Md Kamrul Hasan

Md Kamrul Hasan

Research postgraduate in Medical Image Computing using AI at ICL and Faculty member (on Leave) in Electrical and Electronic Engineering at KUET

Imperial College London (ICL)

Khulna University of Engineering & Technology (KUET)

Biography

Md Kamrul Hasan is a PhD candidate in the Bioengineering department at Imperial College London (ICL), where he explores the deployment of AI agents like Physics-informed Neural Networks (PINNs) in the field of medical image computing. He is an Assistant Professor (on Leave) in Electrical and Electronic Engineering (EEE) at Khulna University of Engineering & Technology (KUET). Mr. Hasan’s research interest primarily concentrates on developing automated AI-based systems for medical appliances.

Mr. Hasan graduated from KUET in 2014 with a BSc in engineering in EEE, with a summa-cum-laude CGPA of 3.93 (out of 4.00) and taking first place out of 115 classmates. He graduated with a summa-cum-laude CGPA of 4.00 (out of 4.00) in 2017 after finishing his MSc engineering in EEE at KUET. Another MSc degree in Medical Imaging and Applications (MAIA) was earned by Mr. Hasan in 2019 through the Erasmus Mundus Joint Master Degree program from the University of Burgundy in France, University of Cassino and Southern Lazio in Italy, and University of Girona in Spain, obtaining a mark of 8.48 out of 10.0.

During his MAIA thesis at the EnCoV research team (Clermont-Ferrand, France), Mr. Hasan studied laparoscopic imaging and AI under the supervision of Professor Dr. Adrien Bartoli. The thesis presented an ART-Net to recognize, segment, and extract geometric features for 3D tool pose estimation of a surgical tool. The segmented masks were employed for tool-aware AR in minimally invasive laparoscopy, increasing its depth perception. The 3D tool posture was deployed for 3D measurement and overlaying the pre-operative 3D model onto the real-time laparoscopic image for computer-assisted laparoscopy. Later, the thesis was published in the Journal of Medical Image Analysis (Elsevier) in 2021 (Article).

Download Mr. Hasan’s Curriculum vitae.

Interests
  • Artificial Intelligence
  • Deep Learning
  • Physics-informed Neural Networks
  • Medical Image Computing
  • Computer Vision
  • Data Science
  • AR in Surgical Robotics
  • Biomedical Signal Processing
Education

  • PhD in Medical Image Computing using AI, 2026 (Expected)

    Imperial College London (ICL), United Kingdom

  • Erasmus Mundus Joint Master Degree Medical Imaging and Applications (MAIA), 2019

    University of Burgundy (France), University of Cassino and Southern Lazio (Italy), University of Girona (Spain)

  • MSc in Electrical and Electronic Engineering (EEE), 2017

    Khulna University of Engineering & Technology

  • BSc in Electrical and Electronic Engineering (EEE), 2014

    Khulna University of Engineering & Technology

All Publications

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Gestational diabetes prediction in pregnancy: A machine learning and data preprocessing approach
Gestational diabetes mellitus (GDM) is characterized by glucose intolerance during pregnancy, resulting in an elevated blood glucose …
Tanver Hasan Riyed, Tasnia Nabi, Aishwariya Dutta, Md. Kamrul Hasan, Ferdous Wahid Anik, Akid Ornob
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Gestational diabetes prediction in pregnancy: A machine learning and data preprocessing approach
A survey, review, and future trends of skin lesion segmentation and classification
The Computer-aided Diagnosis (CAD) system for skin lesion analysis is an emerging field of research that has the potential to relieve …
Md. Kamrul Hasan, Md. Asif Ahamad, Choon Hwai Yap, Guang Yang
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A survey, review, and future trends of skin lesion segmentation and classification
Breast Cancer Classification Using Ensemble of Machine Learning Boosting Algorithms
Breast Cancer (BC) is one of the numerous typical diseases worldwide, occurring in 22.9% of all cancers in women and causing 13.7% of …
Md. Kamrul Hasan, Md. Tasnim Jawad
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Breast Cancer Classification Using Ensemble of Machine Learning Boosting Algorithms
Development of a Smartphone-Based Expert System for COVID-19 Risk Prediction at Early Stage
COVID-19 has imposed many challenges and barriers on traditional healthcare systems due to the high risk of being infected by the …
M. Raihan, Md. Mehedi Hassan, Towhid Hasan, Abdullah Al-Mamun Bulbul, Md. Kamrul Hasan, Md. Shahadat Hossain, Dipa Shuvo Roy, Md. Abdul Awal
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Development of a Smartphone-Based Expert System for COVID-19 Risk Prediction at Early Stage
Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning Based Methods
The Bangla language is the seventh most spoken language, with 265 million native and non-native speakers worldwide. However, English is …
Ovishake Sen, Mohtasim Fuad, Md Nazrul Islam, Jakaria Rabbi, Mehedi Masud, Md Kamrul Hasan, Md Abdul Awal, Awal Ahmed Fime, Md Tahmid Hasan Fuad, Delowar Sikder, Md Akil Raihan Iftee
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Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning Based Methods
Challenges of deep learning methods for COVID-19 detection using public datasets
Since the COVID-19 pandemic, several research studies have proposed Deep Learning (DL)-based automated COVID-19 detection, reporting …
Md Kamrul Hasan, Md Ashraful Alam, Lavsen Dahal, Shidhartho Roy, Sifat Redwan Wahid, Md Toufick E Elahi, Robert Martí, Bishesh Khanal
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Challenges of deep learning methods for COVID-19 detection using public datasets
Early Prediction of Diabetes Using an Ensemble of Machine Learning Models
Diabetes is one of the most rapidly spreading diseases in the world, resulting in an array of significant complications, including …
Aishwariya Dutta, Md Hasan, Mohiuddin Ahmad, Md Awal, Md Islam, Mehedi Masud, Hossam Meshref
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Early Prediction of Diabetes Using an Ensemble of Machine Learning Models
DermoExpert: Skin lesion classification using a hybrid convolutional neural network through segmentation, transfer learning, and augmentation
Background and Objective: Although automated Skin Lesion Classification (SLC) is a crucial integral step in computer-aided diagnosis, …
Md Kamrul Hasan, Md Toufick E Elahi, Md Ashraful Alam, Md Tasnim Jawad, Robert Martí
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DermoExpert: Skin lesion classification using a hybrid convolutional neural network through segmentation, transfer learning, and augmentation
Understanding the nonlinear behavior of EEG with advanced machine learning in artifact elimination
Steady-state Visually Evoked Potential (SSVEP) based Electroencephalogram (EEG) signal is utilized in brain-computer interface …
Md Samiul Haque Sunny, Shifat Hossain, Nashrah Afroze, Md Kamrul Hasan, Eklas Hossain, Mohammad H Rahman
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Understanding the nonlinear behavior of EEG with advanced machine learning in artifact elimination
Associating measles vaccine uptake classification and its underlying factors using an ensemble of machine learning models
Measles is one of the significant public health issues responsible for the high mortality rate around the globe, especially in …
Md. Kamrul Hasan, Md Tasnim Jawad, Aishwariya Dutta, Md Abdul Awal, Md Akhtarul Islam, Mehedi Masud, Jehad F. Al-Amri
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Associating measles vaccine uptake classification and its underlying factors using an ensemble of machine learning models
COVID-19 identification from volumetric chest CT scans using a progressively resized 3D-CNN incorporating segmentation, augmentation, and class-rebalancing
The novel COVID-19 is a global pandemic disease overgrowing worldwide. Computer-aided screening tools with greater sensitivity are …
Md Kamrul Hasan, Md Tasnim Jawad, Kazi Nasim Imtiaz Hasan, Sajal Basak Partha, Md Masum Al Masba, Shumit Saha, Mohammad Ali Moni
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COVID-19 identification from volumetric chest CT scans using a progressively resized 3D-CNN incorporating segmentation, augmentation, and class-rebalancing
Emotion Recognition From EEG Signal Focusing on Deep Learning and Shallow Learning Techniques
Recently, electroencephalogram-based emotion recognition has become crucial in enabling the Human-Computer Interaction (HCI) system to …
Md Rabiul Islam, Mohammad Ali Moni, Md Milon Islam, Md Rashed-Al-Mahfuz, Md Saiful Islam, Md Kamrul Hasan, Md Sabir Hossain, Mohiuddin Ahmad, Shahadat Uddin, Akm Azad, Salem A. Alyami, Md Atiquar Rahman Ahad, Pietro Lio
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Emotion Recognition From EEG Signal Focusing on Deep Learning and Shallow Learning Techniques
Skin Lesion Classification Using Convolutional Neural Network for Melanoma Recognition
Skin cancer, also known as melanoma, is generally diagnosed visually from the dermoscopic images, which is a tedious and timeconsuming …
Aishwariya Dutta, Md Kamrul Hasan, Mohiuddin Ahmad
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Skin Lesion Classification Using Convolutional Neural Network for Melanoma Recognition
Multi-Class Probabilistic Atlas-Based Whole Heart Segmentation Method in Cardiac CT and MRI
Accurate and robust whole heart substructure segmentation is crucial in developing clinical applications, such as computer-aided …
Tarun Kanti Ghosh, Md Kamrul Hasan, Shidhartho Roy, Md Ashraful Alam, Eklas Hossian, Mohiuddin Ahmad
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Multi-Class Probabilistic Atlas-Based Whole Heart Segmentation Method in Cardiac CT and MRI
Ensemble of Convolutional Neural Networks to diagnose Acute Lymphoblastic Leukemia from microscopic images
Acute Lymphoblastic Leukemia (ALL) is a blood cell cancer characterized by the presence of excess immature lymphocytes., Even though …
Chayan Mondal, Md Kamrul Hasan, Mohiuddin Ahmad, Md Abdul Awal, Md Tasnim Jawad, Aishwariya Dutta, Md Rabiul Islam, Mohammad Ali Moni
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Ensemble of Convolutional Neural Networks to diagnose Acute Lymphoblastic Leukemia from microscopic images
Missing value imputation affects the performance of machine learning: A review and analysis of the literature (2010–2021)
Recently, numerous studies have been conducted on Missing Value Imputation (MVI), intending the primary solution scheme for the …
Md Kamrul Hasan, Md Ashraful Alam, Shidhartho Roy, Aishwariya Dutta, Md Tasnim Jawad, Sunanda Das
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Missing value imputation affects the performance of machine learning: A review and analysis of the literature (2010–2021)
Automatic Mass Classification in Breast Using Transfer Learning of Deep Convolutional Neural Network and Support Vector Machine
Mammography is the most widely used gold standard for screening breast cancer, where mass classification is a prominent step. …
Md. Kamrul Hasan, Tajwar Abrar Aleef, Shidhartho Roy
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Automatic Mass Classification in Breast Using Transfer Learning of Deep Convolutional Neural Network and Support Vector Machine
Diabetes prediction using ensembling of different machine learning classifiers
The risk factors and severity of diabetes can be reduced significantly if a precise early prediction is possible. The robust and …
Md Kamrul Hasan, Md Aahraful Alam, Dola Das, Eklas Hossian, Mahmudul Hasan
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Diabetes prediction using ensembling of different machine learning classifiers
Grasp-and-Lift Detection from EEG Signal Using Convolutional Neural Network
People undergoing neuromuscular dysfunctions and amputated limbs require automatic prosthetic appliances. In developing such …
Md Kamrul Hasan, Sifat Redwan Wahid, Faria Rahman, Shanjida Khan Maliha, Sauda Binte Rahman
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Grasp-and-Lift Detection from EEG Signal Using Convolutional Neural Network
Brain tissue segmentation using NeuroNet with different pre-processing techniques
Automatic segmentation of brain magnetic resonance imaging (MRI) images is one of the vital steps for quantitative analysis of the …
Fakrul Islam Tushar, Basel Alyafi, Md. Kamrul Hasan, Lavsen Dahal
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Brain tissue segmentation using NeuroNet with different pre-processing techniques
Prediction of Epileptic Seizure by Analysing Time Series EEG Signal Using kNN Classifier
Electroencephalographic signal is a representative signal that contains information about brain activity, which is used for the …
Md. Kamrul Hasan, Md. Asif Ahamed, Mohiuddin Ahmad, M. A and Rashid
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Prediction of Epileptic Seizure by Analysing Time Series EEG Signal Using kNN Classifier
User Independency of SSVEP Based Brain Computer Interface Using ANN Classifier: Statistical Approach
BCIs, which elaborated as Brain-computer Interface that use brain responses to control the BCI paradigms. These brain responses are …
Md. Kamrul Hasan, Md. Samiul H. Sunny, Shifat Hossain, Mohiuddin Ahmad
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User Independency of SSVEP Based Brain Computer Interface Using ANN Classifier: Statistical Approach
Design and Simulation of Maximum Power Point Tracking of Photovoltaic System Using ANN
Now a days in power generation, renewable energy plays a vital role in which photovoltaic energy generation placed top in the list of …
Md. Samiul Haque Sunny, Abu Naim Rakib Ahmed, Md. Kamrul Hasan
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Design and Simulation of Maximum Power Point Tracking of Photovoltaic System Using ANN
Drowsiness Detection for the Perfection of Brain Computer Interface Using Viola-jones Algorithm
Security and reconnaissance applications are prominent BCI paradigms which are less complex and sophisticated if there is no …
Md. Kamrul Hasan, S. M. Hasnat Ullah, Shantanu Sen Gupta, Mohiuddin Ahmad
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Drowsiness Detection for the Perfection of Brain Computer Interface Using Viola-jones Algorithm
Performance Analysis of SSVEP Based Wireless Brain Computer Interface for Wet and Dry Electrode
A Brain-computer Interface (BCI) is a communication pathway to provide ease to the users for interacting with the outside surroundings …
Md. Kamrul Hasan, Chayan Mondal, Mohiuddin Mahmud, Nahid Al , Ahmad
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Performance Analysis of SSVEP Based Wireless Brain Computer Interface for Wet and Dry Electrode
Alpha Band Dependency of EEG Signal on Different Stimulation of Brain for Human Computer Interaction
Brain-computer Interfaces (BCIs) are the communicating bridges between the human brain and a computer which may be implemented on the …
Md. Kamrul Hasan, Nahid Al Mahmud, Md. Shazzad Hossain, and Mohiuddin Ahmad
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Alpha Band Dependency of EEG Signal on Different Stimulation of Brain for Human Computer Interaction
Design and implementation of low cost ECG monitoring system for the patient using smartphone
Electrocardiographic (ECG) equipment plays a vital role for diagnosis of cardiac disease. However, the cost of this equipment is huge …
Md Asif Ahamed, Md Kamrul Hasan, Md Shahabul Alam
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Design and implementation of low cost ECG monitoring system for the patient using smartphone
Prediction of disease level using multilayer perceptron of Artificial Neural Network for patient monitoring
ANN has been proved as a powerful discriminating classifier for tasks in medical diagnosis for early detection of diseases. In our …
Md Osman Goni Nayeem, Maung Ning Wan, Md Kamrul Hasan
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Prediction of disease level using multilayer perceptron of Artificial Neural Network for patient monitoring
A SSVEP Based EEG Signal Analysis to Discriminate the Effects of Music Levels on Executional Attention
In this work the electrical activity in brain or known as electroencephalogram (EEG) signal is being analyzed to study the various …
Md. Kamrul Hasan, Md. Shazzad Hossain, Tarun Kanti Ghosh, Mohiuddin Ahmad
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A SSVEP Based EEG Signal Analysis to Discriminate the Effects of Music Levels on Executional Attention
Effect of Diverse Stimulations of Brain on EEG Signal for SSVEP Based Brain Computer Interface
Steady-state visual evoked potential (SSVEP) is used for Brain-Computer Interface that requires little training for user, offers high …
Md. Kamrul Hasan, Chayan Mondal, Nahid Al Mahmud, and Mohiuddin Ahmad
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Effect of Diverse Stimulations of Brain on EEG Signal for SSVEP Based Brain Computer Interface
Design and simulation of cost effective wireless EEG acquisition system for patient monitoring
The motive of this paper is to design a low cost wireless EEG acquisition system for easily monitoring of the patient. Using local …
Md. Kamrul Hasan, Rushdi Zahid Rusho, Toufiq Md. Hossain, Tarun Kanti Ghosh, Mohiuddin Ahmad
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Design and simulation of cost effective wireless EEG acquisition system for patient monitoring
A direct noninvasive brain interface with computer based on steady-state visual-evoked potential (SSVEP) with high transfer rates
A Brain Computer Interface (BCI) provides a new communication channel between human brain and the computer. This paper presents a …
Md. Kamrul Hasan, Rushdi Zahid Rusho, Mohiuddin Ahmad
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A direct noninvasive brain interface with computer based on steady-state visual-evoked potential (SSVEP) with high transfer rates

Popular Topics

3D pose estimation AI in medical imaging Augmented reality Biomedical instrumentation Biomedical signal processing Brain-computer interface Cardiac motion tracking CNNs Computer-assisted intervention Data preprocessing Data Science Deep learning Feature engineering Image classification Image registration Image segmentation Machine learning Medical image analysis Natural language processing

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