Mr. Ferdib Al Islam | Machine Learning | Excellence in Research
Assistant Professor, Northern University of Business and Technology Khulna Bangladesh
Ferdib-Al-Islam is an Assistant Professor at Northern University of Business and Technology Khulna, Bangladesh. He holds a Master’s and Bachelor’s degree in Computer Science and Engineering from Khulna University of Engineering & Technology (KUET) and Bangabandhu Sheikh Mujibur Rahman Science and Technology University (BSMRSTU), respectively. His research expertise encompasses Machine Learning, Deep Learning, IoT, Data Science, and Computer Vision. Ferdib’s career includes experience as a software engineer in IoT R&D and lecturer roles, contributing significantly to academic and research pursuits.
Publication Profile
🎓 Education
M.Sc. Eng. in Computer Science and Engineering from KUET (2023) – GPA: 3.50. B.Sc. Eng. in Computer Science and Engineering from BSMRSTU (2018) – GPA: 3.55. HSC in Science from Govt. PC College, Bagerhat (2012) – 5.00. SSC in Science from Bagerhat Govt. Secondary School (2010) – 5.00
💼 Experience
Ferdib has progressed from an intern to a Senior Lecturer, and now an Assistant Professor at Northern University of Business and Technology Khulna. He served as a Lecturer in Computer Science and Engineering from March 2020 to January 2024. His career also includes a Jr. Software Engineer role at W3 Engineers Ltd. in the IoT R&D sector. Ferdib brings practical industry experience into his academic roles, fostering innovation and research.
🏆 Awards & Honors
Ferdib has earned notable accolades, including the Gold Award at Semarak International Research Article Competition III 2024 for his work on Autism Spectrum Disorder detection. He also received the Best Paper Award at ICETIS 2021 for his research on Diabetes Mellitus prediction and the Honorable Mention Award at BDML 2020 for his IoT-based health monitoring tool.
🔬 Research Focus
Ferdib’s primary research interests are in Machine Learning, Deep Learning, IoT, Large Language Models, and Computer Vision. His work focuses on the application of AI techniques to healthcare, predictive modeling, and intelligent systems. His aim is to leverage machine learning for real-world applications like healthcare diagnostics, smart monitoring systems, and data-driven insights in various fields.
Conclusion
Ferdib Al-Islam is an exceptional researcher with notable accomplishments in machine learning, deep learning, and IoT. His commitment to advancing knowledge in these areas, demonstrated by his numerous awards and research contributions, marks him as a leading figure in his field. However, fostering greater interdisciplinary collaborations and increasing his global academic presence will be beneficial for his continued growth as a researcher. He is undoubtedly a deserving candidate for the Excellence in Research award, given his dedication, achievements, and potential for further contributions to the scientific community.
Publication Top Notes
- Prediction of Cervical Cancer from Behavior Risk Using Machine Learning Techniques
- Year: 2021
- Authors: L Akter, Ferdib-Al-Islam, MM Islam, MS Al-Rakhami, MR Haque
- Citation: 73
- An IoT Enabled Health Monitoring Kit Using Non-Invasive Health Parameters
- Year: 2021
- Authors: A Das, SD Katha, MS Sadi, Ferdib-Al-Islam
- Citation: 31
- Hepatocellular Carcinoma Patient’s Survival Prediction Using Oversampling and Machine Learning Techniques
- Year: 2021
- Authors: Ferdib-Al-Islam, L Akter, MM Islam
- Citation: 21
- An Enhanced Stroke Prediction Scheme Using SMOTE and Machine Learning Techniques
- Year: 2021
- Authors: Ferdib-Al-Islam, M Ghosh
- Citation: 20
- Early Identification of Parkinson’s Disease from Hand-drawn Images using Histogram of Oriented Gradients and Machine Learning Techniques
- Year: 2020
- Authors: Ferdib-Al-Islam, L Akter
- Citation: 19
- Dementia Identification for Diagnosing Alzheimer’s Disease using XGBoost Algorithm
- Year: 2021
- Authors: L Akter, Ferdib-Al-Islam
- Citation: 17
- COV-VGX: An automated COVID-19 detection system using X-ray images and transfer learning
- Year: 2021
- Authors: P Saha, MS Sadi, OFMRR Aranya, S Jahan, FA Islam
- Citation: 9
- Detection of Hepatitis C Virus Progressed Patient’s Liver Condition Using Machine Learning
- Year: 2022
- Authors: Ferdib-Al-Islam, L Akter
- Citation: 6*
- Diabetes Mellitus Prediction and Feature Importance Score Finding Using Extreme Gradient Boosting
- Year: 2021
- Authors: L Akter, Ferdib-Al-Islam
- Citation: 4
- COV-Doctor: A Machine Learning Based Scheme for Early Identification of COVID-19 in Patients
- Year: 2022
- Authors: Ferdib-Al-Islam, M Ghosh
- Citation: 3*
- Breast Cancer Risk Prediction Using Different Clustering Techniques
- Year: 2022
- Authors: L Akter, M Raihan, M Raihan, M Sarker, M Ghosh, N Alvi, Ferdib-Al-Islam
- Citation: 3
- Crop-RecFIS: Machine Learning Classifiers for Crop Recommendation and Feature Importance Scores Calculation
- Year: 2023
- Authors: MS Sanim, KM Hasan, MM Alam, MAA Walid, MR Islam
- Citation: 2
- Prediction of Dementia Using SMOTE Based Oversampling and Stacking Classifier
- Year: 2023
- Authors: Ferdib-Al-Islam, MS Sanim, MR Islam, S Rahman, R Afzal, KM Hasan
- Citation: 2*
- An Ensemble Learning Model to Detect COVID-19 Pneumonia from Chest CT Scan
- Year: 2022
- Authors: PC Shill
- Citation: 2