Abir Bin Yousuf is a Lecturer in the Department of Computer Science and Engineering at the University of Liberal Arts Bangladesh (ULAB). He completed his Bachelor of Science in Computer Science and Engineering from BRAC University, Bangladesh, in 2020. Later, he earned his Master of Science in Computer Science and Engineering from the same institution in 2025.
His research interests lie in machine learning, deep learning, and computer vision, with a particular emphasis on developing intelligent and assistive systems. During his undergraduate studies, he developed a food detection and calorie estimation system capable of identifying multiple food items from an image. The system was built using Convolutional Neural Networks (CNN) integrated with the Inception-V3 architecture.
In his postgraduate research, his master’s thesis focused on Bengali Sign Language Recognition, where he proposed a system capable of recognizing Bengali sign words and generating meaningful Bengali sentences. The system employed a hybrid deep learning architecture combining CNNs and Transformer models.
Bachelor of Science, Computer Science and Engineering (CSE)
School of Science & Engineering
MSc, BRAC University, Dhaka, Bangladesh, March 2025.
Thesis: A Hybrid CNN–Transformer Model for Bengali Sign Language Interpretation
Supervisor: Dr. Muhammad Iqbal Hossain, Associate Professor, BRAC University.
BSc, BRAC University, Dhaka, Bangladesh, December 2020.
Thesis: "FoodieCal: A Convolutional Neural Network Based Food Detection and Calorie Estimation System
Supervisor: Dr. Muhammad Iqbal Hossain, Associate Professor, BRAC University.
Machine Learning, Deep Learning, and Computer Vision, Natural Language Processing (NLP).
- S. A. Ayon, C. Z. Mashrafi, A. B. Yousuf, F. Hossain and M. I. Hossain, "FoodieCal: A Convolutional Neural Network Based Food Detection and Calorie Estimation System," 2021 National Computing Colleges Conference (NCCC), Taif, Saudi Arabia, 2021, pp. 1-6, doi: 10.1109/NCCC49330.2021.
9428820. [Accepted].
- Orientation to ULAB
- Induction Training for Tertiary Teachers
- Teaching and learning strategies
- Student Advising
- Use of Technology (Moodle)
- Assessment of Learning