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Lecturer, Department of CSE

Md. Rashed

Designation: Lecturer, Department of CSE

Qualification: B.Sc. (Engr.) in ICE from Pabna University of Science and Technology

Mobile: +880 1780-340222

E-mail: rashedulislam.ice.pust@gmail.com & md.rashed@uob.edu.bd

Md. Rashed is a Lecturer in Computer Science and Engineering at the University of Brahmanbaria. He is a passionate researcher specializing in computer vision, medical image analysis, and deep learning. He holds a B.Sc. (Engr.) in Information and Communication Engineering from Pabna University of Science and Technology, where he developed SE-UNet: Spatial and Channel Refinement for Robust Multi-Anatomical Structure Segmentation in Abdominal Ultrasound.

With a strong record of publications in peer-reviewed journals, including Healthcare Technology Letters, Scientific Reports, IEEE FMLDS, and CIEES, his research focuses on deep learning for medical imaging, computer vision, and intelligent healthcare systems. He has contributed to multiple research projects, including a UGC-funded AI-based real-time fire and accident detection system, where he worked on data preprocessing, model development, and system integration.

Currently, he is working as a Research Assistant at BioRAIN Lab and has prior experience as an Assistant Researcher at PUST, actively contributing to research in AI, Computer Vision, Biomedical Image Processing, and IoT. His work includes developing advanced architectures such as attention-based networks, fully convolutional models, and hybrid machine learning frameworks for real-world applications.

He has been awarded a Fully Funded Master’s Scholarship in Computer Science at Kocaeli University, Turkey; however, his study has not commenced due to visa constraints. He has also received multiple University Merit Scholarships (2021–2023). Additionally, his research received recognition through a Best Paper Award at IEEE CIEES 2025, highlighting his contributions to the field.

He is passionate about conducting impactful research and publishing in top-tier journals, including TMI, PAMI, MIA, and TIP, and conferences such as CVPR, MICCAI, MIDL, ISBI, ICLR, and ECCV. With strong expertise in Python, PyTorch, and large-scale experimentation, his goal is to advance state-of-the-art solutions in Medical Imaging, Computer Vision, and AI-driven systems.

Areas of Interest

Academic Qualifications

B.Sc. (Engineering) in Information and Communication Engineering,
Pabna University of Science and Technology (PUST), Pabna, Bangladesh
Year: 2023 (Examination held in 2025 due to COVID-19)

Higher Secondary Certificate (HSC)
Charfasson Govt. College, Bhola, Bangladesh
Group: Science | Year: 2019

Secondary School Certificate (SSC)
Osmanganj Secondary School, Bhola, Bangladesh
Group: Science | Year: 2017

Professional Experience

Research Assistant — BioRAIN Lab (March 2024 – Present)

Website Address: https://biorainlab.net/author/md.-rashed/

  • Conducting research in Artificial Intelligence, Deep Learning, Biomedical Image Processing, and Medical Image Analysis.
  • Working on deep learning-based medical image segmentation, classification, and healthcare applications.
  • Contributing to research publications and development of AI-based solutions for healthcare.

Assistant Researcher, Pabna University of Science and Technology (PUST) July 2024 – June 2025

  • Conducted research and supported academic research activities in Artificial Intelligence, Machine Learning, and Biomedical Image Processing.
  • Contributed to research projects involving medical image analysis, deep learning, and intelligent healthcare systems.
  • Assisted in research publication and technical development activities.
Research Experience

Journal Papers:

  1. Rashed, M. K. Hasan, M. I. Hossain, M. S. Hosain, A. H. A. Rahman, and S. Islam, “Trustworthy Deep Feature Extraction and Ensemble-Based Machine Learning Approach for Breast Cancer Detections.” Healthcare Technology Letters, 13, no. 1 (2026): e70062. https://doi.org/10.1049/htl2.70062. [Cite Score: 5.8] [IF: 3.3] [Q2]
  2. Rashed, Md. Riad Hassan, Md. Imran Hossain, Md. Rakibul Islam, Feroza Naznin, and Md. Zahidul Islam, “A Standardized Comparative Benchmark of Fully Convolutional and Hybrid Deep Networks for Multi-Anatomical Structure Segmentation in Ultrasound Imaging.” Biomedical Signal Processing and Control, Elsevier, 2026. [Q1] [Under Review] [Paper]
  3. Rashed, Faisal Iqbal Hiron, Md. Imran Hossain, Md. Sarwar Hosain, Ohidujjaman, Md. Zahidul Islam, and Tetsuya Shimamura, “ACMS–Net: A Lightweight Adaptive Multi-Scale Feature Learning with Cross-Scale Attention Network for Multi-Class Classification of Gallbladder Disease in Ultrasound Images.” Academic Radiology, Elsevier, 2026. [Q1] [Accepted but not online yet] [Paper]
  4. Rashed, Muhammad Jamil, Md. Imran Hossain, Adnan Kavak, Md. Riad Hassan, Ohidujjaman, Md. Sarwar Hosain, Özqür Çakır, and Hossein Fotouhi, “BADF-Net: A Method for Enhancing Abdominal Ultrasound Diagnosis via Boundary-Aware Dynamic Fusion Network-Based Multi-Anatomical Structure Segmentation.” Academic Radiology, Elsevier, 2026. [Q1] [Under Review] [Paper]
  5. Muhammad Jamil, Adnan Kavak, Hossein Fotouhi, Rashed, Emre Gezer, Alpaslan Burak İnner, and Gautam Srivastava, “AI-Assisted Nutrition Estimation and Exercise Support for Integrated Lifestyle Management in Patients with Diabetes.” Nutrients, 2026. https://doi.org/10.20944/preprints202608.2273.v1. [Q1] [Accepted] [Paper]
  6. Rashed, Md. Habibul Islam, Md. Imran Hossain, Md. Sarwar Hosain, Ohidujjaman, and Md. Zahidul Islam, “SE–UNet: Spatial and Channel Refinement for Robust Multi–Anatomical Structure Segmentation in Abdominal Ultrasound.” BMC Medical Imaging, Springer, 2026. https://doi.org/10.20944/preprints202607.1481.v1. [Q1] [Accepter but not online yet] [Paper]
  7. Rashed, Muhammad Jamil, Adnan Kavak, Md. Imran Hossain, A. F. M. Zainul Abadin, and Md. Zahidul Islam, “HybridMVNet: A Hybrid MobileNet-VGG19 Ensemble Framework for Accurate Lung Nodule Classification.” Diagnostics, 2026. [Q1] [Under Review] [Paper]
  8. Rashed, and Manik Kumer Saha, Manob Chandra. “Fine-Tuning Flan-T5 for Automated SOAP Note Generation from Doctor Patient Dialogues: A Lightweight and Deployable Clinical NLP Pipeline.” PLOS ONE, 2026. [Q1] [Submitted]
  9. Rashed, Md. Imran Hossain, Akif Mahdi, and Gulam Mustofa, “Hybrid Machine Learning Models for Accurate Type 2 Diabetes Mellitus Prediction Using a Stacking Classifier and a Meta-Model Approach.” Cureus Journals, 2, no. 1 (2025). doi: 10.7759/s44389-025-03135-0
  10. Hossain, Md. Imran, Md. Mojahidul Islam, Tania Nahrin, Rashed, and Md. Atiqur, “Improving Speech Emotion Recognition and Classification Accuracy Using Hybrid CNN-LSTM-KNN Model.” International Journal of Research Publication and Reviews (IJRPR), 2024. ISSN 2582-7421. [Paper]

 

Conference Papers:

  1. Rashed, M. I. Hossain, and A. Kavak, “Da-RDU-Net: Dual Attention and Residual Double U-Net for Colorectal Polyp Segmentation,” 2025 6th International Conference on Communications, Information, Electronic and Energy Systems (CIEES), Ruse, Bulgaria, 2025, pp. 1–6. doi: 10.1109/CIEES66347.2025.11300119. [Received the Best Paper Award] [Scopus Indexed]
  2. Rashed, M. I. Hossain, M. Z. Islam, and F. Naznin, “An Intelligent Video Surveillance System with Temporal-Enhanced YOLOv8 for Real-Time Fire, Accident, and License Plate Detection in Public Safety Monitoring,” 2025 IEEE International Conference on Future Machine Learning and Data Science (FMLDS), Los Angeles, CA, USA, 2025, pp. 139–144. doi: 10.1109/FMLDS67896.2025.00032. [Scopus Indexed]
  3. Rashed, Md. Basim Al Zabir Shammo, Md. Imran Hossain, Md. Anwar Hossain, and Jakaria Habib, “A Machine Learning Framework for Stress Detection Using Photoplethysmography (PPG) Signals,” 2025 International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN), pp. 1–5. IEEE, 2025. DOI: 10.1109/QPAIN66474.2025.11171913 [Scopus Indexed]
  4. Islam, Md. I. Hossain, Md. Rashed, M. B. A. Z. Shammo, M. H. Mohona, and Md. A. Miya, “Machine learning-based prediction of nightmares in children: A pediatric psychological integration,” Proceedings of the 2nd IEEE Conference on Computing Applications and Systems (COMPAS), October 23–24, 2025. doi: 10.1109/COMPAS67506.2025.11381639 [Scopus Indexed]
  5. slam, Md. Habibul, Rashed, Nitun Kumar Podder, Md. Imran Hossain, and Ankur Kumar Mondol, “Enhancing COPD Detection with WaveNet: Assessing the Efficacy of Deep Learning Model,” 2025 International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN), pp. 1–6. IEEE, 2025. doi: 10.1109/QPAIN66474.2025.11171716 [Scopus Indexed]
  6. Rashed, Md. Imran Hossain, and Md. Anwar Hossain, “Enhanced Prediction of Type-2 Diabetes Mellitus Using an Integrated Ensemble Framework (IEF),” 2024 27th International Conference on Computer and Information Technology (ICCIT), pp. 2512–2517. IEEE, 2024. doi: 10.1109/ICCIT64611.2024.11022451 [Scopus Indexed]
  7. Hossain, MD. R., Rashed, Hossain, Md. I., Mahdi, A., & Sumayta Shama. (2024). RA-UNET: A deep learning approach for precise colorectal polyp segmentation. In Undergraduate Conference on Intelligent Computing and Systems (UCICS 2024) [Conference-proceeding]. https://ucics.org/. [Paper]
  8. Kundu, M. R., Hossain, Md. I., Rashed, Rahim, Md. A., & Shama, S. (2024). Continuous Cuffless Blood Pressure Monitoring with Deep-Learning Techniques Utilizing PPG and ECG Features [Journal-article]. Undergraduate Conference on Intelligent Computing and Systems (UCICS 2024). https://ucics.org/. [Paper]


Research Grant:

  • AI-Based Real-Time Fire & Accident Detection System –Funded by the University Grants Commission (UGC). This project focused on developing a real-time surveillance system using YOLOv8 to detect fire incidents, road accidents, and vehicle number plates from CCTV footage. As a Project Assistant, I contributed to data preprocessing (including histogram equalization and optical flow), model training, and system integration. I also supported the implementation of a dual-alert notification system using Telegram and Twilio. The system efficient and scalable solution for enhancing public safety in urban Bangladesh.
SCHOLARSHIPS
  • University Merit Scholarship – 2021
  • University Merit Scholarship – 2022
  • University Merit Scholarship – 2023
AWARDS
  • Best Paper Award, our paper “Da-RDU-Net: Dual Attention and Residual Double U-Net for Colorectal Polyp Segmentation” received the Best Paper Award at the IEEE CIEES 2025             Conference held in Ruse, Bulgaria, between November 26-28, 2025.
  • Best Idea Donor, Innovation Showcase organized to implement e-Governance and Innovation Plan 2023-2024 under Annual Performance Agreement 2023-2024, PUST.
Skills

 

  • Programming Language: Python, C, C++, Java, PHP, HTML, MATLAB, Arduino
  • Database: Microsoft SQL Server, SQLite, MySQL
  • Operating System: Windows, Linux
  • Web Framework: Django, Bottle, Flask, WordPress (CMS)
  • Computer Tools: Cisco Packet Tracer, MATLAB, Proteus Design Suite, PICkit, PyCharm, LaTeX, and Microsoft Office.
Certification

Deep Learning with PyTorch: Image Segmentation – by Coursera Project Network

Issuing authority: Coursera; Credential ID: J9DDSNF5RK7U

Python for Everybody (Specialization) – by University of Michigan

Issuing authority: Coursera; Credential ID: 4VWXRCJBTJSA

Certificate of Appreciation as Reviewer – ICEEI2025

Issuing authority: 10th International Conference on Electrical Engineering and Informatics.

Venue and Date: November 13th- 15th, 2025, in Kuching, Sarawak, Malaysia.

 

Updated On: September 18, 2026