Md. Jalal Uddin Chowdhury

Lecturer

Co-Advisor, IEEE Computer Society LU SB Chapter

Computer Science & Engineering

Contact Information

Cell Phone: +8801646-705394
E-mail: [email protected]

Biography

𝐀𝐜𝐚𝐝𝐞𝐦𝐢𝐜 𝐁𝐚𝐜𝐤𝐠𝐫𝐨𝐮𝐧𝐝:
B.Sc. in CSE, Leading University, Sylhet.

𝐀𝐜𝐡𝐢𝐞𝐯𝐞𝐦𝐞𝐧𝐭:
Dean's Award from Leading University for Academic Excellence

Area of Study

Research Interest:

Machine Learning (ML)
Deep Learning (DL)
Computer Vision
Natural Language Processing (NLP)
Large Language Model (LLM)

Teaching Areas:

Structure Programming (Theory & Sessional)
Computer Algorithms & Complexity (Theory & Sessional)
Object Oriented Programming (Theory & Sessional)
Java Programming (Theory & Sessional)
Compiler Design and Construction (Theory & Sessional)
Machine Learning (Theory & Sessional)

Publications:

Islam, M.S., Chowdhury, M.J.U. et al. (2026) "SarcasmSense: A Novel Multitask Learning Framework for Vlog-Based Political Sarcasm and Irony Detection," in IEEE Access, doi: 10.1109/ACCESS.2026.3674402. [Q1 Journal]
Jisun, S.P., Chowdhury, M.J.U., Hira, M.M.H., Choudhury, T.E., and Rahe, E.A. (2025) BanglaSportsEmotion: A Sports-Focused Bangla Sentiment Corpus with Transformer and Classical Machine Learning Benchmarks. 28th International Conference on Computer and Information Technology (ICCIT) [Accepted]
Jisun, S.P., Chowdhury, M.J.U., Joy, B.D., Onnotoma, S.M. (2025) A Novel Bengali Spam Comment Dataset with Transformer-Based Classification for Social Media Content Moderation. 28th International Conference on Computer and Information Technology (ICCIT) [Accepted]
Kabya, N.D., Jisun, S.P., Chowdhury, M.J.U., Chy, E.H., Rahman, M.S. (2025) NeuroCBAM: Automated Attention-Driven Deep Network for Brain Tumor Classification from MRI. 28th International Conference on Computer and Information Technology (ICCIT) [Accepted]
Amin, M.A., Begum, H., Hasan, K.M.J., Chowdhury, M. J. U. "Ensemble and Transformer Models for Emotion Recognition in Bengali Consumer-Goods E-Commerce Comments" 2025 International Conference on Intelligent Data Analysis and Applications (IDAA 2025). [Accepted]
Tahsin, N.H., Akash, D.B., Rahman, M.N., Chowdhury, M. J. U. "EduXplore: A Centralized Application System for Facilitating Higher Education Abroad" 2025 International Conference on Emerging Technologies in Automation, Computation, and Electronics (EACE-2025). [Accepted & Presented]
Hossain, B., Tuhin, P.A., Ahmed, M.H., Chowdhury, M. J. U. "The Role Of Social Media in Sustaining and Organizing Movements: A Case Study Of JulyMovement in Bangladesh" 2025 International Conference on Big Data, IoT and Machine Learning (BIM 2025). [Accepted & Presented]
Chowdhury, M. J. U., Sultana , N. and Nath, A. D., "TeaLeafBD: Evaluation of a Proposed Dataset for Enhanced Tea Leaf Disease Identification Using Baseline Models," 2025 International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN), Rangpur, Bangladesh, 2025, pp. 1-6, doi: 10.1109/QPAIN66474.2025.11171904.
Absar, S., Miah, R., Shovo, S.S., Mony, M.J.I., Chowdhury, M.J.U. (2025). ViT-SAGE: A Hybrid Vision Transformer based Architecture with Graph Neural Network Fusion for Precise Kidney Disease Classification. IEEE 2nd International Conference on Computing, Applications, and Systems (COMPAS 2025). Index: Scopus. [Accepted & Presented]
Zummon, S.A., & Chowdhury, M. J. U. (2025). "Analyzing Climate Extremes in Sylhet: Investigating Rainfall Patterns for Flood Mitigation and Agricultural Resilience," 2025 International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN), Rangpur, Bangladesh, 2025, pp. 1-6, doi: 10.1109/QPAIN66474.2025.11172199.
Arifuzzaman, M., Ahmed, I., Chowdhury, M. J. U., Rahman, M. S., Hossain, M. E., Nath, A.D., & Absar, S.(2025). A Novel Ensemble-Based Deep Learning Model with Explainable AI for Accurate Kidney Disease Diagnosis. Adv. Artif. Intell. Mach. Learn., 5 (1 ):3425-3445
Sakib, S., Chowdhury, M.J.U., Hira, M.H., Choudhury, T.A., and Das, S. (2025) Deep Learning-Based Sentiment Analysis of Social Media and E-Commerce Reviews. 2025 IEEE 4th International Conference on Computing and Machine Intelligence (ICMI), MI, USA, 2025, pp. 1-5, doi: 10.1109/ICMI65310.2025.11141034.
Zummon, S.A., Chowdhury, M.J.U. (2025) "Enhancing Neurological Care: Multi-Label Classification Framework for Brain Disease Detection Using MRI," 2025 International Conference on Electrical, Computer and Communication Engineering (ECCE), Chittagong, Bangladesh, 2025, pp. 1-6. IEEE.
Rashid, D., Tohin, M. I., Chowdhury, M. J. U., & Mony, M. J. I. (2024, December). Enhancing Lung Cancer Classification Performance on Diverse Datasets: Utilizing Advanced Feature Selection and Novel Ensemble Approaches. In 2024 27th International Conference on Computer and Information Technology (ICCIT) (pp. 897-902). IEEE.
Tusar, S.D., Chowdhury, S.M.A.A., Chowdhury, M.J.U., Pir., R.M., Alam., H.M.N.A., Rahman., M.R., Siddiky., M.N.A., Rahman, M.E. (2024) Advancing Chronic Kidney Disease Prediction through Machine Learning and Deep Learning with Feature Analysis. Frontiers in Health Informatics, 13 (3), 11338-11348.
Sakib, S., Siddiky, M. N. A., Arifuzzaman, M., & Chowdhury, M. J. U. (2024, July). Optimizing Facial Recognition: An Analytical Comparison of Traditional and Deep Learning Approaches. In 2024 International Conference on Data Science and Its Applications (ICoDSA) (pp. 271-276). IEEE.
Arifuzzaman, M., Chowdhury, M. J. U., Ahmed, I., Siddiky, M. N. A., & Rashid, D. (2024, July). Heart Disease Prediction through Enhanced Machine Learning and Diverse Feature Selection Approaches. In 2024 IEEE 10th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA) (pp. 119-124). IEEE.
Chowdhury, M. J. U., & Kibria, S. (2023). Performance Analysis for Convolutional Neural Network Architectures Using Brain Tumor Datasets: A Proposed System. 2023 International Workshop on Artificial Intelligence and Image Processing (IWAIIP) (pp. 0163-0167). IEEE.
Chowdhury, M. J. U., Mou, Z.I., Afrin, R. & Kibria, S. (2023). Plant Leaf Disease Detection and Classification Using Deep Learning: A Review and A Proposed System on Bangladesh’s Perspective. International Journal of Science and Business, 28(1), 193-204.
Chowdhury, M. J. U., Hussan, A., Hridoy, D. A. I., & Sikder, A. S. (2023, March). Incorporating an Integrated Software System for Stroke Prediction using Machine Learning Algorithms and Artificial Neural Network. In 2023 IEEE 13th Annual Computing and Communication Workshop and Conference (CCWC) (pp. 0222-0228). IEEE.

Profile Links:

Others Responsibilities:

- Member Secretary, Departmental Research Community (CSE), (Feb'24 - Present)
- Advisor, CSE 67th Batch (Jan'26 - Present)
- Advisor, CSE 58th Batch (Jan'25 - Jan'26)

Publications

Optimizing Facial Recognition: An Analytical Comparison of Traditional and Deep Learning Approaches

Abstract – In the rapidly evolving domains of AI and Internet tech, face recognition, a key machine learning application, is increasingly used in security, identity verification, and public monitoring. As this technology progresses, its applications are expanding. A critical factor in its growing popularity is the advancement of the underlying algorithms, which drives its effectiveness […]

Heart Disease Prediction through Enhanced Machine Learning and Diverse Feature Selection Approaches

Abstract – According to a recent WHO report, heart-related problems are growing more widespread, with 17.9 million people suffering as a result each year. With a growing demographic, it becomes more difficult to detect and initiate treatment at an early stage. This arouses great interest in professionals in the field and researchers in creating more […]

Plant Leaf Disease Detection and Classification Using Deep Learning: A Review and A Proposed System on Bangladesh’s Perspective

Abstract – A very crucial part of Bangladeshi people’s employment, GDP contribution, and mainly livelihood is agriculture. It plays a vital role in decreasing poverty and ensuring food security. Plant diseases are a serious stumbling block in agricultural production in Bangladesh. At times, humans can’t detect the disease from an infected leaf with the naked […]

Performance Analysis for Convolutional Neural Network Architectures using Brain Tumor Datasets: A Proposed System

Abstract – Brain tumors remain a pressing global health concern, with high mortality rates despite significant medical advancements. The brain tumor is a potentially deadly condition, and its categorization creates an enormous challenge for radiologists due to the diverse composition of tumor cells. In recent times, there has been a growing interest in the development […]

Incorporating an Integrated Software System for Stroke Prediction using Machine Learning Algorithms and Artificial Neural Network

Abstract – A stroke is a condition where there is no flow of blood in the brain, depriving it of oxygen and resulting in long-term brain damage and loss of function. Most typically, a clot in an artery delivering blood to the brain is the culprit. Hemorrhage, in which blood leaks into the brain due […]