Ferdib Al Islam | Machine Learning | Excellence in Research

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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

Google Scholar

🎓 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

 

 

 

Ronny Mabokela | NLP and AI | Best Researcher Award

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Mr. Ronny Mabokela | NLP and AI | Best Researcher Award

PHD at University of Johannesburg, South Africa

Koena Ronny Mabokela is a South African computer scientist with a diverse background in technology and education. Currently pursuing a PhD in Computer Science at the University of the Witwatersrand, he has built a career focused on speech technology, system integration, and tech innovation. With years of experience as an educator, lecturer, and researcher, he also holds a leadership role at the University of Johannesburg, where he serves as Acting Deputy Head of Department and Head of the Technopreneurship Centre. Koena is passionate about fostering technological advancements, particularly in education and enterprise systems.

Profile

Scholar

🎓 Education

Koena Ronny Mabokela holds a PhD in Computer Science from the University of the Witwatersrand (2020-2024). He earned a Master of Science in Computer Science with a focus on Speech Technology at the University of Limpopo (2012-2014). His academic journey includes a Bachelor of Science Honours in Computer Science (2011) and a Bachelor of Science in Computer Science and Mathematics (2008-2010), both from the University of Limpopo.

💼 Experience

Mabokela’s career spans various leadership and academic roles. He is currently the Acting Deputy HoD for CEPs/SLPs and Online at the University of Johannesburg. Previously, he served as the Head of the Technopreneurship Centre, managing strategy, projects, and research. He has taught various programming modules and supervised postgraduate students while conducting research and engaging in community development. His professional experience also includes roles at Vodacom and Telkom in business systems integration and product development.

🏆 Awards and Honors

Mabokela has received numerous accolades, including being a session chair for SATNAC 2014 and a peer reviewer for prestigious conferences like IEEE and SATANC. He has also contributed to the scientific community with his published research in areas such as sentiment analysis and AI for under-resourced languages. His leadership skills and contributions to innovation have been recognized throughout his academic and professional career.

🔬 Research Focus

Koena Mabokela’s research interests revolve around speech technology, AI, and multilingual sentiment analysis, particularly for under-resourced languages. He focuses on enhancing language identification and sentiment analysis systems for South African languages. His work includes exploring distant supervision approaches and applying AI to tackle social challenges, as seen in his published papers and presentations at international conferences. His research aims to bridge technological gaps in underrepresented languages and communities.

Conclusion

Koena Ronny Mabokela is an outstanding researcher with a diverse and impactful portfolio that bridges academia and industry. His extensive experience, leadership in academic development, and commitment to advancing knowledge in computer science and technology position him as a top candidate for the Best Researcher Award. While there are opportunities to expand his interdisciplinary work and enhance the practical impact of his research, his contributions to the academic community and the field of technology are significant. His future work promises to continue shaping the landscape of digital innovation and research.

Publications 📚