Sabbir Hossen

B.Sc in Computer Science and Engineering,
Bangladesh University

Research Assistant,
National Institute of Textile Engineering and Research

Address: Kishoreganj, Dhaka, Bangladesh

About Me

I am a recent Computer Science and Engineering graduate from Bangladesh University with a strong foundation in Machine Learning (ML). I am currently working as a Research Assistant at National Institute of Textile Engineering and Research (NITER), a constituent institute of the University of Dhaka, under the supervision of Prof. Anichur Rahman, with additional research guidance from Dr. Abu Saleh Musa Miah. My research spans Natural Language Processing (NLP), Computer Vision (CV), Large Language Models (LLMs), and Vision-Language Models (VLMs). My research is driven by the fundamental question: How can we make LLMs and VLMs more efficient, adaptable, and capable when data and computational resources are limited?

This question shapes my broader interest in understanding how AI systems can learn, adapt, reason, and generalize effectively under real-world constraints. My long-term goal is to build computational systems in which language and vision models work together to interpret information and ground their reasoning in real-world settings. I hope to contribute techniques that support this goal across diverse application domains, including settings with limited data and resources. For more information about my research background, ongoing work, and academic experience, please see the Background, Highlights, and Publications sections.

If you are interested in research collaboration, have questions about my work, or would like to discuss a potential research opportunity, please feel free to reach out to me at sabbir.hossen@bu.edu.bd . You can also connect with me through my social profiles to follow my latest research activities, publications, projects, and other academic updates.

Research Interests

Natural Language Processing

Large Language Models (LLMs)
Information Extraction & Understanding
NLP for Real-World Applications

Computer Vision

Visual Representation Learning
Deepfake & Multimedia Forensics
Medical Image Analysis

Multimodal AI

Vision-Language Models (VLMs)
Multimodal Representation Learning
Multimodal Learning for Healthcare

Efficient AI

Efficient Deep Learning Architectures
Low-Resource Language Processing
AI for Resource-Constrained Settings

Latest Updates & News

Mar 2026
Our Paper “Explainable Machine Learning Framework for Cardiovascular Disease Diagnosis and Prognosis" has been accepted at 9th International Conference on Smart Computing and Systems Engineering (SCSE).
Dec 2025
Our Paper “TransCNN: A Hybrid CNN-Transformer Synergy for Reliable Deepfake Forensics" has been accepted at 28th International Conference on Computer and Information Technology (ICCIT).
Oct 2025
Our Paper "A Sophisticated Feature Vectorization-Based Stacked Machine Learning Approach for Fake News Detection in Bangla and English" has been accepted at Social Network Analysis and Mining [Q1].
Sep 2025
Appointed as a Research Assistant at National Institute of Textile Engineering and Research.
Jul 2025
New Preprint "An Efficient Deep Learning Framework for Brain Stroke Diagnosis Using Computed Tomography Images" is out. [Click Here]
Jun 2025
Our Paper "Jellyfish Species Identification: A CNN Based Artificial Neural Network Approach" has been accepted at 2nd International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN).
May 2025
Our Paper "StackTrace-AI: Identifying Generative AI Text Origins using Ensemble Learning" has been accepted at 2nd International Conference on Computing, Applications and Systems (COMPAS).
May 2025
Our Paper "Optimized Hybrid Cascaded Approach for Accurate Oral Cancer Detection in Histopathology Images Using Deep CNNs" has been accepted at IEEE 2nd International Conference on Next-Generation Computing, IoT and Machine Learning (NCIM).
Apr 2025
Our Paper "Social Media Sentiments Analysis on the July Revolution in Bangladesh: A Hybrid Transformer Based Machine Learning Approach" has been accepted at IEEE 17th International Conference on Electronics, Computers and Artificial Intelligence (ECAI).
Jan 2025
Our Paper "A Hybrid Machine Learning Approach Utilizing CNN Feature Extraction with Traditional Classifiers to Identify Strawberry Leaf Diseases" has been accepted at IEEE 4th International Conference on Electrical, Computer and Communication Engineering (ECCE).
Nov 2024
Our Paper "An Explainable AI Driven Machine Learning Approach for Maternal Health Risk Analysis." has been accepted at IEEE 27th International Conference on Computer and Information Technology (ICCIT).
Jun 2024
Successfully defended Bachelor's thesis, fulfilling all requirements for the B.Sc. degree in Computer Science.
May 2023
Appointed as an Undergraduate Research Assistant at NextGen AI Lab, Bangladesh University.