# Mohammad Junayed Hasan

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/mohammad-junayed-hasan/

## Facts

| Field | Value |
| --- | --- |
| Citations | 83 |
| Field | Machine Learning in Healthcare |
| h-index | 5 |
| i10-index | 3 |
| Last Known Institution | Johns Hopkins University |
| OpenAlex ID | https://openalex.org/A5100577622 |
| ORCID iD | 0009-0008-3451-0267 |
| Works | 19 |

## Researcher papers

- [Predicting life satisfaction using machine learning and explainable AI](https://scholariq.org/papers/predicting-life-satisfaction-using-machine-learning-and-explainable-ai/)
- [OptimCLM: Optimizing clinical language models for predicting patient outcomes via knowledge distillation, pruning and quantization](https://scholariq.org/papers/optimclm-optimizing-clinical-language-models-for-predicting-patient-outcomes-via-2/)
- [CQ-CNN: A lightweight hybrid classical–quantum convolutional neural network for Alzheimer’s disease detection using 3D structural brain MRI](https://scholariq.org/papers/cq-cnn-a-lightweight-hybrid-classical-quantum-convolutional-neural-network-for/)
- [Early detection of occupational stress: Enhancing workplace safety with machine learning and large language models](https://scholariq.org/papers/early-detection-of-occupational-stress-enhancing-workplace-safety-with-machine/)
- [Deployable Deep Learning for Cross-Domain Plant Leaf Disease Detection via Ensemble Learning, Knowledge Distillation, and Quantization](https://scholariq.org/papers/deployable-deep-learning-for-cross-domain-plant-leaf-disease-detection-via/)
- [Bridging Classical and Quantum Machine Learning: Knowledge Transfer From Classical to Quantum Neural Networks Using Knowledge Distillation](https://scholariq.org/papers/bridging-classical-and-quantum-machine-learning-knowledge-transfer-from/)
- [DeepMarkerNet: Leveraging supervision from the Duchenne Marker for spontaneous smile recognition](https://scholariq.org/papers/deepmarkernet-leveraging-supervision-from-the-duchenne-marker-for-spontaneous/)
- [Optimclm: Optimizing Clinical Language Models for Predicting Patient Outcomes Via Knowledge Distillation, Pruning and Quantization](https://scholariq.org/papers/optimclm-optimizing-clinical-language-models-for-predicting-patient-outcomes-via/)
- [A novel framework for detection of noncommunicable diseases via prompt engineering and domain knowledge integration](https://scholariq.org/papers/a-novel-framework-for-detection-of-noncommunicable-diseases-via-prompt/)
- [Distilling the Knowledge of Clinical Outcome Predictions in Large Language Models for Resource Constrained Healthcare Systems](https://scholariq.org/papers/distilling-the-knowledge-of-clinical-outcome-predictions-in-large-language/)

## Researcher topics

- [Machine Learning in Healthcare](https://scholariq.org/topics/machine-learning-in-healthcare/)
- [Quantum Computing Algorithms and Architecture](https://scholariq.org/topics/quantum-computing-algorithms-and-architecture/)
- [Topic Modeling](https://scholariq.org/topics/topic-modeling/)
- [Face recognition and analysis](https://scholariq.org/topics/face-recognition-and-analysis/)
- [Quantum Information and Cryptography](https://scholariq.org/topics/quantum-information-and-cryptography/)

## Researcher university

- [Johns Hopkins University](https://scholariq.org/institutions/johns-hopkins-university/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.