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Rashidul Hasan Hridoy

Exploring Data Science and Analytics, Sharing Experiences!

Lecturer, Department of Software Engineering, Daffodil International University, Bangladesh.
Former Lecturer, Department of Computer Science and Engineering, Daffodil International University, Bangladesh.

Greetings! I completed my Bachelor of Science in Computer Science & Engineering from Daffodil International University, Bangladesh. Now, I am working as a Lecturer at Daffodil International University, Bangladesh. I have been involved in research since 2020, and several of my research outcomes have already been published in renowned international journals, books, and conferences. My research interests include Machine Learning, Deep Learning, Computer Vision, Computational Biology, Natural Language Processing, and Internet of Things. Besides this, I review manuscripts in several Elsevier journals. Currently, I am working on several machine learning and deep learning methods for developing efficient systems for the healthcare and agriculture sectors.

Take a look at my ResearchGate, Google Scholar, or LinkedIn profile.
Email: rashidulhasanhridoy@gmail.com


Education

Bachelor of Science in Computer Science & Engineering, Daffodil International University, Bangladesh.
January 2017 - March 2021, CGPA 3.93 out of 4.00, 148 credits toward a bachelor’s degree.

Thesis title: Betel Leaf Disease Recognition Using Deep Learning.
Supervised by Dr. Md. Tarek Habib, Former Associate Professor, Department of Computer Science and Engineering, Daffodil International University.

Publication of undergraduate thesis:
I. R. H. Hridoy, M. T. Habib, M. S. Rahman, and M. S. Uddin, "Deep Neural Networks-Based Recognition of Betel Plant Diseases by Leaf Image Classification," Evolutionary Computing and Mobile Sustainable Networks, Lecture Notes on Data Engineering and Communications Technologies, Springer, Singapore, 2022, vol. 116, pp. 227-241.
II. R. H. Hridoy, M. T. Habib, I. Jabiullah, R. Rahman, and F. Ahmed, "Early Recognition of Betel Leaf Disease using Deep Learning with Depth-wise Separable Convolutions," IEEE Region 10 Symposium, Jeju, Republic of Korea, 2021, pp. 1-7.


Publications

Journal Article

I. R. H. Hridoy, A. D. Arni, and A. Haque, "Improved Vision-Based Diagnosis of Multi-Plant Disease Using an Ensemble of Deep Learning Methods," Int J Elec & Comp Eng, 2023, vol. 13, no. 5, pp. 15109-5117. DOI

II. R. H. Hridoy, A. D. Arni, S. K. Ghosh, N. R. Chakraborty, and I. Mahmud, "Performance enhancement of machine learning algorithm for breast cancer diagnosis using hyperparameter optimization," Int J Elec & Comp Eng, 2024, vol. 14, no. 2, pp. 2181-2190. DOI

Book Chapter

III. R. H. Hridoy, T. Yeasmin, and M. Mahfuzullah, "A Deep Multi-scale Feature Fusion Approach for Early Recognition of Jute Diseases and Pests," Inventive Systems and Control, Lecture Notes in Networks and Systems, Springer, Singapore, 2022, vol. 436, pp. 553-567. DOI

IV. R. H. Hridoy, M. T. Habib, M. S. Rahman, and M. S. Uddin, "Deep Neural Networks-Based Recognition of Betel Plant Diseases by Leaf Image Classification," Evolutionary Computing and Mobile Sustainable Networks, Lecture Notes on Data Engineering and Communications Technologies, Springer, Singapore, 2022, vol. 116, pp. 227-241. DOI

V. R. H. Hridoy, and A. Rakshit, "BGCNN: A Computer Vision Approach to Recognize of Yellow Mosaic Disease for Black Gram," Computer Networks and Inventive Communication Technologies, Lecture Notes on Data Engineering and Communications Technologies, Springer, Singapore, 2022, vol. 75, pp. 189-202. DOI

VI. P. Sarker, S. H. Islam, K. Akter, L. Rukhsara, and R. H. Hridoy, "A Deep Neural Networks-Based Food Recognition Approach for Hypertension Triggering Food," Third International Conference on Image Processing and Capsule Networks, Lecture Notes in Networks and Systems, Springer, Cham, 2022, vol. 514, pp. 360-373. DOI

VII. M. Hasan, N. Sakib, R. H. Hridoy, N. H. Ananto, S. Akhter, and M. T. Habib, "An LSTM-Based Word Prediction in Bengali," Inventive Communication and Computational Technologies. Lecture Notes in Networks and Systems, Springer, Singapore, 2022, vol. 383, pp. 931-944. DOI

VIII. S. Biswas, M. Islam, U. Sarker, R. H. Hridoy, and M. T. Habib, "Machine Learning-Based Depression Detection," Computer Networks and Inventive Communication Technologies. Lecture Notes on Data Engineering and Communications Technologies, Springer, Singapore, 2023, vol. 141, pp. 809-821. DOI

IX. A. K. M. T. Alam, Z. H. Nirob, A. J. Urme, A. Rahman, R. H. Hridoy, M. T. Habib, and F. Ahmed, "A Systematic Analysis for Machine Learning Based Cow Price Prediction," Business Intelligence. Lecture Notes in Business Information Processing, Springer, Cham, 2023, pp. 17-28. DOI

Conference Paper

X. R. H. Hridoy, A. D. Arni, and M. A. Hassan, "Recognition of Mustard Plant Diseases Based on Improved Deep Convolutional Neural Networks," IEEE Region 10 Symposium, Mumbai, India, 2022, pp. 1-6. DOI

XI. R. H. Hridoy, M. T. Habib, I. Jabiullah, R. Rahman, and F. Ahmed, "Early Recognition of Betel Leaf Disease using Deep Learning with Depth-wise Separable Convolutions," IEEE Region 10 Symposium, Jeju, Republic of Korea, 2021, pp. 1-7. DOI

XII. R. H. Hridoy, and M. R. A. Tuli, "A Deep Ensemble Approach for Recognition of Papaya Diseases using EfficientNet Models," 5th International Conference on Electrical Engineering and Information Communication Technology, Dhaka, Bangladesh, 2021, pp. 1-6. DOI

XIII. R. H. Hridoy, M. Afroz, and F. Ferdowsy, "An Early Recognition Approach for Okra Plant Diseases and Pests Classification Based on Deep Convolutional Neural Networks," Innovations in Intelligent Systems and Applications Conference, Elazig, Turkey, 2021, pp. 1-6. DOI

XIV. R. H. Hridoy, F. Akter, and A. Rakshit, "Computer Vision Based Skin Disorder Recognition using EfficientNet: A Transfer Learning Approach," International Conference on Information Technology, Amman, Jordan, 2021, pp. 482-487. DOI

XV. R. H. Hridoy, F. Akter, and M. Afroz, "An Efficient Computer Vision Approach for Rapid Recognition of Poisonous Plants by Classifying Leaf Images using Transfer Learning," 12th International Conference on Computing Communication and Networking Technologies, Kharagpur, India, 2021, pp. 1-7 DOI

XVI. R. H. Hridoy, F. Akter, M. Mahfuzullah, and F. Ferdowsy, "A Computer Vision Based Food Recognition Approach for Controlling Inflammation to Enhance Quality of Life of Psoriasis Patients," International Conference on Information Technology (ICIT), Amman, Jordan, 2021, pp. 543-548. DOI


Skills

Coding

Python, Java, C, R, PHP, and JavaScript.

Framework

Keras, TensorFlow, Pytorch, Laravel, and Java Swing.

Tools

Git & Github, Linux, and Bash.

Database

MySQL, and MongoDB.

Languages

Strong listening, reading, writing and speaking competencies for Bengali and English.

Also familiar with Data Analysis, Software Testing, Software Design and Development.



Contact

Email: rashidulhasanhridoy@gmail.com (Personal), rashidul15-8596@diu.edu.bd (Academic)

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