# Khulna University

**Type:** Institutions  
**Canonical URL:** https://scholariq.org/institutions/khulna-university/

## Facts

| Field | Value |
| --- | --- |
| Avg h-index | 15 |
| Citations | 238,011 |
| City | Khulna |
| Country | BD |
| Description | Khulna University is a research organisation in Khulna, BD. OpenAlex records 9,807 works and 238,011 citations for it. 3,387 researchers list it as their most recent affiliation. |
| Homepage | http://www.ku.ac.bd/ |
| OpenAlex ID | https://openalex.org/I124386471 |
| Researchers | 3,387 |
| ROR ID | https://ror.org/05pny7s12 |
| Type | education |
| Wikidata ID | https://www.wikidata.org/wiki/Q13057681 |
| Works | 9,807 |

## University papers

Showing 12 of 14.

- [A Machine Learning Approach to Diagnosing Lung and Colon Cancer Using a Deep Learning-Based Classification Framework](https://scholariq.org/papers/a-machine-learning-approach-to-diagnosing-lung-and-colon-cancer-using-a-deep/)
- [IoT-Based Healthcare-Monitoring System towards Improving Quality of Life: A Review](https://scholariq.org/papers/iot-based-healthcare-monitoring-system-towards-improving-quality-of-life-a/)
- [Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond:a deep reinforcement learning based approach](https://scholariq.org/papers/intelligent-resource-slicing-for-embb-and-urllc-coexistence-in-5g-and-beyond-a/)
- [Transfer Learning for Sentiment Analysis Using BERT Based Supervised Fine-Tuning](https://scholariq.org/papers/transfer-learning-for-sentiment-analysis-using-bert-based-supervised-fine-tuning/)
- [eMBB-URLLC Resource Slicing: A Risk-Sensitive Approach](https://scholariq.org/papers/embb-urllc-resource-slicing-a-risk-sensitive-approach/)
- [Severity Classification of Diabetic Retinopathy Using an Ensemble Learning Algorithm through Analyzing Retinal Images](https://scholariq.org/papers/severity-classification-of-diabetic-retinopathy-using-an-ensemble-learning/)
- [A Novel Bayesian Optimization-Based Machine Learning Framework for COVID-19 Detection From Inpatient Facility Data](https://scholariq.org/papers/a-novel-bayesian-optimization-based-machine-learning-framework-for-covid-19/)
- [A comparative assessment of machine learning algorithms with the Least Absolute Shrinkage and Selection Operator for breast cancer detection and prediction](https://scholariq.org/papers/a-comparative-assessment-of-machine-learning-algorithms-with-the-least-absolute/)
- [4D: A Real-Time Driver Drowsiness Detector Using Deep Learning](https://scholariq.org/papers/4d-a-real-time-driver-drowsiness-detector-using-deep-learning/)
- [NeuroNet19: an explainable deep neural network model for the classification of brain tumors using magnetic resonance imaging data](https://scholariq.org/papers/neuronet19-an-explainable-deep-neural-network-model-for-the-classification-of/)
- [Unveiling the Essence of Digital Twins](https://scholariq.org/papers/unveiling-the-essence-of-digital-twins/)
- [Diabalance ML](https://scholariq.org/papers/diabalance-ml/)

## University researchers

- [Anupam Kumar Bairagi](https://scholariq.org/researchers/anupam-kumar-bairagi/)
- [Hirak Mondal](https://scholariq.org/researchers/hirak-mondal/)

## University top topics

Showing 8 of 23.

- [Child Nutrition and Water Access](https://scholariq.org/topics/child-nutrition-and-water-access/)
- [Nanofluid Flow and Heat Transfer](https://scholariq.org/topics/nanofluid-flow-and-heat-transfer/)
- [Fish Biology and Ecology Studies](https://scholariq.org/topics/fish-biology-and-ecology-studies/)
- [Aquaculture Nutrition and Growth](https://scholariq.org/topics/aquaculture-nutrition-and-growth/)
- [Coastal wetland ecosystem dynamics](https://scholariq.org/topics/coastal-wetland-ecosystem-dynamics/)
- [Global Maternal and Child Health](https://scholariq.org/topics/global-maternal-and-child-health/)
- [COVID-19 and Mental Health](https://scholariq.org/topics/covid-19-and-mental-health/)
- [Climate change impacts on agriculture](https://scholariq.org/topics/climate-change-impacts-on-agriculture/)

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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.