Md. Sohrawordi

About Md. Sohrawordi

Md. Sohrawordi, With an exceptional h-index of 5 and a recent h-index of 5 (since 2020), a distinguished researcher at Hajee Mohammad Danesh Science and Technology University, specializes in the field of Bioinformatics, Biomedical, Image Processing, Data Mining, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

An Efficient Feature Optimization Approach with Machine Learning for Detection of Major Depressive Disorder Using EEG Signal

Enhanced Brain Tumor Classification from MRI Images Using Deep Learning Model

Optimal Feature Identification and Major Depressive Disorder Prediction through Correlation-Based Machine Learning Approach

Selective HybridNET: Spectral-Spatial Dimensionality Reduction for HSI Classification

Subgrouping-based nmf with imbalanced class handling for hyperspectral image classification

An Empirical Feature Selection Approach for Phishing Websites Prediction with Machine Learning

PLP_FS: prediction of lysine phosphoglycerylation sites in protein using support vector machine and fusion of multiple F_Score feature selection

Prediction of lysine formylation sites using support vector machine based on the sample selection from majority classes and synthetic minority over-sampling techniques

Md. Sohrawordi Information

University

Position

Assistant ProfessorDept. of CSE

Citations(all)

88

Citations(since 2020)

82

Cited By

19

hIndex(all)

5

hIndex(since 2020)

5

i10Index(all)

2

i10Index(since 2020)

2

Email

University Profile Page

Hajee Mohammad Danesh Science and Technology University

Google Scholar

View Google Scholar Profile

Md. Sohrawordi Skills & Research Interests

Bioinformatics

Biomedical

Image Processing

Data Mining

Machine Learning

Top articles of Md. Sohrawordi

Title

Journal

Author(s)

Publication Date

An Efficient Feature Optimization Approach with Machine Learning for Detection of Major Depressive Disorder Using EEG Signal

Ashikur Rahman Bhuyain

Jannatul Ferdouse

Mozaddid Ul Hoque Babar

Md Sohrawordi

Md Rashedul Islam

...

2023/12/13

Enhanced Brain Tumor Classification from MRI Images Using Deep Learning Model

Asadullah Bin Rahman

Md Touhid Islam

Md Rashedul Islam

Md Sohrawordi

Md Nahid Sultan

2023/12/13

Optimal Feature Identification and Major Depressive Disorder Prediction through Correlation-Based Machine Learning Approach

Mozaddid Ul Hoque Babar

Ashikur Rahman Bhuyain

Jannatul Ferdouse

Md Sohrawordi

Emran Ali

2023/12/7

Selective HybridNET: Spectral-Spatial Dimensionality Reduction for HSI Classification

Md Rashedul Islam

Md Touhid Islam

Md Sohrawordi

2023/2/23

Subgrouping-based nmf with imbalanced class handling for hyperspectral image classification

Md Touhid Islam

Mohadeb Kumar

Md Rashedul Islam

Md Sohrawordi

2022/12/17

An Empirical Feature Selection Approach for Phishing Websites Prediction with Machine Learning

Pankaj Bhowmik

Md Sohrawordi

UA Md Ehsan Ali

Pulak Chandra Bhowmik

2021/12/30

PLP_FS: prediction of lysine phosphoglycerylation sites in protein using support vector machine and fusion of multiple F_Score feature selection

Briefings in Bioinformatics

Md Sohrawordi

Md Ali Hossain

Md Al Mehedi Hasan

2022/9

Prediction of lysine formylation sites using support vector machine based on the sample selection from majority classes and synthetic minority over-sampling techniques

Biochimie

Md Sohrawordi

Md Ali Hossain

2022/1/1

Cardiotocography data analysis to predict fetal health risks with tree-based ensemble learning

Inf. Technol. Comput. Sci

Pankaj Bhowmik

P Chandra Bhowmik

UME Ali

Md Sohrawordi

2021

A LSB based image steganography using random pixel and bit selection for high payload

International Journal of Mathematical Sciences and Computing

UA Md Ehsan Ali

Emran Ali

Md Sohrawordi

Md Nahid Sultan

2021

Incorporation of Kernel Support Vector Machine for Effective Prediction of Lysine Formylation from Class Imbalance Samples

Md Sohrawordi

Ali Hossain

2021

Analysis of social media data to classify and detect frequent issues using machine learning approach

Pankaj Bhowmik

Md Sohrawordi

UA Md Ehsan Ali

Md Najmul Hasan

Prodip Kumar Roy

2020/11/28

Lyfor: prediction of lysine formylation sites from sequence based features using support vector machine

Md Sohrawordi

Md Al Mehedi Hasan

2020/6/5

See List of Professors in Md. Sohrawordi University(Hajee Mohammad Danesh Science and Technology University)

Co-Authors

H-index: 18
Dr. Md Palash Uddin

Dr. Md Palash Uddin

Deakin University

H-index: 11
Masud Ibn Afjal

Masud Ibn Afjal

Hajee Mohammad Danesh Science and Technology University

H-index: 8
Adiba Mahjabin Nitu

Adiba Mahjabin Nitu

Hajee Mohammad Danesh Science and Technology University

H-index: 6
Emran Ali

Emran Ali

Deakin University

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