
Publications
55
Citations
924
Est. group size
~1
Recurring co-author estimate
Active years
19
Publishing since 2008
Golrokh Mirzaei works on applying machine learning and deep learning methods to medical and biological data, with a strong focus on brain imaging analysis for Alzheimer's disease and brain tumor detection/segmentation, as well as integrating multi-omics (genomic) data for cancer classification. Techniques used include graph-based neural networks, attention-based image segmentation models, and reinforcement learning applied to MRI and genomic datasets.
Publication output was low and sporadic from 2017-2020, then increased notably from 2021 onward, with a peak of 8 publications in 2025, suggesting a growing and recently accelerating research output.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Radiogenomic Bipartite Graph Representation Learning for Alzheimer’s Disease Detection
Lecture notes in computer science · 2026
- Variance-Penalized MC-Dropout as a Learned Smoothing Prior for Brain Tumour Segmentation
arXiv (Cornell University) · 2026
- Variance-Penalized MC-Dropout as a Learned Smoothing Prior for Brain Tumour Segmentation
arXiv (Cornell University) · 2026
- MO-GCAN: multi-omics integration based on graph convolutional and attention networks
Bioinformatics · 2025
- Timepoint-Specific Benchmarking of Deep Learning Models for Glioblastoma Follow-Up MRI
Cancers · 2025
- Hybridization of Attention UNet with Repeated Atrous Spatial Pyramid Pooling for Improved Brain Tumor Segmentation
2025
- Hybridization of Attention UNet with Repeated Atrous Spatial Pyramid Pooling for Improved Brain Tumour Segmentation
arXiv (Cornell University) · 2025
- Radiogenomic Bipartite Graph Representation Learning for Alzheimer's Disease Detection
arXiv (Cornell University) · 2025
- Performance analysis of data resampling on class imbalance and classification techniques on multi-omics data for cancer classification
PLoS ONE · 2024
- Reinforcement-Learning-Based Localization of Hippocampus for Alzheimer’s Disease Detection
Diagnostics · 2023
- Constructing gene similarity networks using co-occurrence probabilities
BMC Genomics · 2023
- GraphChrom: A Novel Graph-Based Framework for Cancer Classification Using Chromosomal Rearrangement Endpoints
Cancers · 2022
- Multi-armed bandit approach for multi-omics integration
2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · 2022
- End to End Trained Long Term Recurrent Convolutional Network for Subject-level Alzheimer Detection
2022
- Ensembles of Convolutional Neural Network Pipelines for Diagnosis of Alzheimer’s Disease
2021 55th Asilomar Conference on Signals, Systems, and Computers · 2021
- Reviews in the Neurosciences×4
- arXiv (Cornell University)×4
- Cancers×3
- International Journal of Molecular Sciences×2
- Biomedical Signal Processing and Control×1
- Satyaki Roy Chowdhury
Neuroscience · The Ohio State University
- Debanjan Konar
Neuroscience · Purdue University West Lafayette
- Md. Motiur Rahman
Computer Science · Purdue University West Lafayette
- M. May Dixon
Agricultural and Biological Sciences · The Ohio State University
- Jamin G. Wieringa
Agricultural and Biological Sciences · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 19, 2026.
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