Dipta Justin Gomes

@cs.aiub.edu

Assistant Professor, Department of Computer Science
American International University-Bangladesh (AIUB)

Dipta Justin Gomes


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https://researchid.co/diptagomes
Completed my Masters of Science (MSc) in Computer Science from University of Ulster, Belfast, Northern Ireland in January, 2023. Before, I have completed my Higher Secondary Certificate (HSC) from Notre Dame College, Dhaka in 2013 and then started my undergraduate in Computer Information Systems at American International University-Bangladesh (AIUB) back in 2014. Since then, I fell in love with algorithms, programming languages and lastly Artificial Intelligence at all its diversities. During my undergradate, I have taken part in various national and international events organized all around the country; One of the achievements include 2nd Runner's Up position in National Hackathon 2016 organized by ICT Ministry of Bangladesh. After finishing my undergraduate, I joined Notre Dame College, Dhaka as a lecturer in the ICT department. Besides my job, I finished my Masters in Computer Science (MSc CS) at AIUB specializing in intelligent systems in 2019. I was awarded "Summa Cum Laude" for h

EDUCATION

Masters of Science in Computer Science, University of Ulster, Belfast, Northern Ireland (September 2021-January 2023)

Masters of Science in Computer Science, American International University-Bangladesh, Bangladesh (April 2018-August 2019)

Bachelor of Science in Computer Information Systems, American International University-Bangladesh, Bangladesh (January 2014-December 2017)

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Science
34

Scopus Publications

127

Scholar Citations

5

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • FRF-HHO: Early ovarian cancer prediction using explainable fuzzy random forest optimized by Harris Hawks algorithm
    K.M. Yeaser Arafat, Ahmed Hossain, Mushfika Ikfat, Md. Areful Amin, Kazi Tanvir, Dipta Gomes, Mahfujur Rahman
    Advances in Biomarker Sciences and Technology, 2026
    Ovarian cancer remains one of the most lethal gynecological malignancies, largely due to delayed diagnosis and the absence of reliable early screening tools. This study proposes an interpretable machine learning framework that integrates Fuzzy Random Forest (FRF) with Harris Hawks Optimization (HHO) for early ovarian cancer prediction using routine clinical data. The analysis was conducted on a publicly available dataset comprising 349 patient records with 51 clinical and biochemical features. To mitigate overfitting and data leakage, Recursive Feature Elimination with Cross-Validation (RFECV), preprocessing, and SMOTE–Tomek balancing were applied exclusively within the training data. A total of 31 relevant biomarkers were selected for model development. The HHO-optimized FRF achieved an accuracy of 94.12%, precision of 91.43%, recall of 96.07%, and an F1-score of 93.69%, outperforming several baseline ensemble and gradient boosting models evaluated under identical experimental conditions. Model interpretability was enhanced through SHAP and LIME analyses, which consistently identified AFP, HE4, CA125, and Age as influential predictors, aligning with established clinical knowledge. The high recall indicates strong sensitivity to cancer cases, an essential requirement for diagnostic support. Despite encouraging performance, the study is limited by its moderate sample size and a retrospective design. Consequently, the findings should be interpreted as preliminary. Future work will focus on validation using larger, multi-center cohorts and prospective studies to assess generalizability and clinical scalability. • Hybrid FRF-HHO model achieved 94.12% accuracy and 96.07% recall for early ovarian cancer prediction. • RFECV selected 31 key clinical biomarkers, improving diagnostic precision and reducing dimensionality. • Explainable AI (SHAP and LIME) revealed AFP, HE4, CA125, and Age as dominant diagnostic indicators. • Model demonstrated superior interpretability and reliability, outperforming existing ML frameworks statistically (p < 0.05).
  • SSC-BanglaTutor: A curriculum-aligned Bengali dataset for intelligent tutoring systems
    Eshraque Jabid Ifti, Fihab Ifty, Mehadi Hasan, Rahul Chandra Shil, Utshab Kumar Saha, Kazi Tanvir, Mahfujur Rahman, Dipta Gomes
    Data in Brief, 2026
    This dataset presents a Bengali-language dataset designed to fine-tune AI powered hint-based tutoring systems for the Secondary School Certificate (SSC) science curriculum in Bangladesh. This data includes 11,286 hint-based question-answer entries, comprising 4859 questions from Biology covering 14 chapters, 3034 from Chemistry across 12 chapters, and 3393 from Physics spanning 14 chapters. All items were created manually using government-issued textbooks, SSC focused study materials, and past exam question banks. Each question is paired with candidate answers containing one correct option and several closely related but incorrect options to help measure the effectiveness of the hints. A convergence score is attached to each entry, estimating how far a student may need to go through the hints to answer correctly. These features support personalized feedback and offer meaningful insight into the students' learning progress. The dataset is encoded in UTF-8, with some English terms retained for scientific precision and consistency with source materials. This makes it accessible to native learners while remaining valuable for low-resource Natural Language Processing (NLP) applications. By emphasizing curriculum alignment, ranked hinting, and learner modeling, the dataset provides a strong foundation for fine-tuning large language models (LLMs) and developing intelligent tutoring systems that are both linguistically inclusive and educationally effective.
  • Transforming Science Education Through Generative AI Through Adaptive Learning, Ethical Practices, and Inclusive Curriculum Design
    Dipta Gomes, Saikat Baul, Jubayer Ahamed, Dip Nandi
    Harnessing Generative Artificial Intelligence for Science Education, 2026
    This chapter explores the integration of GenAI into STEM education with a primary focus on Science education. It examines how GenAI can revolutionize teaching and learning by providing adaptive learning environments, personalized assessments, and real-time feedback that cater to the diverse needs of students also ensuring the ethical challenges associated with the implementation of GenAI, including concerns around bias, transparency, data privacy, and academic integrity. The chapter emphasizes the importance of balancing technological innovation with ethical practices to ensure equitable access and responsible use of GenAI tools. Looking ahead, the chapter outlines key future directions, including the refinement of adaptive learning tools and the need for AI literacy programs for educators. The chapter concludes by highlighting the potential of GenAI to transform science education while ensuring that it is used in ways that promote fairness, inclusivity, and accountability.
  • A Comprehensive Study on the Ethical Perspective of Integration of Agentic AI for Autonomous Vehicles
    Mirza Asif Mahmud, Mahfujur Rahman, Dipta Gomes, Kazi Tanvir, Md. Reazul Islam
    Agentic AI for Autonomous Vehicles Safety Reliability Law and Ethics, 2026
    This chapter explores the ethical integration of Agentic AI into autonomous vehicles, detailing a technical architecture that embeds ethical considerations across goal setting, memory, human oversight, transparency, and robustness. It highlights how V2X connectivity transforms AVs into collaborative agents within intelligent ecosystems. The chapter also presents evaluation frameworks and metrics to measure safety, fairness, and public trust, ensuring autonomous driving aligns with societal values and legal standards.
  • Technological Advances in Generative and Explainable AI for Next- Generation Cyber Defense
    Saikat Baul, Jubayer Ahamed, Md Sajid Bin-Faisal, Md. Khairul Alam Mazumder, Dipta Gomes, Victor Stany Rozario
    Rise of Explainable and Generative Aidriven Cyber and Information Security, 2026
    This manuscript surveys the transformative convergence of Generative AI (GenAI) and Explainable AI (XAI) in cybersecurity, addressing computational democratization and evolving threats like polymorphic malware 2.0, LLM-chaining, deepfakes, and adversarial poisoning. Through systematic review of 2022-2025 literature, it analyzes GenAI applications in SOCs such as dynamic playbooks, LLM threat hunting, GAN synthetic data—and critiques XAI limitations (e.g., SHAP latency), proposing neuro-symbolic hybrids and federated frameworks. Hardware innovations like AI-driven Trojan detection and PUFs are evaluated alongside taxonomies for unified paradigms. Findings reveal enhanced detection accuracy and interpretability, yet gaps in real-time scalability persist. Future directions emphasize causal reasoning, adversarial robustness, and regulatory compliance for trustworthy cyber defense.
  • Harnessing AI for Seamless E-Collaboration in Healthcare Through Building Smarter, Connected, and PatientCentric Systems
    Noboranjan Dey, Mahfujur Rahman, Shaikat Das Joy, Kazi Tanvir, Rahul Biswas, Dipta Gomes
    Strengthening E Collaboration in Healthcare Through AI, 2026
    This chapter explores the transformative role of Artificial Intelligence (AI) in healthcare, focusing on its evolution from experimental technology to a key driver of digital transformation and e-collaboration. It examines how advances in machine learning, natural language processing, robotics, blockchain, and Internet of Medical Things (IoMT) have enabled AI-powered tools to enhance patient care, clinical decision-making, and operational efficiency. The chapter highlights AI's impact across telemedicine, remote diagnostics, multidisciplinary collaboration, and personalized medicine, emphasizing how AI complements human expertise by automating routine tasks and enabling real-time data sharing. It also discusses challenges related to ethics, privacy, and regulation, while outlining future trends and global efforts to standardize AI adoption in healthcare.
  • Vision Language Models in Healthcare Through a Multimodal Approach to Medical Imaging and Clinical Applications
    Kazi Tanvir, Rahul Biswas, Dipta Gomes, Mahfujur Rahman, Noboranjan Dey, Md. Reazul Islam
    Vision Language Models for Next Generation Healthcare, 2026
    This chapter explores the emerging role of Vision Language Models (VLMs) in healthcare, focusing on their ability to integrate visual and textual data to improve medical imaging analysis and clinical decision-making. It examines the key components of VLMs, including vision and language models, their fusion techniques, and their applications in tasks like disease detection, report generation, and visual question answering. The chapter also addresses challenges such as data scarcity, privacy concerns, and model interpretability. Additionally, it highlights future directions for enhancing model generalization, improving explainability, and ensuring seamless integration into clinical workflows, while emphasizing the importance of ethical considerations and real-world validation for safe deployment in healthcare environments.
  • Synthetic Healthcare Data in Generation, Validation, and Integration for Ethical and Scalable Health Innovation
    Shaikat Das Joy, Noboranjan Dey, Md. Reazul Islam, Mirza Asif Mahmud, Mahfujur Rahman, Kazi Tanvir, Dipta Gomes
    Advances in Synthetic Healthcare Data Opportunities Challenges and Emerging Trends, 2026
    Synthetic healthcare data offers a transformative solution to the privacy and accessibility constraints of real patient data. This chapter comprehensively examines its generation, from traditional statistical methods to advanced AI like GANs, VAEs, and Transformers. It explores critical applications in clinical trial simulation, medical imaging, and AI training. The analysis extends beyond technology to address pivotal barriers: ethical concerns of bias, evolving GDPR/HIPAA regulations, validation challenges, and interoperability with systems like HL7 FHIR. It concludes that responsible adoption hinges on merging technical rigor with ethical governance and cross-disciplinary collaboration to build trustworthy, innovative digital health ecosystems.
  • An explainable ensemble learning framework for ovarian cancer classification using blood biomarkers
    Kazi Tanvir, Md. Sayem Kabir, Kazi Tasnim Hena, Tasnim Sultana Sintheia, Shanzida Zaman Shimu, Dipta Gomes, Mahfujur Rahman, Mirza Asif Mahmud
    Informatics and Health, 2026
    Background Ovarian cancer remains one of the most lethal gynecological malignancies, largely due to delayed diagnosis and the limited sensitivity of conventional screening approaches. Methods This study proposes an interpretable machine learning framework for the binary classification of ovarian cancer and benign ovarian tumors using routine blood biomarker data. A soft voting ensemble combining Histogram-Based Gradient Boosting and K-Nearest Neighbors was developed to capture complementary global and local data patterns. Class imbalance was mitigated using the ROSE resampling technique, while LASSO-based embedded feature selection improved model robustness and generalization. Model transparency was ensured through a comprehensive explainable AI pipeline incorporating SHAP, LIME, anchor rules, ELI5, Partial Dependence Plots, and surrogate decision trees. Findings The proposed ensemble consistently outperformed eleven benchmark classifiers across multiple resampling strategies, achieving a maximum accuracy and F1-score of 98.61Interpretation Integrating ensemble learning with multi-level explainability yields a highly accurate, reliable, and clinically interpretable diagnostic tool, supporting its potential adoption in real-world ovarian cancer screening and decision-support systems.
  • A Framework for Robust and Interpretable Yield-Risk Classification Using Country-Year-Crop Data (X- AMLF)
    Sk Muktadir Hossain, Sharif Eime Akhter, Ayswarjo Sarkar, Kazi Samia Mostofa, Md Sadiqur Rahman, Dipta Gomes, Mahfujur Rahman, Kazi Tanvir
    AI for Climate Governance Agriculture and Earth Systems, 2026
    This study introduces the Explainable Agro-Intelligence Machine Learning Framework (X-AMLF), which is a structured evaluation framework for yield risk classification in agriculture using aggregated country-year-crop data. A harmonised dataset was created by combining data on crop yield, annual average temperature, rainfall, pesticide use, crop identity, and country indicators to create 28,242 complete observations on the yield of 101 countries (1990–2016) for 10 major crops. Multiple classification models were evaluated, such as linear baselines and tree-based ensembles, and hyperparameters were optimised with Optuna to investigate variations in prediction and error behaviour. Under random splitting, ensemble models were able to get very high scores (e.g. Random forest F1 ≈ 0.976), but under a stricter evaluation, performance dropped. With country-holdout validation, the best-performing models had F1 ≈ 0.843, attenuation of performance when tested on unseen regions.
  • IoMT Architecture for Healthcare: Integration, Security, and Real-Time Decision Support
    Md. Reazul Islam, Mirza Asif Asif Mahmud, Kazi Tanvir, Shaikat Das Joy, Mahfujur Rahman, Noboranjan Dey, Dipta Gomes
    Robotics and Iot Synergy in Next Generation Healthcare, 2025
  • Fair Use Policies of Digital Contents: Some Observations and Recommendations
    Dr. Md. Manzurul Hasan, Md Shariful Alam, Shahadat Hossain, Dipta Gomes
    Icca 2024 3rd International Conference on Computing Advancements 2024, 2025
  • Smart agriculture using advancing tea leaf quality assessment with deep learning
    Md. Sayem Kabir, Mohammad Ariyan Pathan, Kazi Tanvir, Dipta Justin Gomes
    Intelligent Internet of Everything for Automated and Sustainable Farming, 2025
  • Innovative approaches to tomato leaf disease detection bridging tradition and technology
    Ahmed Imtiaz, Sk Muktadir Hossain, Rahat Rihan, Dipta Justin Gomes
    Intelligent Internet of Everything for Automated and Sustainable Farming, 2025
  • AI-driven insights into revolutionizing poultry farming with behavioral monitoring and ethical management
    Md. Sayem Kabir, Tasnim Sultana Sintheia, Kazi Tanvir, Dipta Justin Gomes
    Intelligent Internet of Everything for Automated and Sustainable Farming, 2025
  • Enhancing Capabilities and Security Features of Drone Networks Through Machine Learning: A Comprehensive Overview
    Dipta Gomes, Manzurul Hasan, Supta Richard Philip
    Advances in Science Technology and Innovation, 2025
  • Securing Patient Privacy and Data Protection by Federated Learning in AI- Driven Healthcare
    Dip Sarker, Md Tafhimul Haque Sadi, Dipta Gomes, Md. Manzurul Hasan
    Enabling Collaborative Health Intelligence with Federated Learning, 2025
  • Optimizing Workforce Productivity with TrackMee: An Online Resource Management System
    Md. Manzurul Hasan, Dipta Gomes, A M Touhidul, Shahadat Hossain
    2025 2nd International Conference on Next Generation Computing Iot and Machine Learning Ncim 2025, 2025
  • Hybrid Vision Transformer Naive Bayes Model for Mosquito Species Recognition with Virus Colony Search Optimization
    Farzana Nazera, Kazi Tanvir, Md. Sayem Kabir, MD. Shakil Hasan, Kazi Tasnim Hena, Dipta Gomes
    2025 IEEE International Conference on Quantum Photonics Artificial Intelligence and Networking Qpain 2025, 2025
  • Enhanced Java Plum Leaf Disease Classification Using ShuffleNetV2 and GSA-Tuned AdaBoost
    Md. Fahim Kabir Chowdhury, Md. Sayem Kabir, Sadman Samir Rafith, Kazi Tanvir, Farzana Nazera, Dipta Gomes
    2025 IEEE 2nd International Conference on Computing Applications and Systems Compas 2025, 2025
  • Automated Bladder Tissue Classification Using ViTXception with Explainable AI
    Md. Sayem Kabir, Mohammad Ariyan Pathan, Paul Tamal, Laboni Somoddar, Kazi Tanvir, Dipta Gomes
    2025 IEEE 7th International Conference on Sustainable Technologies for Industry 5 0 Sti 2025, 2025
  • Automated Classification of Husk Species Using DenseNet121 and Vision Transformer
    Dipta Gomes, Kazi Tanvir, Md. Sayem Kabir, Tasnim Sultana Sintheia, Sadman Samir Rafith, Mohammad Ariyan Pathan
    Communications in Computer and Information Science, 2025
  • Forecasting Crime Trends in Bangladesh Through a Pre and Post 2024 Political Shift Analysis Using Machine Learning
    Tonmoy Kumar Sarker, Dipankar Roy Dip, Abdullah Al Hasib, Md. Tafhimul Haque Sadi, Dip Sarker, Md. Rakibul Islam, Dipta Gomes
    2025 IEEE 2nd International Conference on Computing Applications and Systems Compas 2025, 2025
  • A Comprehensive Study of Advancements in Intelligent Tutoring Systems Through Artificial Intelligent Education Platforms
    Dipta Gomes
    Improving Student Assessment with Emerging AI Tools, 2024
  • An Experimental Analysis on Different Pivot Selection Approaches for the Quicksort Algorithm
    Jeba Tahsin, Dipta Gomes, Md. Manzurul Hasan
    2024 International Conference on Innovations in Science Engineering and Technology Innovative Technologies for Global Solutions Iciset 2024, 2024
  • An Efficient Integrated Negative Fractional Counting Sort Algorithm
    Dip Sarker, Dipta Gomes, Shahadat Hossain, Md. Manzurul Hasan
    2024 IEEE Conference on Computing Applications and Systems Compas 2024, 2024
  • Enhancing Watermelon Diseases Detection using Dense-EfficientNet and Explainable AI
    Jahidul Islam, Md. Sayem Kabir, K. M Tahsin Kabir, Tasnim Sultana Sintheia, Kazi Tanvir, Dipta Gomes
    2024 27th International Conference on Computer and Information Technology Iccit 2024 Proceedings, 2024
  • Robust Underwater Fish Detection Using an Enhanced Convolutional Neural Network
    , Dipta Gomes, A.F.M. Saifuddin Saif
    International Journal of Image Graphics and Signal Processing, 2021
  • A comprehensive study of real-time vacant parking space detection towards the need of a robust model
    Rifath Mahmud, A. F. M. Saifuddin Saif, Dipta Gomes
    Aiub Journal of Science and Engineering, 2021
  • Graceful Cascading Labelling Algorithm: Construction of Graceful Labelling of Trees
    Dipta Gomes, Md. Manzurul Hasan
    International Conference on Robotics Electrical and Signal Processing Techniques, 2021
  • Discovering rules for nursery students using apriori algorithm
    Mohammad Marufuzzaman, Dipta Gomes, Aneem Al Ahsan Rupai, Lariyah Mohd Sidek
    Bulletin of Electrical Engineering and Informatics, 2020
  • Robust underwater object detection with autonomous underwater vehicle: A comprehensive study
    Dipta Gomes, A. F. M. Saifuddin Saif, Dip Nandi
    ACM International Conference Proceeding Series, 2020
  • Banking queue waiting time prediction based on predicted service time using support vector regression
    Dipta Gomes, Rashidul Hasan Nabil, Kamruddin Nur
    Proceedings of International Conference on Computation Automation and Knowledge Management Iccakm 2020, 2020

RECENT SCHOLAR PUBLICATIONS

  • An explainable ensemble learning framework for ovarian cancer classification using blood biomarkers
    K Tanvir, MS Kabir, KT Hena, TS Sintheia, SZ Shimu, D Gomes, ...
    Informatics and Health , 2026
    2026
  • Navigating Stock Market Forecasting: A Comparative Study of Levenberg-Marquardt and BFGS Quasi-Newton Algorithms in Optimizing Feed-Forward Neural Networks
    MM Hasan, R Azad, D Gomes, S Hossain
    2025 28th International Conference on Computer and Information Technology … , 2026
    2026
  • BitterGNN: An Explainable Graph-Based Framework for Bitter Peptide Classification
    K Tanvir, D Gomes, M Rahman, MA Mahmud, MA Noor, MH Bhuyan
    2025 28th International Conference on Computer and Information Technology … , 2026
    2026
  • Explainable Breast Cancer Diagnosis with Vision Transformers and ACOR-Optimized Decision Trees
    SS Rafith, SM Rohan, MS Kabir, K Tanvir, D Gomes, M Rahman
    2025 28th International Conference on Computer and Information Technology … , 2026
    2026
  • Technological Advances in Generative and Explainable AI for Next-Generation Cyber Defense
    S Baul, J Ahamed, MS Bin-Faisal, MKA Mazumder, D Gomes, VS Rozario
    The Rise of Explainable and Generative AI-Driven Cyber and Information … , 2026
    2026
  • Developing a Negative Fractional Counting Sort Algorithm for Fast Real Number Sorting
    D Sarker, D Gomes, T Dey, MM Hasan, D Nandi
    AIUB Journal of Science and Engineering (AJSE) 24 (1), 67 - 74 , 2026
    2026
  • A Framework for Robust and Interpretable Yield- Risk Classification Using Country-Year- Crop Data (X-AMLF)
    SM Hossain, SE Akhter, A Sarkar, KS Mostofa, MS Rahman, D Gomes, ...
    AI for Climate Governance, Agriculture, and Earth Systems 1, 237-292 , 2026
    2026
  • SSC-BanglaTutor: A Curriculum-Aligned Bengali Dataset for Intelligent Tutoring Systems
    EJ Ifti, F Ifty, M Hasan, RC Shil, UK Saha, K Tanvir, M Rahman, D Gomes
    Data in Brief , 2026
    2026
  • Enhanced Java Plum Leaf Disease Classification Using ShuffleNetV2 and GSA-Tuned AdaBoost
    MFK Chowdhury, MS Kabir, SS Rafith, K Tanvir, F Nazera, D Gomes
    2025 IEEE 2nd International Conference on Computing, Applications and … , 2026
    2026
  • Forecasting Crime Trends in Bangladesh Through a Pre and Post 2024 Political Shift Analysis Using Machine Learning
    TK Sarker, DR Dip, AA Hasib, MTH Sadi, D Sarker,, MR Islam, D Gomes
    2025 IEEE 2nd International Conference on Computing, Applications and … , 2026
    2026
  • FRF-HHO: Early ovarian cancer prediction using explainable fuzzy random forest optimized by Harris Hawks algorithm
    KMY Arafat, A Hossain, M Ifkat, MA Amin, K Tanvir, D Gomes, M Rahman
    Advances in Biomarker Sciences and Technology , 2026
    2026
  • Transforming Science Education Through Generative AI Through Adaptive Learning, Ethical Practices, and Inclusive Curriculum Design
    D Gomes, S Baul, J Ahamed, D Nandi
    Harnessing Generative Artificial Intelligence for Science Education 1, 163-206 , 2026
    2026
  • Automated Classification of Husk Species Using DenseNet121 and Vision
    D Gomes, K Tanvir, MS Kabir¹
    Data Science, AI and Applications: First International Conference, ICDSAIA … , 2026
    2026
  • Securing the Future: Enhancing Cybersecurity and Resilience in Digital and Software Supply Chains
    MO Patwary, R Jarin, A Biswas, MMT Partho, D Gomes, MR Islam
    AI-Driven Cybersecurity Systems, Applications, and Resilient Infrastructure … , 2026
    2026
  • A Comprehensive Study on the Ethical Perspective of Integration of Agentic AI for Autonomous Vehicles
    MA Mahmud, M Rahman, D Gomes, K Tanvir, MR Islam
    Agentic AI for Autonomous Vehicles: Safety, Reliability, Law, and Ethics … , 2026
    2026
  • Vision Language Models in Healthcare Through a Multimodal Approach to Medical Imaging and Clinical Applications
    K Tanvir, R Biswas, D Gomes, M Rahman, N Dey, MR Islam
    Vision Language Models for Next-Generation Healthcare, 259-292 , 2026
    2026
  • Harnessing AI for Seamless E-Collaboration in Healthcare Through Building Smarter, Connected, and Patient-Centric Systems
    N Dey, M Rahman, SD Joy, K Tanvir, R Biswas, D Gomes
    Strengthening E-Collaboration in Healthcare Through AI, 1-48 , 2026
    2026
  • Synthetic Healthcare Data in Generation, Validation, and Integration for Ethical and Scalable Health Innovation
    SD Joy, N Dey, MR Islam, MA Mahmud, M Rahman, K Tanvir, D Gomes
    Advances in Synthetic Healthcare Data: Opportunities, Challenges, and … , 2026
    2026
  • Securing Patient Privacy and Data Protection by Federated Learning in AI-Driven Healthcare
    D Sarker, MTH Sadi, D Gomes, MM Hasan
    Enabling Collaborative Health Intelligence With Federated Learning 1, 317-352 , 2026
    2026
  • IoMT Architecture for Healthcare: Integration, Security, and Real-Time Decision Support
    MR Islam, MAA Mahmud, K Tanvir, SD Joy, M Rahman, N Dey, D Gomes
    Robotics and IoT Synergy in Next-Generation Healthcare, 305-340 , 2026
    2026
    Citations: 1

MOST CITED SCHOLAR PUBLICATIONS

  • A Comprehensive Study of Advancements in Intelligent Tutoring Systems through Artificial Intelligent Education Platforms
    D Gomes
    Improving Student Assessment With Emerging AI Tools , 2024
    2024
    Citations: 42
  • Robust Underwater Object Detection with Autonomous Underwater Vehicle: A Comprehensive Study
    D Gomes, AFMS Saif, D Nandi
    ICCA 2020: Proceedings of the International Conference on Computing … , 2020
    2020
    Citations: 30
  • Robust Underwater fish detection using an enhanced convolutional neural network
    D Gomes, AFMS Saif
    International Journal of Image, Graphics and Signal Processing 11 (3), 44 , 2021
    2021
    Citations: 10
  • Banking Queue Waiting Time Prediction based on predicted service time using Support Vector Regression
    D Gomes, RH Nabil, K Nur
    2020 International Conference on Computation, Automation and Knowledge … , 2020
    2020
    Citations: 8
  • Classification of Food Objects Using Deep Convolutional Neural Network Using Transfer Learning
    D Gomes
    International Journal of Education and Management Engineering (IJEME) 14 (2 … , 2024
    2024
    Citations: 7
  • Discovering rules for nursery students using apriori algorithm
    M Marufuzzaman, D Gomes, AAA Rupai, LM Sidek
    Bulletin of Electrical Engineering and Informatics 9 (1), 298-303 , 2020
    2020
    Citations: 5
  • Enhancing Watermelon Diseases Detection using Dense-EfficientNet and Explainable AI
    J Islam, MS Kabir, KMT Kabir, TS Sintheia, K Tanvir, D Gomes
    2024 27th International Conference on Computer and Information Technology … , 2025
    2025
    Citations: 4
  • A Comprehensive Study of Real-Time Vacant Parking Space Detection Towards the need of a Robust Model
    R Mahmud, AFMS Saif, D Gomes
    AIUB Journal of Science and Engineering (AJSE) 19 (3), 99-106 , 2020
    2020
    Citations: 4
  • A Lightweight Hybrid CNN Model for Classication of Arsenic-Induced Skin Lesions
    TS Sintheia, MS Kabir, K Tanvir, D Gomes, AI Jony, KT Hena
    Research Square , 2025
    2025
    Citations: 3
  • Enhancing Bangla Local Speech-to-Text Conversion Using Fine-Tuning Wav2vec 2.0 with OpenSLR and Self-Compiled Datasets Through Transfer Learning
    SM Hossain, R Rihan, A Imtiaz, PK Boni, D Gomes
    7th IEOM Bangladesh International Conference on Industrial Engineering and … , 2025
    2025
    Citations: 3
  • Innovative Approaches to Tomato Leaf Disease Detection Bridging Tradition and Technology
    A Imtiaz, SM Hossain, MR Rihan, D Gomes
    Intelligent Internet of Everything for Automated and Sustainable Farming , 2025
    2025
    Citations: 2
  • An Explainable Machine Learning Framework for Obesity Classification with Optimized Support Vector Machines
    K Tanvir, MS Kabir, TS Sintheia, KT Hena, D Gomes
    SSRN , 2025
    2025
    Citations: 2
  • IoMT Architecture for Healthcare: Integration, Security, and Real-Time Decision Support
    MR Islam, MAA Mahmud, K Tanvir, SD Joy, M Rahman, N Dey, D Gomes
    Robotics and IoT Synergy in Next-Generation Healthcare, 305-340 , 2026
    2026
    Citations: 1
  • Hybrid Vision Transformer Naive Bayes Model for Mosquito Species Recognition with Virus Colony Search Optimization
    F Nazera, K Tanvir, MS Kabir, MDS Hasan, KT Hena, D Gomes
    2025 International Conference on Quantum Photonics, Artificial Intelligence … , 2025
    2025
    Citations: 1
  • Enhancing capabilities and security features of Drone Networks through Machine Learning: A Comprehensive Overview
    D Gomes, MM Hasan, SR Philip
    Machine Learning for Drone-Enabled IoT Networks: Opportunities, Developments … , 2025
    2025
    Citations: 1
  • Weathering the Forecast: Using Data Mining Techniques to Investigate Temperature Effect on Ice Cream Sales
    A Bushra, M Hasan, D Gomes
    IEOM Society International, USA , 2025
    2025
    Citations: 1
  • A Hybrid Optimization and Tree-Based Learning Framework for Dengue Diagnosis Using Hematological Data
    K Tanvir, M Rahman, D Gomes
    Available at SSRN 5687196 , 2025
    2025
    Citations: 1
  • Fair Use Policies of Digital Contents: Some Observations and Recommendations
    DMM Hasan, MS Alam, S Hossain, D Gomes
    Proceedings of the 3rd International Conference on Computing Advancements … , 2024
    2024
    Citations: 1
  • An Efficient Integrated Negative Fractional Counting Sort Algorithm
    D Sarker, D Gomes, S Hossain, MM Hasan
    IEEE CONFERENCE ON COMPUTING APPLICATIONS AND SYSTEMS (COMPAS 2024) , 2024
    2024
    Citations: 1
  • An explainable ensemble learning framework for ovarian cancer classification using blood biomarkers
    K Tanvir, MS Kabir, KT Hena, TS Sintheia, SZ Shimu, D Gomes, ...
    Informatics and Health , 2026
    2026

GRANT DETAILS

Summa Cum Laude, Masters of Science in Computer Science, Highest Academic Honors for achieving a CGPA of more than 3.95. American International University-Bangladesh (AIUB)

Dean's List Honors for achieving a CGPA of more than 3.90 in my undergraduate.

Daily Star Award for achieving more than 6 A's in GCSE O Levels-2013

RESEARCH OUTPUTS (PATENTS, SOFTWARE, PUBLICATIONS, PRODUCTS)

2nd Runners Up at National Hackathon 2016. Link

Taking part as a Galactic Solver at National Space Apps Challenge, 29-30 April 2017. Link