Monirul I Mahmud

Chapter So Far

A curious man with a deep passion for areas in Multimodal AI, Blockchain, differential privacy, Machine Learning and Zero-Shot Vision-Language Models (VLM). Proficient in Python, TensorFlow, D3.js, Tableau, Matlab, PySpark, and committed to continuously advancing my expertise in these areas. As a Graduate student at Georgia Tech and Fordham University, I like to embrace cultural diversity, engage in interdisciplinary projects and contribute to creating sustainable solutions. Beside my academic and professional pursuits, I enjoy Football, Traveling, Hiking, and immersing myself in Research Innovations. Let's connect and explore the Dynamic World of Data together!

Latest Updates

Feb 2026

I'm excited to share that I’ve been accepted to the PhD in Computer Science at the University of Cincinnati, UT Arlington, University of Georgia and Lousiana State University from Fall 2026!

Dec 2025

Another Q1 Journal Acceptance: Attention and Residual Mechanism-based CNN Architecture (ARC-Net) with Enhanced Fairness Generalization for Deepfake Facial Image Detection

SEP 2025

Our paper "DFU_DIALNet" is now online! DOI: https://doi.org/10.1371/journal.pone.0330669

AUG 2025

Our paper "DFU_DIALNet: Towards Reliable and Trustworthy Diabetic Foot Ulcer Detection with Synergistic Confluence of Grad-CAM and LIME" is accepted at PLoS ONE (Q1 Tier)!

DEC 2024

A proud milestone in my journey—I've been accepted into the M.S. in Analytics program at Georgia Institute of Technology! Very excited to join one of the world's Top 10 CS Ranked universities.

NOV 2024

Our paper "Linear Discriminant Analysis in Credit Scoring: A Transparent Hybrid Model Approach" has been accepted to IEEE International Conference on Computer and Information Technology (ICCIT) 2024.

Oct 2024

Our paper, titled "Optimizing Stroke Detection: An Analysis of Various Feature Selection Methods" has been published online (doi: 10.1145/3675094.3677602) at the UbiComp 2024 Conference, Australia.

MAY 2024

I am honored to serve as the Reviewer in peer-reviewed IEEE Pervasive Computing.

Mar 2024

I have started my Masters in Computer & Information Science at Fordham University, New York with GSAS Centennial Scholarship.

DEC 2023

I am officially graduated from North South University with a Bachelors in Computer Science & Engineering.

Jul 2023

I have started working as Research Assistant at Design Inclusion & Access Lab (DIAL). Working on the project - 'Feasibility of Alternative Credit Scoring for the Credit Invincibles of Bangladesh' funded by NSU-CTRG (CTRG-23-SEPS-02)

Interested in Security & Privacy in Multimodal AI and Zero-Shot VLM.

Blockchain, Security, Machine Learning95%

Python, PostGreSQL, SQL & MongoDB 90%

Power BI, Tableau & D3.js 80%

PySpark, Pandas & Seaborn 70%

A/B Testing, Hypothesis Testing 65%

Education

Fordham University, New York

2024 - Ongoing

M.S. in Computer & Information Science

➛ As a Full-time Graduate Student, 90% of my Tution Fee is funded by GSAS Centennial Scholarship.
➛ Developing expertise in areas including but not limited to Smart Contracts, Distributed Ledger systems, Trustworthy AI, Text Mining and Graph Mining. [Transcript]

North South University, Dhaka

2020 - 2023

B.Sc in Computer Science & Engineering

➛ Engaged in a comprehensive curriculum covering key areas such as Algorithms, Data Structures, Software Engineering, Theory of Computation and Machine Learning. [Transcript][Certificate]

Experience

Fordham University

2025 - Present

Research Assistant

➛ Working under Prof. Mohamed Rahouti on a 'Blockchain-Empowered Proof of Reputation (PoR)-Driven Federated Learning for Secure Medical Data Sharing' (Under Review, IEEE TCE).
➛ Developed 'A Merkle Tree and ZKP enhanced Secure Credit Scoring' (Under Review, IEEE TIFS).

Design Inclusion and Access Lab (DIAL)

2024 - 2025

Graduate Research Assistant

➛ Team Lead of Medical Imaging group - mentoring 5 members to ensure successful project execution under the supervision of Prof. Nova Ahmed.
➛ Worked on 2 projects - 'Attention and Residual Mechanism-based Deepfake Recognition' and ‘DFU_DIALNet: Reliable and Trustworthy Diabetic Foot Ulcer Detection’ projects. Find me

Recent Projects

VLM Jailbreaking

Survey on Adversarial Attacks on Vision-Language Models

Secured WBAN/IoMT System

Blockchain based FL with Proof of Reputation (PoR)

Trustworthy Keylogger detection

Ensemble and Feature Selections through Explainable AI

Hyperbolic CLIP for Cloud Perception

Open-Vocabulary Segmentation in Ground-Based Imagery

Attention & Residual based DeepFake

ARC-Net with XAI for Deepfake Image Detection

Ground based Cloud Segmentation

U-Net based FCNN for sharper Sky insights

Markle Tree based Credit Scoring

Trustworthy Zero-Knowledge Proof Enhanced Approach

Alveolar Bone Defects Segmentation

Unsupervised Domain Adaptation with 3D Data Labeling

Elderly People Activity Recognition

Multi-Head Temporal Attention based Bi-LSTM Approach

GradCam based Diabetic Foot Ulcer

Trustworthy proposed DFU_DIALNet to detect DFU

PCA & LDA based Stroke Detection

Linear Discriminant Analysis with XAI

Alternative Credit Scoring

Multi-Domain Validation of Bayesian Optimized Ensembles

Health Express BD

Emergency Ambulance, Medicine & Doctor.

Student Study Portal

Definition, Books, Homework, Task.

LinkedIn Job Analysis 2024

Uncover trends in top industries, skills in USA

Benchmark Datasets

1. Human Activity Recognition from Wearable Sensors

A comprehensive dataset of 72,000 readings of 6 persons, collected using a 3D accelerometer and gyroscope sensor from Rasperry PI 4 Device. We also proposed a mobile app to collect and tracking human activity.

Dataset Link: (Coming soon)

2. Diabetic Foot Ulcer Dataset

A specialized image dataset comprising 500 foot images (250 normal, 250 with ulcers) for the detection of Diabetic Foot Ulcers. This dataset was collected with approval from the North South University IRB/ERC (Application No. 2024/OR-NSU/IRB/1110).

Dataset Link: Click Here

3. DeepFake and Real Face Image Collection

A dataset of 500 facial images, including real Bangladeshi individuals of diverse genders and ages, collected with explicit written consent for deepfake detection research. Data collection was approved by North South University IRB/ERC (Application No. 2024/OR-NSU/IRB/1109).

Dataset Link: Click Here

4. Ground-Based Cloud Segmentation Dataset

A segmented dataset of 110 ground-based cloud images, meticulously annotated using Roboflow. This dataset was developed for training and evaluating U-Net based Fully Convolutional Neural Networks (F-CNN) for cloud segmentation tasks.

Dataset Link: (Coming soon)

Publications

M. I. Mahmud, M. S. Reza, M. O. A. Akash, F. Elias, and N. Ahmed. 2025. “DFU_DIALNet: Towards reliable and trustworthy diabetic foot ulcer detection with synergistic confluence of Grad-CAM and LIME,” PLoS ONE, vol. 20, no. 9, p. e0330669, USA. DOI: 10.1371/journal.pone.0330669..

M. I. Mahmud, M. S. Reza, and S. S. Khan. 2024. “Optimizing Stroke Detection: An Analysis of Different Feature Selection Approaches.” In Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp '24), Melbourne VIC, Australia, 142–146. https://doi.org/10.1145/3675094.3677602.

M. S. Reza, M. I. Mahmud, I. A. Abeer and N. Ahmed, "Linear Discriminant Analysis in Credit Scoring: A Transparent Hybrid Model Approach," 2024 27th International Conference on Computer and Information Technology (ICCIT), Cox's Bazar, Bangladesh, 2024, pp. 56-61. doi: 10.1109/ICCIT64611.2024.11022149.

M. I. Mahmud, M. S. Reza, and H. Akter, “Human Activity Recognition Using Multiple Learning & XAI Techniques with Wearable Sensor Data,” North South University, Dhaka, Bangladesh. 2023. https://repository.northsouth.edu/handle/123456789/1093

M. I. Mahmud, “Towards Trustworthy Keylogger detection: A Comprehensive Analysis of Ensemble Techniques and Feature Selections through Explainable AI,” arXiv.org, May 22, 2025. https://arxiv.org/abs/2505.16103

M. I. Mahmud, “ZeroML: A Next Generation AutoML Language,” arXiv.org, May 23, 2025. https://arxiv.org/abs/2505.18243

Under Review ⏳

J. Bieniek, M. I. Mahmud, M. Rahouti, A. Chehri, and G. Jeon, "ReMerkle: Proof of Reputation-driven Federated Learning with Compact Merkle Verification for Consumer-centric IoMT," IEEE TCE.
M. I. Mahmud, J. Bieniek, M. Rahouti, A. Chehri, and G. Jeon, "Trustworthy Consumer-Centric IoMT: Reputation-Driven Federated Learning for Secure Medical Data Sharing," IEEE Trans. on Consumer Electronics.
M. I. Mahmud, S. Patel, M. Rahouti, Kaiqi Xiong and A. Chehri, "Secure Credit Scoring: A Merkle Tree and Zero-Knowledge Proof-Enhanced Approach with Proactive Security Strategies in Consumer Applications," IEEE Transactions on Information Forensic & Security.
M. I. Mahmud, M. S. Reza, F. Elias, K. A. Ahmed, M. Ahammad, I. A. Abeer, and N. Ahmed, "Multi-Domain Validation of Bayesian Optimized Stacking Ensembles for Next-Generation Credit Risk Modeling with Granular Explainability and Robust Statistical Inference," SN Computer Science.
M. S. Reza, F. Elias, M. I. Mahmud, and N. Ahmed, "Attention and Residual Mechanism-based CNN Architecture (ARC-Net) with Enhanced Fairness Generalization for Deepfake Facial Image Detection," PLoS ONE.
M. I. Mahmud, M. S. Reza and I. T. Naheen, "Multi-Head Temporal Attention Enhanced Bi-LSTM for Human Activity Recognition: Introducing a Novel Benchmark Wearable Sensor Dataset," Knowledge-Based Systems.