EXTERNAL PROFILES
Assistant Professor
Md Iftekharul Alam Efat
I particularly enjoy collaborating with Software Systems with Artificial Intelligence and solve new challenges. Currently, doing research on "Precision Agriculture and Digital Twin Technologies", using machine learning approaches to enhance production of Agriculture with smart way.
Institute of Information Technology (IIT)
BIOGRAPHY
I am Md. Iftekharul Alam Efat, an Assistant Professor at the Institute of Information Technology (IIT), Noakhali Science and Technology University (NSTU). I hold both a BSc and an MSc in Software Engineering from the Institute of Information Technology (IIT), University of Dhaka (DU).I am an enthusiastic, adaptive, and fast learner with a strong passion for Secure Software Design & Architecture. I enjoy collaborating on software systems that integrate Artificial Intelligence and thrive on solving complex, real-world challenges. Recently, I’ve conducted research on IoT-Based Health Status Monitoring Technology, where I used neural networks to build a system capable of continuously monitoring the health conditions of diabetic patients. Currently, doing research on "Automated Bug Triaging and Classification using Machine Learning Techniques", applying state-of-the-art ML techniques on software repositories. My aim is to contribute to the development of intelligent and secure healthcare solutions through cutting-edge research and innovation.
RESEARCH INTERESTS
2013 - 2014
M.Sc. in Software Engineering
Institute of Information Technology (IIT)
University of Dhaka (DU), Bangladesh
Thesis: Thesis: Reusability Measurement for Software Components CGPA – 3.79 (in the scale of 4.00)
2009 - 2012
Bachelor of Information Technology
Major in Software Engineering
Institute of Information Technology (IIT), University of Dhaka (DU), Bangladesh
Thesis: Thesis: Face Recognition with Vibrant Local Ternary Pattern (VLTP) CGPA – 3.84 (in the scale of 4.00)
2006 - 2008
Higher Secondary Certificate
Science
Notre Dame College, Dhaka, Bangladesh
1996 - 2006
Secondary School Certificate
Science
St. Gregory’s High School, Dhaka, Bangladesh
Last updated on 2026-01-13 08:24:28
2019-02-12
2017-10-15
2017-04-30
Last Updated: 2025-10-07 13:29:45
Last Updated: 2025-10-07 13:48:48
AWARDS AND ACHIEVEMENTS
1
Best Presenter Award
ICIEV 2014
Description: 3rd International Conference on Informatics, Electronics & Vision (ICIEV '14) for paper: "Face Verification with Fully Dynamic Size Blocks based on Landmark Detection".2
University Undergraduate Scholarship of Excellence
University of Dhaka, Dhaka, Bangladesh
Description: Achieved scholarship for excellent result and other co-curricular activities throughout graduation period. Awarded by, University of Dhaka, Bangladesh3
2nd Runners-up
Banglalink Grandmaster Idea Contest
Description: Business plan and implementation of a VAS (Value Added Service) for Banglalink Idea: SMS based bus ticketing named EASY PASSANGER for inter-city & intra-city bus services in Bangladesh4
1st Runners-up on Project Showcasing
Islamic University of Technology (IUT), Gazipur, Bangladesh
Description: 3rd National ICT FEST 2011, Islamic University of Technology (IUT), Gazipur, Bangladesh Project: mobile based loan & payment, providing three features including account checking, mobile balance recharge, loan & payment using the Credit Rating idea.5
2nd Runners-up on Software Project Fair
East West University (EWU), Dhaka, Bangladesh
Description: EWU IT Festival 2011, East West University (EWU), Dhaka, Bangladesh Project: m-Tourism: A Mobile based Tourism System of seeking and booking6
Champion on BCSIR Science Fair
Bangladesh Council of Scientific and Industrial Research (BCSIR), Dhaka, Bangladesh
Description: Project: E-Voting: A Pathway to Free, Fair & Transparent Election7
Runners-up on 4th Divisional (Dhaka) Mathematics Olympiad
Bangladesh Mathematical Olympiad (BdMO)
Lightweight temporal violence detection using YOLOv7-Tiny and Bi-GRU for resource-constrained environments
Blockchain Aided Smart Consensus Model for IoMT Architecture
A Systematic Review of Blockchain Applications
Identifying Optimised Speaker Identification Model using Hybrid GRU-CNN Feature Extraction Technique
Deep-learning Model using Hybrid Adaptive Trend Estimated Series for Modelling and Forecasting Sales
Paperless Vehicle Certification (PVC) Framework for Transport Stakeholders
Dynamic Blocks for Face Verification
Vision Inspired Local Ternary Pattern (VLTP) for Face Recognition & Verification
Book Name: Lecture Notes in Networks and Systems (LNNS)
Chapter Title: Optimized Energy Consumption in Healthcare WSNs Using Enhanced LEACH Protocol with K-Means
Book Name: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (LNICST)
Chapter Title: Deep Convolutional Comparison Architecture for Breast Cancer Binary Classification
Book Name: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (LNICST)
Chapter Title: Block-chain aided Cluster based Logistic Network for Food Supply Chain
Book Name: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (LNICST)
Chapter Title: IoT based Smart Health Monitoring System for Diabetes Patients using Neural Network
A Hybrid GRU-CNN Feature Extraction Technique for Speaker Identification
Blockchain aided Vehicle Certification (BVC): A Secured E-Governance Framework for Transport Stakeholders
Trend Estimation of Stock Market: An Intelligent Decision System
Dynamic Local Ternary Pattern for Face Recognition and Verification
Face Verification with Fully Dynamic Size Blocks based on Landmark Detection
Feature Prioritization for Analyzing and Enhancing Software Reusability
Automated Bangla Text Summarization by Sentence Scoring and Ranking
Agri
Abstract: pricision agriculture
Last Updated: 2026-07-15 19:51:29
No Project Found
Last Updated: 2026-07-15 19:51:29
No Course Materials Found....
Rahat Uddin Azad
MSc. Student, IIT, NSTU
Thesis Title: A Dual Encoder Fusion Model for Semantic-Aware Bangla Paraphrase Generation Using Bangla-T5 and Gemini Embedding
Overview: The primary objective of this research is to build and validate a paraphrase generation system for Bangla that maximizes semantic fidelity while producing meaningful, non-trivial re- expressions of the input sentences. A core challenge in achieving this goal is mitigating semantic drift, which can occur under conditions of limited and heterogeneous supervision. To address this issue, the methodology incorporates a stable, frozen semantic signal from Gemini Embeddings, which is integrated into both the representation and the objective functions of the model. This strategy is intended to ensure that the generated paraphrases retain semantic accuracy despite the inherent variability in the input data.
Imtiaz Chowdhury
Software Engineer
Thesis Title: A Framework for Maximizing Assertion Accuracy in LLMs Generated Test Code
Overview: Well designed and cost-effective unit tests are crucial to developing and maintaining quality software. Recently, Large Language Models have dramatically improved automated test generation; however, the precision of assertions in such tests is still an important issue to address. A novel framework is presented that uses a step-by-step approach to improve assertion reliability in LLM-generated test code by performing assertion quality classification, mutation-guided evaluation, and a targeted strategy for model fine-tuning. The framework was applied to a dataset of 1,328 test cases and shows substantial improvements in the accuracy of assertions. Empirical findings attest to the framework’s ability to enhance assertion power by at least double, while raising mutation scores by up to 93.57\%. The proposed framework addresses unique issues related to assertion generation and offers a highly effective approach to improving the dependability and efficiency of LLM-generated tests in actual software development scenarios.
Shoriful Habib
Software Engineer
Thesis Title: AI Driven Dynamic Multi Period Vehicle Routing
Overview: This thesis addresses the Dynamic Multi-Period Vehicle Routing Problem (DMPVRP) in order delivery logistics, focusing on efficient route planning for multiple vehicles under dynamic customer demands and operational constraints. A novel Graph Neural Network (GNN)-based framework is proposed to learn routing policies from heuristic-generated data and adaptively optimize delivery routes over multiple days. The GNN approach is evaluated against a classical Nearest Neighbor heuristic, demonstrating promising adaptability despite initial lower route efficiency. Experimental results show the heuristic achieves shorter total distance and lower fuel cost, while the GNN model offers scalability and potential for improvement through advanced training. This research bridges traditional optimization and modern AI, providing a foundation for scalable, robust dynamic routing solutions in real-world logistics.ew
Shuvra Aditya
MSc. Student, IIT, NSTU
Thesis Title: Explainable Artificial Intelligence (XAI) Enabled Machine Learning-based Intrusion Detection System to Enhance Interpretability and Trustworthiness
Overview: Despite the increasing popularity of machine learning models in cyber-security applications such as intrusion detection systems (IDS), most of these models are often perceived as black-box solutions. The significance of eXplainable Artificial Intelligence (XAI) has grown as it allows for the interpretation of machine learning models, thereby enhancing trust management. XAI enables human experts to comprehend the underlying data evidence and causal reasoning, leading to improved trust in the system. While previous studies have primarily focused on the accuracy of various classification algorithms for trust in IDS, they often lack insights into the behavior and reasoning of these complex algorithms. In this paper, we address the concept of XAI to enhance trust management in IDS by examining the decision tree model. By utilizing simple decision tree algorithms that are easily interpretable and resemble human decision-making processes, we split choices into smaller subchoices for IDS. We conducted experiments using a widely used KDD benchmark dataset and extracted rules to assess the effectiveness of this approach. Additionally, we compared the accuracy of the decision tree approach with other state-of-the-art algorithms.
- Institutional Email: iftekhar.iit@nstu.edu.bd
- Personal Email: iftekhar.efat@gmail.com
- Mobile number: 01727208714
- Emergency Contact: 01842208714
- PABX:1202
- Website:https://iftekhar.sererl.com/
Institute
Institute of Information Technology (IIT)
Noakhali Science and Technology University