NAZMUL HUDA BADHON

Bachelor of Science | Deep Learning Research

Nazmul Huda Badhon – Graduate | Research in Deep Learning and Computer Vision

Nazmul Huda BADHON
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badhon15-4772@diu.edu.bd

+880 1903-906230

Dhaka, Bangladesh

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Nazmul Huda Badhon is a Bachelor of Science graduate in Computer Science and Engineering, Class of 2025, at Daffodil International University. His undergraduate thesis is on "Tabular data based lightweight convolutional neural networks for electricity energy demand prediction" under the supervision of Associate Professor Nazmun Nessa Moon. His research focuses on designing computationally efficient deep neural network architectures. He specializes in convolutional neural networks, and their applications in interdisciplinary fields.

Open to

Exploring research roles in Deep Learning & Computer Vision

Deep Learning · Machine Learning · Computer Vision

Academic Profile

My research journey began during my second year of undergraduate studies at Daffodil International University, Bangladesh. While studying there I took part in a semester exchange program at Dongseo University, South Korea, and this experience significantly strengthened my interest in deep learning and advanced AI research. During this period, I formed and worked with a dedicated research team, collaboratively developing machine learning and deep learning projects and systematically publishing our findings in peer-reviewed journals.

I have experience in international research collaboration with research teams across multiple countries. Throughout this journey, I have had the privilege of collaborating closely with my research mentor Imrus Salehin and team members SM Noman, Md Tomal Ahmed Sajib, Nazrul Amin, and Pritom Saha. These collaborations have resulted in 5 peer-reviewed publications in high-impact venues including Q1 and Q2: Global Energy Interconnection, Elsevier; Engineering Reports, Wiley; Taylor & Francis; These collaborations have contributed to applied research in machine learning, deep learning, and CNN-based image analysis within interdisciplinary domains.

Academic Highlights


  • Nazmul Huda Badhon with faculty members

    Undergraduate Thesis

    · Thesis: A novel Lightweight CNN · submitted under the supervision of Associate Prof. Moon, with Prof. Fernaz

  • Nazmul Huda Badhon participating in an international academic camp at Dongseo University, South Korea

    International Academic Camp

    · Busan, South Korea. International exposure while attending semester exchange.

  • Semester exchange at Dongseo University, South Korea

    Semester Exchange

    · Dongseo University, South Korea.
    Completed one semester with fully-funded GKS scholarship.

  • Nazmul Huda Badhon recognized as top performer in computer vision bootcamp at Daffodil International University

    Top Performer in Computer Vision Bootcamp

    · Daffodil International University, Bangladesh

My work and academic efforts have been recognized through key honors including the fully funded Global Korea Scholarship GKS in 2023 by the Government of the Republic of Korea and the Research Award in 2024 from the Division of Research and Department of Computer Science and Engineering at Daffodil International University. I was also acknowledged as a Top Performer in the Computer Vision and Deep Learning bootcamp for Medical Data at DIU.


Education

Bachelor of Science in Computer Science and Engineering

DIU Daffodil International University, Dhaka, Bangladesh
Duration: Spring 2022 – Fall 2025 CGPA: 3.88 / 4.00

Semester Exchange, Computer Engineering

Dongseo University Dongseo University, South Korea
CGPA: 3.94 / 4.50
GKS Scholarship Global Korea Scholarship (GKS) Fall 2023

Recent Key Publications

Nazmul Huda Badhon, Imrus Salehin, Md Tomal Ahmed Sajib, Md Sakibul Hassan Rifat, SM Noman, Nazmun Nessa Moon, " TLCNN: Tabular data-based Lightweight Convolutional Neural Network for Electricity Energy Demand Prediction. " In Global Energy Interconnection, Elsevier, December 2025.

Md Tomal Ahmed Sajib, Nazmul Huda Badhon, Imrus Salehin, Md Sakibul Hassan Rifat, Faysal Ahmed, Nazmun Nessa Moon, "A comparative deep learning methodology for plant insect image classification: assessment of CNN architectures and augmentation techniques " In MethodsX, December 2025.

Imrus Salehin, Md Tomal Ahmed Sajib, Nazmul Huda Badhon, Md Sakibul Hassan Rifat, Nazrul Amin, Nazmun Nessa Moon, "Systematic Literature Review of LLM–Large Language Models in Medical: Digital Health, Technology and Applications. " In Engineerinng Reports, September 2025.