Sajeeb Kumar Ray
Experience
- Lecturer
- Department of Computer Science and Engineering
- Varendra University · Full-time
- Feb 2026 – Present*
- Researcher,
- BioRAIN Lab · Part-time
- Oct 2024 – Present*
- International Editorial Board Member,
- Journal of Applied Science, Engineering, Technology, and Education (ASCI)
- Jun 2025 – Present*
- Research Assistant,
- Dept. of ICE, Pabna University of Science and Technology
- May 2024 – Jun 2025
Academic
- B.Sc. (Engineering) in ICE · Dept. of Information and Communication Engineering, Pabna University of Science and Technology, Pabna, Bangladesh.
- CGPA: 3.91 out of 4.00 (Honours; First Position)
- Dean’s List
- Prospective Gold Medalist (awaiting final results)
- Higher Secondary School Certificate · Collectorate School and College Rangpur (CSCR), Rangpur · 2019
- GPA: 5.00 out of 5.00
- Secondary School Certificate · Jaldhaka Government Model Pilot High School (JGMPHS), Jaldhaka · 2017
- GPA: 5.00 out of 5.00
Biography
Sajeeb Kumar Ray is a Bangladeshi researcher and lecturer specializing in Deep Learning, Machine Learning, and Computer Vision. He has over three years of research experience in image transformation, classification, segmentation, registration, and explainable artificial intelligence. His recent research direction focuses on Multimodal Learning and Trustworthy AI, aiming to develop interpretable, reliable, and practically deployable intelligent systems.
He completed his BACHELOR OF SCIENCE IN ENGINEERING DEGREE WITH HONOURS in Information and Communication Engineering from Pabna University of Science and Technology (PUST), Bangladesh, graduating first in his class.
Currently, he serves as a Lecturer in the Department of Computer Science and Engineering at Varendra University (VU), Bangladesh, where he teaches Digital Image Processing and contributes to AI and computer vision research activities.
Research Interests
- Computer Vision
- Image Processing
- Deep Learning
- Multimodal Learning
- Trustworthy AI
- Explainable AI (XAI)
- Medical Image Analysis
Research Contributions
Healthcare AI
In the healthcare domain, he co-developed RViT-FusionNet, a hybrid CNN–Transformer framework for brain tumor diagnosis from MRI images, accepted for publication in Neural Computing and Applications (Springer, Q1).
The framework combines:
- ResNet-50 for local feature extraction
- Vision Transformers (ViT) for global contextual learning
- Local Cross-Attention (LCA) for feature fusion
- A domain discriminator for domain-invariant representation learning
Key contributions include:
- Hybrid CNN–Transformer architecture
- Cross-attention-based feature fusion
- Statistical t-test analysis
- Grad-CAM visualizations for explainability
The model demonstrated strong performance and interpretability for multi-class brain tumor classification using MRI images .
He also contributed to medical image segmentation research through XR-U-Net for X-ray image segmentation.
Agriculture AI
Sajeeb developed a Dual-Head CNN (DH-CNN) architecture for simultaneous plant species classification and disease identification. The work was published in the Journal of Agriculture and Food Research (Elsevier, Q1) and demonstrated strong performance for automated plant health monitoring .
He also proposed a Multi-Task Learning CNN (MTL-CNN) framework for fruit and vegetable freshness detection and classification .
His recent agricultural AI research explores hybrid CNN–Vision Transformer (ViT) architectures with:
- Cross-attention-based feature fusion
- Grad-CAM-based explainability
- Large-scale plant species and disease recognition
He initiated a mango fruit disease recognition project, leading the first systematic curation of a mango image dataset within his research group. The project evaluates optimized pretrained models and is being extended using:
- YOLO-based object detection
- Segment Anything Model (SAM)
- Automated agricultural diagnosis pipelines
Technical and Programming Background
Beyond AI research, Sajeeb completed three major embedded systems projects integrating hardware and intelligent software systems.
He is also an active competitive programmer with:
- Participation in 80+ programming contests
- 750+ solved algorithmic problems
Online Judge Achievements
- Specialist on Codeforces
- 4-Star on CodeChef
- Gold Badge on HackerRank
Leadership and Organizational Activities
Sajeeb has demonstrated strong leadership and organizational involvement through several academic and student organizations, including:
- Vice President of the ICE Association’s 1st Executive Committee
- Vice President of Solver Green
- General Secretary of the Nilphamari Student Welfare Society
- Founding Member of the PUST Career and Entrepreneurship Club
He contributed to organizing:
- Academic programs
- Innovation events
- Student activities
- 1st ICE Alumni Reunion
- ICE Fiesta – 2025
Awards and Achievements
- Dean’s List
- Student of the Year Award – 2025
- Academic Excellence Award – 2025
- Finalist – Disaster Hackathon 2.0
- Champion – Innovation Showcasing 2024
Research Vision
Sajeeb Kumar Ray’s current research direction focuses on developing Multimodal and Trustworthy AI systems that are:
- Explainable
- Reliable
- Interpretable
- Practically deployable
His long-term goal is to build intelligent systems that can be effectively used in real-world healthcare and agricultural environments.