Profile of Md. Fazle Rabbi

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Md. Fazle Rabbi

Professor

Department of Computer Science and Engineering (CSE)

Faculty of Computer Science and Engineering

Hajee Mohammad Danesh Science & Technology University, Dinajpur.

E-mail: rabbi@hstu.ac.bd

Mobile: +8801717012945


CAREER OBJECTIVE

    To be a good researcher as well as good academician.

RESEARCH INTEREST

    Artificial Intelligence, Machine Learning, Data Mining, Bio-informatics, Cryptography and information Security.

EDUCATION

  1. Masters of Science in Computer Science, 2018

    Jahangirnagar University (JU)

  2. B.Sc. in Computer Science and Engineering, 2008

    Hajee Mohammad Danesh Science and Technology University (HSTU)

  3. Higher Secondary School Certificate (HSC), 2002

    Nazipur Govt. College

  4. SecondarySchoolCertificate (SSC), 2000

    Nazipur High School


PROFESSIONAL EXPERIENCES

  1. Professor
    Hajee Mohammad Danesh Science and Technology University (HSTU), Dinajpur, Bangladesh.

    September 17, 2023 to Present

  2. Associate Professor
    Hajee Mohammad Danesh Science and Technology University (HSTU), Dinajpur, Bangladesh.

    September 17, 2018 to September 16, 2023

  3. Assistant Professor
    Hajee Mohammad Danesh Science and Technology University (HSTU), Dinajpur, Bangladesh.

    May 10, 2013 to September 16, 2018

  4. Lecturer
    Hajee Mohammad Danesh Science and Technology University (HSTU), Dinajpur, Bangladesh.

    May 10, 2010 to May 09, 2013

  5. Lecturer (Part- time)
    Hajee Mohammad Danesh Science and Technology University (HSTU), Dinajpur, Bangladesh.

    May 04, 2009 to May 09, 2010

  6. System Engineer
    RingTech Limited

    March 20, 2008 to May 03, 2009


PUBLICATIONS

Journal Papers

  1. Md. Fazle Rabbi, Md. Palash Uddin, Md. Arshad Ali, Md. Faruk Kibria, Masud Ibn Afjal, Md. Safiqul Islam and Adiba Mahjabin Nitu (2018). Performance Evaluation of Data Mining Classification Techniques for Heart Disease Prediction. American Journal of Engineering Research (AJER). E-ISSN: 2320-0847 P-ISSN: 2320-0936. Volume-7, Issue-2, pp-278-283.

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  2. Mahmudul Hasan, Md. Fazle Rabbi, Md. Nahid Sultan, Adiba Mahjabin Nitu and Md Palash Uddin, A Novel Data Balancing Technique via Resampling Majority and Minority Classes Toward Effective Classification. TELKOMNIKA (Telecommunication, Computing, Electronics and Control), (2020 SJR IF=0.26, Scopus, Q3), Volume-21, Issue-6, pp-1308-1316, ISSN: 1693-6930 e-ISSN: 2302-9293, 2023.

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  3. Md. Arshad Ali, Yuta Kodera, Md. Fazle Rabbi, Takuya Kusaka, Yasuyuki Nogami, Satoshi Uehara, Robert H. Morelos-Zaragoza, Well Balanced Multi-value Sequence and its Properties Over Odd Characteristic Field. Advances in Science, Technology and Engineering Systems Journal (ASTESJ), Volume 4, Issue 4, Page No 188-196, 2019.

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  4. Md. Fazle Rabbi, Md. Nahid Sultan, Mahmudul Hasan and Md. Zahidul Islam, Tribal Dress Identification using Convolutional Neural Network, Journal of Information Hiding and Multimedia Signal Processing (JIHMSP), Volume-14, Number-03, ISSN: 2073-4212, pp-72-80, September 2023.

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  5. Md. Abu Sayeed Sardar, Hasi Saha, Md. Nahid Sultan and Md. Fazle Rabbi, Intrusion Detection in Electric Vehicles using Machine Learning with Model Explainability, Journal of Information Hiding and Multimedia Signal Processing (JIHMSP), Volume-14, Number-03, ISSN: 2073-4212, pp-81-89, September 2023.

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  6. Sharmin Sultana, Afrida Khanam, Md. Rashedul Islam, Adiba Mahjabin Nitu, Md. Palash Uddin, Masud Ibn Afjal and Md. Fazle Rabbi (2018). A Modified Filtering Approach of LSB Image Steganography Using Stream Builder along with AES Encryption. Recent Trends in Information Technology and its Applications. Volume-1, Issue-2, pp-1-10.

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  7. S.M. Hasan Mahmud, Md. Fazle Rabbi, Kazihise Ntikurako Guy-Fernand, (2016). An Agent-based Meta-Search Engine Architecture for Open Government Datasets Search, Communications on Applied Electronics (CAE), Volume 04, Number-07, ISSN : 2394-4714, pp: 21-25, March 2016.

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Conference Papers

  1. Md. Omar Faruk, Radiya Binte Reza, Sabbir Hossain Sourav, Mahmudul Hasan and Md. Fazle Rabbi, An Explainable AI Enable Approach to Reveal Feature Influences on Social Media Customer Purchase Decisions, 2nd International Conference on Big Data, IoT and Machine Learning 2023. September 06-08, 2023, Dhaka, Bangladesh.

  2. Md. Mahedi Hassan, Md. Fazle Rabbi, Mahmudul Hasan and Bhagyobandhu Roy, An Ensemble Machine Learning Approach to Classify Parkinsons Disease from Voice Signal, 2nd International Conference on Big Data, IoT and Machine Learning 2023. September 06-08, 2023, Dhaka, Bangladesh.

  3. Maksuda Bilkis Baby, Bushra Ankhari, Md. Shajalal, Md. Atabuzzaman, Md. Fazle Rabbi, and Masud Ibn Afjal, "Identifying Duplicate Questions Leveraging Recurrent Neural Network", in Springer 4th International Conference on Trends in Computational and Cognitive Engineering (TCCE-2022), Bangladesh, 2022.

  4.  Mahmudul Hasan, Md. Abu Marjan, Emran Ali, Md. Palash Uddin, Masud Ibn Afjal and Md. Fazle Rabbi, Predicting Agricultural Crop Cultivation and Production Rate in Bangladesh Using Machine Learning-based Approach, IEEE Computer Society Bangladesh Chapter Winter Symposium, November 13-14, 2020, Bangladesh.

  5. Sadi Mohammud Syfullah, Zareen Binta Zakaria, Md. Palash Uddin, Md. Fazle Rabbi, Masud Ibn Afjal and Adiba Mahjabin Nitu, "Efficient Vector Code-book Generation using K-means and Linde-Buzo-Gray (LBG) algorithm for Bengali Voice Recognition," IEEE International Conference on Advancement in Electrical and Electronic Engineering - (ICAEEE 2018), Bangladesh, 2018.

Book Chapter

  1. Md. Fazle Rabbi, Mahmudul Hasan Moon, Fahmida Tasnim Dhonno, Ayrin Sultana, and Mohammad Zoynul Abedin, 2022, Foreign Currency Exchange Rate Prediction Using Long Short-Term Memory, Support Vector Regression and Random Forest Regression, In: Financial Data Analytics, Springer Nature, Switzerland, pp. 251–267.

  2. Sad Wadi Sajid, Mahmudul Hasan, Md. Fazle Rabbi, and Mohammad Zoynul Abedin, 2023, An Ensemble LGBM (Light Gradient Boosting Machine) Approach for Crude Oil Price Prediction, In: Novel Financial Applications of Machine Learning and Deep Learning, International Series in Operations Research & Management Science, Springer Nature, Switzerland, pp. 153–165.

  3. Baby MB, Ankhari B, Shajalal M, Atabuzzaman M, Rabbi MF, and Afjal MI, 2023. Identifying Duplicate Questions Leveraging Recurrent Neural Network. In: Proceedings of the Fourth International Conference on Trends in Computational and Cognitive Engineering (Ed. Kaiser MS, Waheed S, Bandyopadhyay A, Mahmud M, and Ray K). Springer Nature, Singapore, pp. 331–341.


PROJECTS

  1. Hyperparameter Optimization of Classifiers and Feature Ranking to classify Liver Disease using Machine Learning Based Approach.

    Funded by: Institute of Research and Training (IRT) of HSTU.

    Position: Principle Investigator

    Description: FY 2022-2023; Completed

  2. Agricultural crop cultivation and production rate prediction in Bangladesh Using Deep Learning.

    Funded by: Institute of Research and Training (IRT) of HSTU.

    Position: Principle Investigator

    Description: FY 2021-2022; Completed

  3. Prediction of Flood in Non-tidal River in Dinajpur Using Machine Learning and Deep Neural Networks.

    Funded by: Institute of Research and Training (IRT) of HSTU.

    Position: Principle Investigator

    Description: FY 2020-2021; Completed

  4. Designing A 3-Layer Network Security Technique in Servers for Prevention of DDOS Attack.

    Funded by: Institute of Research and Training (IRT) of HSTU.

    Position: Principle Investigator

    Description: FY 2019-2020; Completed

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