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

 

 

 

Hyung-Pil Chang | Deep Learning | Best Researcher Award

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Mr. Hyung-Pil Chang | Deep Learning | Best Researcher Award

Mr at Korea University,  South Korea

Hyung-pil Chang is a dedicated graduate student at Korea University, pursuing a Ph.D. in Computer Science and Engineering. With a keen interest in deep learning and speech processing, he focuses on enhancing communication between humans and machines. He has contributed to several innovative projects in voice conversion and speech recognition, demonstrating a commitment to advancing technology in these fields. In addition to his academic pursuits, Chang actively engages in various sports and cultural activities, reflecting a well-rounded personality. His passion for research is complemented by his desire to develop practical solutions for real-world problems in artificial intelligence.

Profile

Scopus

Orcid

Scholar

Education 🎓

Hyung-pil Chang began his academic journey at Hansung University, where he earned a Bachelor of Science in Information System and Engineering from March 2014 to February 2020. He continued his studies at Korea University, obtaining a Master of Science in Computer Science and Engineering from 2020 to 2022. Currently, he is pursuing his Doctor of Philosophy in the same field at Korea University, enhancing his knowledge and expertise in deep learning, speech recognition, and human-computer interaction.

Experience 💼

Chang has gained valuable experience as a research assistant at Korea University’s Artificial Intelligence Laboratory since March 2020, working under the guidance of Prof. Dongsuk Yook. He has also served as a teaching assistant for undergraduate courses in Artificial Intelligence and Machine Learning, honing his teaching skills and sharing his knowledge with students. Additionally, he briefly worked in the Voice Generation Team at KT on a multi-modal project, where he contributed to advancements in voice conversion technologies, further solidifying his practical experience in the field.

Awards and Honors 🏆

Hyung-pil Chang has received recognition for his academic and research achievements, including publications in reputable journals such as MDPI Applied Sciences and IEEE Access. His contributions to voice conversion and speaker anonymization research have garnered attention in the field of speech processing. While specific awards are not listed, his active participation in conferences and collaboration on innovative projects highlight his commitment to excellence in research and development, positioning him as an emerging talent in artificial intelligence and deep learning.

Research Focus 🔬

Chang’s research centers on enhancing communication between people and machines, particularly in speech processing. He aims to improve speech recognition models using self-training techniques on large amounts of unlabeled data. His work also explores explainable AI and the development of a general-purpose domain agent capable of interacting with humans across various tasks, including vision and natural language processing. Key areas of focus include speech recognition, synthesis, voice conversion, and human-computer interaction, contributing to advancements in multi-modal language models.

📝 Conclusion

Hyung-pil Chang demonstrates strong potential as a leading researcher in deep learning and speech processing. His academic background, research contributions, and innovative spirit position him well for the Best Researcher Award. By focusing on collaboration, expanding his publication record, and engaging more with the broader community, he can enhance his impact even further. Given his current trajectory, he is well on his way to making significant contributions to his field and is a worthy candidate for recognition.

Publications Top Notes

  • Wav2wav: Wave-to-Wave Voice Conversion
    C Jeong, H Chang, IC Yoo, D Yook
    Applied Sciences, 2024, 14(10), 4251.

 

  • Zero-Shot Unseen Speaker Anonymization via Voice Conversion
    HP Chang, IC Yoo, C Jeong, D Yook
    IEEE Access, 2022, 10, 130190-130199.

 

  • CycleDiffusion: Voice Conversion Using Cycle-Consistent Diffusion Models
    D Yook, G Han, HP Chang, IC Yoo
    Applied Sciences, 2024, 14(20), 9595.