Victor Stany Rozario

@aiub.edu

Assistant Professor, Department of Computer Science, Faculty of Science & Technology
American International University-Bangladesh

Victor Stany Rozario


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https://researchid.co/stany.rozario

RESEARCH, TEACHING, or OTHER INTERESTS

Artificial Intelligence, Computational Theory and Mathematics, Computer Science, Computer Science Applications
8

Scopus Publications

87

Scholar Citations

5

Scholar h-index

4

Scholar i10-index

Scopus Publications

  • A Lightweight Data Mining Approach for Fake Review Detection: An Integrated Textual and Behavioral Analysis
    Kazi Abdullah Jarif, Mst. Nadiya Noor, Moizuddin Mohammad Mujahid Rashid, Victor Stany Rozario
    Lecture Notes in Networks and Systems, 2026
  • AI Perspectives Within Computational Neuroscience: EEG Integrations and the Human Brain
    Zarif Bin Akhtar, Victor Stany Rozario
    Artificial Intelligence and Applications, 2025
    Current advancements within the realm of computational neuroscience, combined with the transformative capabilities of artificial intelligence (AI), have opened new paths for understanding the human brain’s interconnected complexity. This research exploration integrates electroencephalography (EEG), computational neuroscience, along with AI toward the investigation of complex cognitive mechanisms and neural activations associated with the various types of mental states. As a non-invasive tool, EEG mainly captures the internal electrical activity that reveals the interconnected cognitive processes in real time. By leveraging AI techniques—such as deep learning (DL), machine learning (ML), transfer learning, and convolutional neural networks (CNN)—this investigation deciphers EEG data to identify various specific neural patterns accompanying various types of cognitive states, memory formation, and especially toward emotional responses. To further refine these results and findings, this study organizes applications chronologically, presenting a developmental perspective on the AI-driven EEG advancements and their significance in detecting nuanced brain activity. This research not only addresses how experimental methods impact cognitive state reliability but also examines the amygdala’s role in EEG during emotional stimuli, thus expanding our multimodal level for understanding of emotional and memory-related neural signatures. By merging EEG data with AI-calibrated models, this investigation proposes new perspectives on the neural basis of attention, perception, and cognitive function, potentially informing early diagnosis of neurological disorders and enhancing brain-computer interfaces. Through this multidisciplinary lens, the exploration advances clinical applications and cognitive interventions, highlighting the interplay between EEG, computational neuroscience, and AI as an essential frontier in terms of both science and neurotechnology. Received: 26 August 2024 | Revised: 28 October 2024 | Accepted: 4 November 2024 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement The data that support the findings of this study are openly available in PhysioNet at https://www.nigms.nih.gov/; National Institute of Biomedical Imaging and Bioengineering at https://www.nibib.nih.gov/; NIH at https://archive.physionet.org/about.shtml; PhysioBank at https://archive.physionet.org/physiobank/; PhysioToolkit at https://archive.physionet.org/physiotools/. Author Contribution Statement Zarif Bin Akhtar: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization. Victor Stany Rozario: Supervision, Project administration.
  • Geo-temporal Disease Visualization of Bangladesh from Empirical Data Using Machine Learning
    Kawser Irom Rushee, Tabin Hasan, Victor Stany Rozario, Dip Nandi, Farzana Fariha
    Lecture Notes in Networks and Systems, 2025
  • Enhancing Breast Cancer Detection Systems: Augmenting Mammogram Images Using Generative Adversarial Networks
    Md. Rifat, Md. Sazid Uddin, Victor Stany Rozario, Dip Nandi
    Studies in Big Data, 2024
  • In-Depth Case Study on Artificial Neural Network Weights Optimization Using Meta-Heuristic and Heuristic Algorithmic Approach
    Victor Stany Rozario Rozario, Partha Sutradhar
    Aiub Journal of Science and Engineering, 2022
    The Meta-heuristic and Heuristic algorithms that have been introduced for deep neural network optimization is in this paper. Artificial Intelligence, and also the most used Deep Learning methods are all growing in popularity these days, thus we need faster optimization strategies for finding the results of future activities. Neural Network Optimization with Particle Swarm Optimization, Backpropagation (BP), Resilient Propagation (Rprop), and Genetic Algorithm (GA) is used for numerical analysis of different datasets and comparing each other to find out which algorithms work better for finding optimal solutions by reducing training loss. Genetic algorithm and also bio-inspired Particle Swarm Optimization is introduced in this paper. Besides, Resilient Propagation and Conventional Backpropagation algorithms which are application-specific algorithms have also been introduced. Meta-heuristic algorithms GA and PSO are a higher-level formula and problem-independent technique that may be used to a diverse number of challenges. The characteristic of Heuristic algorithms has extremely specific features that vary depending on the problem. The conventional Backpropagation (BP) based optimization, the Particle Swarm Optimization methodology, and Resilient Propagation (Rprop) are all fully presented, and how to apply these procedures in Artificial Deep Neural networks Optimization is also thoroughly described. Applied numerical simulation over several datasets proves that the Meta-heuristic algorithm Particle Swarm Optimization and also Genetic Algorithm performs better than the conventional heuristic algorithm like Backpropagation and Resilient Propagation.
  • Multi-Modal Case Study on MRI Brain Tumor Detection Using Support Vector Machine, Random Forest, Decision Tree, K-Nearest Neighbor, Temporal Convolution & Transfer Learning
    Partha Sutradhar, Prosenjit Kumer Tarefder, Imran Prodan, Md. Sheikh Saddi, Victor Stany Rozario
    Aiub Journal of Science and Engineering, 2021
    In the Medical field, Brain Tumor Detection has become a critical and demanding task because of its several shapes, locations, and intensity of image. That’s why an automated system is important to aid physicians and radiologists in detecting and classifying brain tumors. In this research, we have discussed different machine learning as well as deep learning algorithm which are mostly used for image classification. We have also compared different models that are being used for tumor classification based on machine learning and deep learning. MRI images of Glioma tumor, Pituitary tumor, Meningioma tumor are the base of this research, and we have compared different techniques along with the accuracy of different classification models using those MRI images. We have used different deep learning pre-trained models for training the brain tumor images. Those pre-trained models have provided outstanding performance along with less power consumption and computational time. EfficientNet-B3 has provided the best accuracy of 98.16% among other models as well as traditional machine learning algorithms. The experimental result of this model is proven the best and most efficient for tumor detection and classification in comparison with other recent studies.
  • The design approach of an artificial human brain in digitized formulation based on machine learning and neural mapping
    Zarif Bin Akhtar, Victor Stany Rozario
    2020 International Conference for Emerging Technology Incet 2020, 2020
  • Enhancing smartphone lock security using vibration enabled randomly positioned numbers
    M. Monjirul Kabir, Nasimul Hasan, Md Khalid Hassan Tahmid, Tanjil Ahmed Ovi, Victor Stany Rozario
    ACM International Conference Proceeding Series, 2020

RECENT SCHOLAR PUBLICATIONS

  • 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
    2026.0
  • A Lightweight Data Mining Approach for Fake Review Detection: An Integrated Textual and Behavioral Analysis
    KA Jarif, MN Noor, MMM Rashid, VS Rozario
    International Conference on Big Data, IoT and Machine Learning, 682-698 , 2025
    2025.0
  • EEG Integrations and the Human Brain Explorations: AI Perspectives towards Computational Neuroscience
    ZB Akhtar, VS Rozario
    Journal of Brain and Neurosciences 2 (1), 1-15 , 2025
    2025.0
  • AI perspectives within computational neuroscience: EEG integrations and the human brain
    ZB Akhtar, VS Rozario
    Artificial Intelligence and Applications 3 (2), 145-160 , 2025
    2025.0
    Citations: 16
  • A Comprehensive Analysis on Non-Communicable Diseases by Quantitative Approach: Using Graphical Visualization
    VS Rozario
    American Journal of Interdisciplinary Research and Innovation 3 (4(Special … , 2024
    2024.0
  • Enhancing breast cancer detection systems: augmenting mammogram images using generative adversarial networks
    M Rifat, MS Uddin, VS Rozario, D Nandi
    Data-driven clinical decision-making using deep learning in imaging, 167-187 , 2024
    2024.0
    Citations: 2
  • Geo-temporal Disease Visualization of Bangladesh from Empirical Data Using Machine Learning
    KI Rushee, T Hasan, VS Rozario, D Nandi, F Fariha
    International Conference on Trends in Electronics and Health Informatics … , 2023
    2023.0
  • In-Depth Case Study on Artificial Neural Network Weights Optimization Using Meta-Heuristic and Heuristic Algorithmic Approach
    P Sutradhar, VS Rozario
    The AIUB journal of science and engineering , 2022
    2022.0
    Citations: 4
  • Sentence-Level Emotion Apprehension Through Facial Expression & Speech Verification Analysis
    MM Haque, AF Polin
    ScienceOpen Preprints , 2022
    2022.0
    Citations: 1
  • Multi-modal case study on MRI brain tumor detection using support vector machine, random forest, decision tree, K-nearest neighbor, temporal convolution & transfer learning
    P Sutradhar, PK Tarefder, I Prodan, MS Saddi, VS Rozario
    AIUB Journal of Science and Engineering (AJSE) 20 (3), 107-117 , 2021
    2021.0
    Citations: 23
  • The design approach of an artificial human brain in digitized formulation based on machine learning and neural mapping
    ZB Akhtar, VS Rozario
    2020 International Conference for Emerging Technology (INCET), 1-7 , 2020
    2020.0
    Citations: 19
  • Enhancing smartphone lock security using vibration enabled randomly positioned numbers
    MM Kabir, N Hasan, MKH Tahmid, TA Ovi, VS Rozario
    Proceedings of the international conference on computing advancements, 1-7 , 2020
    2020.0
    Citations: 16
  • Community detection in social network using temporal data
    VS Rozario, AZM Chowdhury, MSJ Morshed
    arXiv preprint arXiv:1904.05291 , 2019
    2019.0
    Citations: 6
  • AgriHAFNet: A Dual Branch Neural Framework for Multi-Crop Disease Recognition
    SSZ Ahmed, B Biswas, SN Eity, T Fairooz, J Ahamed, VS Rozario, ...
  • Evaluating the Performance of Agile–Waterfall Integrated Approaches in Large Scale Engineering Projects in Bangladesh
    J Ahamed, ASM Alvy, VS Rozario, MA Ali, SM Abdullah, Z Labiba
  • Sentence-Level Emotion Apprehension Through Facial Expression & Speech Verification Analysis
    VS Rozario
  • Social Network Data Analysis for Community Detection
    SJ Morshed, AZME Chowdhury, VS Rozario

MOST CITED SCHOLAR PUBLICATIONS

  • Multi-modal case study on MRI brain tumor detection using support vector machine, random forest, decision tree, K-nearest neighbor, temporal convolution & transfer learning
    P Sutradhar, PK Tarefder, I Prodan, MS Saddi, VS Rozario
    AIUB Journal of Science and Engineering (AJSE) 20 (3), 107-117 , 2021
    2021.0
    Citations: 23
  • The design approach of an artificial human brain in digitized formulation based on machine learning and neural mapping
    ZB Akhtar, VS Rozario
    2020 International Conference for Emerging Technology (INCET), 1-7 , 2020
    2020.0
    Citations: 19
  • AI perspectives within computational neuroscience: EEG integrations and the human brain
    ZB Akhtar, VS Rozario
    Artificial Intelligence and Applications 3 (2), 145-160 , 2025
    2025.0
    Citations: 16
  • Enhancing smartphone lock security using vibration enabled randomly positioned numbers
    MM Kabir, N Hasan, MKH Tahmid, TA Ovi, VS Rozario
    Proceedings of the international conference on computing advancements, 1-7 , 2020
    2020.0
    Citations: 16
  • Community detection in social network using temporal data
    VS Rozario, AZM Chowdhury, MSJ Morshed
    arXiv preprint arXiv:1904.05291 , 2019
    2019.0
    Citations: 6
  • In-Depth Case Study on Artificial Neural Network Weights Optimization Using Meta-Heuristic and Heuristic Algorithmic Approach
    P Sutradhar, VS Rozario
    The AIUB journal of science and engineering , 2022
    2022.0
    Citations: 4
  • Enhancing breast cancer detection systems: augmenting mammogram images using generative adversarial networks
    M Rifat, MS Uddin, VS Rozario, D Nandi
    Data-driven clinical decision-making using deep learning in imaging, 167-187 , 2024
    2024.0
    Citations: 2
  • Sentence-Level Emotion Apprehension Through Facial Expression & Speech Verification Analysis
    MM Haque, AF Polin
    ScienceOpen Preprints , 2022
    2022.0
    Citations: 1
  • 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
    2026.0
  • A Lightweight Data Mining Approach for Fake Review Detection: An Integrated Textual and Behavioral Analysis
    KA Jarif, MN Noor, MMM Rashid, VS Rozario
    International Conference on Big Data, IoT and Machine Learning, 682-698 , 2025
    2025.0
  • EEG Integrations and the Human Brain Explorations: AI Perspectives towards Computational Neuroscience
    ZB Akhtar, VS Rozario
    Journal of Brain and Neurosciences 2 (1), 1-15 , 2025
    2025.0
  • A Comprehensive Analysis on Non-Communicable Diseases by Quantitative Approach: Using Graphical Visualization
    VS Rozario
    American Journal of Interdisciplinary Research and Innovation 3 (4(Special … , 2024
    2024.0
  • Geo-temporal Disease Visualization of Bangladesh from Empirical Data Using Machine Learning
    KI Rushee, T Hasan, VS Rozario, D Nandi, F Fariha
    International Conference on Trends in Electronics and Health Informatics … , 2023
    2023.0
  • AgriHAFNet: A Dual Branch Neural Framework for Multi-Crop Disease Recognition
    SSZ Ahmed, B Biswas, SN Eity, T Fairooz, J Ahamed, VS Rozario, ...
  • Evaluating the Performance of Agile–Waterfall Integrated Approaches in Large Scale Engineering Projects in Bangladesh
    J Ahamed, ASM Alvy, VS Rozario, MA Ali, SM Abdullah, Z Labiba
  • Sentence-Level Emotion Apprehension Through Facial Expression & Speech Verification Analysis
    VS Rozario
  • Social Network Data Analysis for Community Detection
    SJ Morshed, AZME Chowdhury, VS Rozario