Faruk Ahmed

Lecturer, Department of Software Engineering, Daffodil International University, Dhaka, Bangladesh

AI researcher building lightweight, explainable deep learning for real-world deployment in agriculture and healthcare.

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Portrait of Faruk Ahmed

Research interests

Deep LearningComputer VisionExplainable AI (XAI)Lightweight Neural Architecture DesignMedical Image AnalysisEdge AI & TinyMLMachine Learning AlgorithmsBiomedical Engineering Applications
I am an AI researcher specializing in computer vision, explainable AI (XAI), and resource-efficient deep learning systems. My research focuses on designing lightweight neural architectures for real-world deployment in resource-constrained environments, medical image analysis, and trustworthy AI. I have demonstrated the ability to produce independent, high-quality research, publishing in Q1 journals (Scientific Reports, IEEE Access) and contributing 10 open-access datasets to the research community before completing my undergraduate degree.

Featured research projects

Explainable Minimal CNN for Tea Leaf Disease Detection

2024–2025

Lead Researcher (BSc Thesis)

  • Designed a custom ultra-lightweight CNN with only 49K trainable parameters (190KB) — a novel architectural contribution targeting edge deployment on resource-constrained devices.
  • Achieved 98% classification accuracy; deployed as an Android mobile application enabling real-time, offline inference directly in agricultural field settings.
  • Integrated Grad-CAM-based Explainable AI (XAI) techniques to provide interpretable, human-understandable model decisions for non-expert users.
49K params190KB98% accuracyAndroid deploymentGrad-CAM

Grad-CAM, Explainable Minimal CNN for Tea Leaf Disease Detection

AI-Enabled IoT Smart Irrigation System

2025

AI Lead & System Architect

  • Designed and implemented an end-to-end AI-integrated IoT framework for adaptive, sensor-driven irrigation scheduling using predictive ML models.
  • Achieved a 38% reduction in water consumption under field-tested conditions, demonstrating measurable real-world impact.
  • Awarded Award of Distinction at the 5th International Data Science Olympiad (IDSOL 2025), Hong Kong.
38% water reductionIDSOL 2025 Award of Distinction

LBNet: Lightweight CNN for Breast Cancer Classification with XAI

2025–2026

Co-Researcher

  • Co-developed an optimized lightweight CNN for mammographic breast cancer classification integrating XAI-based interpretability for clinical decision support.
  • Published in Scientific Reports (Nature Portfolio, Q1).
Scientific ReportsQ1Nature Portfolio

Publications

Journal Publications

  1. Ahmmed, J., Faruk Ahmed, Kabir, M. A., Ahad, M. T., Jadoon, M. A., Rehman, A. U., & Bermak, A. (2026). LBNet: an optimized lightweight CNN for mammographic breast cancer classification with XAI-based interpretability. Scientific Reports, 16.

    Q1, Nature Portfolio

  2. Ahmmed, J., Faruk Ahmed, Rehman, A. U., Ali, N., Kabir, M. A., & Bermak, A. (2026). HPrEd: A Tuned Ensemble with Model-Agnostic XAI to Explain Social Media's Association with Academic Productivity. IEEE Access.

    Q1, IEEE

  3. Ahad, M. T., Faruk Ahmed, Bhowmik, A. C., Mim, Z. M., Anu, A. D., & Busch, P. (2025). Exploring micro-credential affordances in Bangladeshi higher education. Education and Information Technologies, 1–33.

    Q1, Springer

  4. Islam, R., Ahad, M. T., Faruk Ahmed, Song, B., & Li, Y. (2024). Mental Health Diagnosis From Voice Data Using Convolutional Neural Networks and Vision Transformers. Journal of Voice.

    Elsevier

  5. Bhowmik, A. C., Ahad, M. T., Emon, Y. R., Faruk Ahmed, Song, B., & Li, Y. (2024). A customised Vision Transformer for accurate detection and classification of Java Plum leaf disease. Smart Agricultural Technology, 8, 100500.

    Elsevier

Conference Publications

  1. Faruk Ahmed, et al. (2025). DMX: A Weighted Softmax Fusion of Heterogeneous CNNs for Burmese Leaf Disease Classification. 28th International Conference on Computer and Information Technology (ICCIT) (pp. 1654–1659).

    IEEE

  2. Faruk Ahmed, et al. (2025). A Comprehensive Review of Machine Learning-Based Approaches for Malware Detection. 5th International Conference on Emerging Smart Technologies and Applications (eSmarTA), pp. 1–8.

  3. Faruk Ahmed, et al. (2024). Drug Addiction Analysis in Bangladesh Using Machine Learning. 15th International Conference on Computing Communication and Networking Technologies (ICCCNT), pp. 1–7.

    IEEE

  4. Faruk Ahmed, Emon, Y. R., Ahad, M. T., Munna, M. H., & Mamun, S. B. (2023). A fuzzy-based vision transformer model for tea leaf disease detection. International Conference on Trends in Computational and Cognitive Engineering, pp. 229–242.

    Springer Nature

  5. Faruk Ahmed, Sagor, S., Hossan, M. F., Faruk, A. B., Reyad, M. Z. I., & Das, I. (2025). GViT: A Customized Vision Transformer Model for Guava Leaf Disease Detection. [Presented] 3rd International Conference on Big Data, IoT and Machine Learning (BIM 2025).

  6. Faruk Ahmed, Hasan, M., Hossain, S., Ahmed, F., Hasan, M. K., & Ahmmed, J. (2025). DRX Ensemble: An Optimized Rank-Based Deep CNN Model for Java Plum Leaf Disease Classification. [Presented] 16th International Conference on Computing Communication and Networking Technologies (ICCCNT 2025).

  7. Faruk Ahmed, Sagor, S., Ahamed Neloy, M. H., Hossain Asif, M. A., Islam Reyad, M. Z., & Hossan, M. F. (2025). A Computationally Optimized Fine-Tuning Approach for CNN-Based Lung Cancer Detection. [Presented] 16th International Conference on Computing Communication and Networking Technologies (ICCCNT 2025).

  8. Hossain, S., Faruk Ahmed, et al. (2025). MXD: A Weighted Soft Voting Ensemble of Fine-Tuned CNNs for Blood Cancer Detection from Microscopic Images. [Presented] 16th International Conference on Computing Communication and Networking Technologies (ICCCNT 2025).

  9. Ahmmed, J., Faruk Ahmed, Kabir, M. A., Uddin, A. Z. M. J., & Bhuiyan, T. (2025). RVE: An Optimized Ensemble Model for Breast Cancer Detection. [Presented] 5th International Conference on Trends in Electronics and Health Informatics (TEHI 2025).

Open-access datasets

BDSIDSocial Media & Academic PerformanceMango Leaf AnnotationsBDRubberLeafTLD-BDSunflower Plant HealthLychee & Jackfruit Plant DiseasesLemonLENSCSADDrug Use Dynamics

Academic & teaching timeline

  1. Daffodil International University logo

    May 2021 – April 2025

    Bachelor of Science in Computer Science and Engineering

    Daffodil International University · Dhaka, Bangladesh

    • CGPA: 3.96/4.00
    • Achieved 1st Position in the Batch
  2. Daffodil International University logo

    January 2024 – January 2025

    Undergraduate Researcher, 4IR Research Cell

    Daffodil International University · Dhaka, Bangladesh

    • Conducted research on deep learning and computer vision systems for real-world applications, focusing on image analysis, feature representation learning, and model optimization.
    • Supervised and mentored 50+ undergraduate researchers in AI-focused projects and academic writing.
    • Led dataset curation, model training, evaluation, and deployment of multiple machine learning projects resulting in peer-reviewed publications and open-access dataset releases.
  3. Daffodil International University logo

    September 2025 – Present

    Lecturer, Department of Software Engineering

    Daffodil International University · Dhaka, Bangladesh

    • Teach core undergraduate courses: Introduction to Machine Learning (Theory & Lab), Artificial Intelligence Lab, Statistical Data Analysis (Theory & Lab), Research Methodology, and Data Structures.
    • Develop course materials, labs, and assessments; supervise student research projects in AI and computing.
    • Currently collaborating with department head on a research project in student mental health analysis using AI.

Awards & honors

Award of Distinction

5th International Data Science Olympiad (IDSOL 2025)

Hong Kong · 2025

Top international recognition for applied AI and data science innovation in a global competitive setting.

2nd Runner-Up, Project Showcasing Track

VisionX: AI-Powered National Innovation Challenge

Dhaka, Bangladesh · November 2025

Organized by the Department of Computer Science and Engineering, University of Dhaka

Honorable Mention (AI Category)

Blockchain Olympiad Bangladesh (BCOLBD 2025)

Dhaka, Bangladesh · 2025

Organized by Bangladesh ICT Division, BASIS, Bangladesh Computer Council, and others

Champion, Crack Dataset Contest 2024

DIU NLP Lab, Daffodil International University

Dhaka, Bangladesh · 2024

First place in a Machine Learning-based dataset analysis and problem-solving contest.

Finalist (AI Category)

Blockchain Olympiad Bangladesh (BCOLBD 2024)

Dhaka, Bangladesh · 2024

Editorial & review activities

Service & outreach

Skills

Programming

Python (advanced) · C/C++ · Java

AI & Machine Learning

Deep Learning (CNNs, Vision Transformers) · Transfer Learning · Ensemble Learning · Model Optimization · Explainable AI (XAI) · Grad-CAM · SHAP · LIME · Edge AI / TinyML

Computer Vision

Image Processing · OpenCV · Feature Extraction · Augmentation · Object Detection · Image Classification

Frameworks & Libraries

PyTorch · TensorFlow · Keras · Scikit-learn · NumPy · Pandas · Matplotlib

Research Skills

Independent research design · Academic writing · Dataset curation and publication · Peer review · Student mentoring