Md. Farukuzzaman Faruk

মোঃ ফারুকুজ্জামান ফারুক

Assistant Professor

  •   Deputy Director of Students' Welfare
  •  Room No:  Dept. Of CSE, RUET
  •  Phone:   880-1725344079
  •  Email:
  •  Website:
Deep Learning, Machine Learning, Biomedical Imaging, Signal Processing
Field of Research
  •  Deep Learning
  •  Machine Learning
  •  Biomedical Imaging
  •  Biomedical Signal Processing
ORCID Research Gate Google Scholar
  •  First Joined: 05th Nov, 2019
  •      Dept. of Computer Science & Engineering



Book / Book Chapter
Journal Articles
Conference Papers
SL Authors Title Publisher Details Publication Year Type
1 Anirban Barai , Md. Farukuzzaman Faruk , Shakil Mahmud Shuvo , Azmain Yakin Srizon, SM Mahedy Hasan, Abu Sayeed A Late Fusion Deep CNN Model for the Classification of Brain Tumors from Multi-Parametric MRI Images IEEE(NCIM-2023) 2023 Conference
2 Tahsen Islam Sajon, Barsha Roy, Md. Farukuzzaman Faruk, Azmain Yakin Srizon, Shakil Mahmud Shuvo, Md. Al Mamun, Abu Sayeed, S. M. Mahedy Hasan Attention Mechanism-enhanced Deep CNN Architecture for Precise Multi-Class Leukemia Classification Springer 2023 Conference
3 Shakil Mahmud Shuvo, Md. Farukuzzaman Faruk, Azmain Yakin Srizon, Tahsen Islam Sajon, S. M. Mahedy Hasan, Anirban Barai, A. F. M. Minhazur Rahman, Md. Al Mamun Multi-Class Brain Tumor Classification with DenseNet Based Deep Learning Features and Ensemble of Machine Learning Approaches Springer 2023 Conference
4 Tahsen Islam Sajon, Maria Chowdhury, Azmain Yakin Srizon, Md. Farukuzzaman Faruk, S. M. Mahedy Hasan, Abu Sayeed, A. F. M. Minhazur Rahman Recognition of Leukemia Sub-types Using Transfer Learning and Extraction of Distinguishable Features Using an Effective Machine Learning Approach IEEE(ECCE 2023) 2023 Conference
5 Nahrin Jannat, S. M. Mahedy Hasan, Anwar Hossain Efat, Md Fakrul Taraque, Mostarina Mitu, Md. Al Mamun, Md. Farukuzzaman Faruk Stacking Ensemble Technique for Multiple Medical Datasets Classification: A Generalized Prediction Model IEEE(ECCE 2023) 2023 Conference
6 Md. Farukuzzaman Faruk, Md. Rabiul Islam and Emrana Kabir Hashi Screening Pathological Abnormalities in Gastrointestinal Images Using Deep Ensemble Transfer Learning IEEE 2022 Conference
7 Protiva Ahammed, Md. Farukuzzaman Faruk, Nasif Raihan and Mrinmoy Mondal Inception V3 Based Transfer Learning Model for the Prognosis of Acute Lymphoblastic Leukemia from Microscopic Images IEEE 2022 Conference
8 A. Y. Srizon, S. M. M. Hasan, M. F. Faruk, A. Sayeed and M. A. Hossain Human Activity Recognition Utilizing Ensemble of Transfer-Learned Attention Networks and a Low-Cost Convolutional Neural Architecture IEEE 2022 Conference
9 M. S. I. Shopnil, S. M. M. Hasan, A. Y. Srizon and M. F. Faruk Post-Pandemic Sentiment Analysis Based on Twitter Data Using Deep Learning IEEE 2022 Conference
10 Farukuzzaman Faruk VGGCovidNet: A Deep Convolutional Neural Network to Predict COVID-19 Cases from X-Ray Images IEEE 2021 Conference
11 Farukuzzaman Faruk RGU-Net: Residual Guided U-Net Architecture for Automated Segmentation of COVID-19 Anomalies Using CT Images IEEE 2021 Conference
12 Md. Farukuzzaman Faruk ResidualCovid-Net: An Interpretable Deep Network to Screen COVID-19 Utilizing Chest CT Images IEEE 2021 Conference
13 Mrinmoy Mondal; Md. Farukuzzaman Faruk; Nasif Raihan; Protiva Ahammed Deep Transfer Learning Based Multi-Class Brain Tumors Classification Using MRI Images IEEE 2021 Conference
14 Md. Ahsan Habib Raj , Md. Al Mamun & Md. Farukuzzaman Faruk CNN Based Diabetic Retinopathy Status Prediction Using Fundus Images IEEE 2020 Conference
15 Abu Sayeed, Abdul Alim, Ali Hossain & Md. Farukuzzaman Faruk Target Class Oriented Subspace Detection for Hyperspectral Image Classification by Using Mutual Information and Cross Cumulative Residual Entropy IEEE 2020 Conference
16 Md. Farukuzzaman Faruk and Abu Sayeed K-mer Based DNA Methylation Status Prediction Using Support Vector Machine IEEE 2019 Conference
  •  Best Paper Award in ICECTE-2019
Phd Students
IdNameThesis workCurrent Position
Masters Students
IdNameThesis workCurrent Position
Undergraduate Students
IdNameThesis workCurrent Position
Activity Description