ECCT 2026 - International Conference on Electrical, Computer and Communication Technologies (ECCT 2026)

Keynote Talk

Al And Advances in The Medical Sector (An Incomplete Tale)

by Dr. M. Sohel Rahman

Speaker

Dr. M. Sohel Rahman

Professor

Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology, Bangladesh

ABSTRACT

Artificial Intelligence (Al) promises to revolutionize the medical sector. With tremendous advances in machine learning and deep learning algorithms, we now have the ability to make more decisions based on data leveraging its capability to analyze vast amounts of data quickly and accurately. It is not possible to cover the advancement of Al in the medical field in just one talk. Therefore, in this talk we will focus on some unique and state of the art technologies like CRISPR/Cas9 and present some recent research progresses thereon. The overarching goal of this talk would be to discuss the enormous prospect of Al, particularly that of ML and DL techniques and how these can shape the future of the medical sector.

BIOGRAPHY

Dr. M. Sohel Rahman is a Professor of the CSE department of BUET. He had worked as a Visiting Research Fellow of King's College London, UK during 2008-2011 and again as a Visiting Senior Research Fellow there during 2014-15. He is a Senior Member of IEEE; member of American Mathematical Society (AMS) and London Mathematical Society (LMS). He is also a Peer-review College Member of EPSRC, UK. He has been honoured as a Distinguished Member of the ACM for "Trailblazing Achievements across Computing Field". He has also been recognized as Distinguished Contributor of IEEE Computer Society for his technical contributions to the profession and the society. He is a Fellow of Bangladesh Academy of Sciences and Bangladesh Computer Society. He received different scholarships and fellowships including Commonwealth Scholarship, Commonwealth Fellowship, ACU Titular Fellowship, University College London-Big Data Institute visiting grant, London Mathematical Society Visiting Grant etc. He is also a recipient of the Bangladesh Academy of Sciences Gold Medal and UGC Award. He has led research and development projects funded by British Council, UGC- World Bank, ICT Division, Government of Bangladesh and BUET. He has so far published 156 peer-reviewed international journal papers. Among his notable results are the work on MultiResUNet (an improvement over the U-Net, which is the de-facto architecture for medical imaging segmentation tasks), high dimensional Knapscak problems, sequence alignment problems, data structures and string combinatorics, sufficient conditions for Hamiltoninicity, Machine Learning based predictors in Bioinformatics, and metaheuristics solutions for hard problems. Dr. Rahman is an Editor of Neural Networks journal, Academic Editor of PLOS One, Associate Editor of BMC Bioinformatics and BMC Research Notes and had edited special issues as guest editors in Theoretical Computer Science, Journal of Graph Algorithms and Applications, Journal of Discrete Algorithms, Fundamenta Informaticae etc. He has also served as Program Committee members in a number of conference series' of international repute. Dr. Rahman regularly writes reviews at Mathematical Review and ACM Computing Review. He is a Distinguished Speaker of ACM; he was also the Distinguished Lecturer of IEEE Computer Society. He has been included in the Stanford/Elsevier list, highlighting the top 2% of the most cited scientists across the globe. Since November 2024, Dr. Sohel Rahman has been serving in a constitutional post as a member of the Bangladesh Public Service Commission, playing a key role in ensuring a merit-based civil service for the republic.

Keynote Talk

Generative Al and Large Language Models (LLMs) for Cyber-Security and Political Sciences Transportation Security and Resiliency

by Professor Latifur Khan

Speaker

Professor Latifur Khan

Fellow of IEEE, AAAS, IET, BCS

Department of Computer Science, University of Texas at Dallas (UT Dallas), USA

ABSTRACT

This presentation explores the transformative potential of generative artificial intelligence-particularly large language models (LLMs)-in addressing critical challenges in domains such as cybersecurity, intelligent transportation systems (ITS) and political sciences. Generative Al-Enhanced Threat Modeling in ITS: We develop an LLM-based framework to automate threat modeling for complex intelligent transportation systems by mapping information flows to MITRE ATT&CK techniques and NIST Cybersecurity Framework controls. The approach evaluates multiple Al methods, including zero-shot learning, RAG, multimodal reasoning, in-context learning, and fine-tuning. Policy Analysis for Secure Transportation Systems: This project enhances transportation cybersecurity policy using Al-driven legal analysis and stakeholder engagement. Building on the TraCR Al system, it integrates U.S. and international regulations and uses agentic Al and graph-based retrieval to identify policy gaps and propose improvements for data security and privacy in autonomous transportation. Conflict and Political Violence Monitoring: We developed ConfliBERT, a domain-specific pretrained language model for analyzing conflict and political violence data, which outperforms general-purpose LLMs in classification and question-answering tasks and has over 14,000 downloads on GitHub and Hugging Face. We also proposed ensemble-based active learning methods-Ensemble Union and Ensemble Intersection-that combine multiple heuristics to improve sample selection. Experiments on the United Nations Parallel Corpus show these approaches achieve performance comparable to full- dataset training while requiring far fewer labeled examples. Cybersecurity Intelligence Extraction: In partnership with researchers at NIST, we automated the extraction of cyber-attack techniques from Common Vulnerabilities and Exposures (CVE) and Cyber Threat Intelligence (CTI) reports. These extracted techniques are mapped to the MITRE ATT&CK framework using a combination of LLMs and active learning strategies. We have shown how this structured, machine- assisted analysis enhances the ability of security analysts to respond to emerging threats more effectively.

BIOGRAPHY

Dr. Latifur Khan is a (tenured) full Professor in the Computer Science department at the University of Texas at Dallas, USA where he has been teaching and conducting research since September 2000 and is the Director of the Artificial Intelligence and Cyber Security Center. He received his Ph.D. degree in Computer Science from the University of Southern California (USC) in August of 2000. Dr. Khan is a fellow of IEEE, AAAS, and the British-based IET and BCS, and an ACM Distinguished Scientist. He has received prestigious awards including the IEEE ITSS Intelligence and Security Informatics 2012 Technical Achievement Award, IEEE Big Data Security 2019 Senior Research Award, and 2016 IBM Faculty Award for research. Dr. Khan has published over 300 papers in premier journals and prestigious conferences. His research focuses on artificial intelligence and data science and their applications in cyber security and transportation systems, as well as in complex data management including geospatial and multimedia data. His research has been supported by grants including from NSF, USDOT, AFOSR, ARL, ARO, NIH, DOE, NSA, IBM, Raytheon, Nokia, and HPE. More details can be found at www.utdallas.edu/~lkhan

Keynote Talk

Cultivating Global Talent: Mentorship and Research Pipelines from Bangladesh

by Dr. Chanchal Roy

Speaker

Dr. Chanchal Roy

Professor

Department of Computer Science and Engineering, University of Saskatchewan, Canada

ABSTRACT

Bangladesh has emerged as a strong and reliable source of high-caliber software engineering graduates. This talk focuses on the University of Saskatchewan's experience recruiting and mentoring students from institutions such as Khulna University, BRAC University, KUET, IUT, EWU, and CUET. It highlights effective mentorship practices, student growth, and how these graduates transition into successful research careers in North America. Emphasis is placed on building supportive supervision structures, identifying promising applicants, and sustaining long-term academic pipelines. Students have contributed to a range of software engineering research areas, including empirical studies, clone detection, and data-driven development, with growing use of LLM-based techniques. The talk briefly touches on these research directions while focusing primarily on lessons learned in mentorship and international collaboration. It concludes with practical guidance on fostering cross-border partnerships and expanding recruitment to strengthen diversity and global engagement in software engineering.

BIOGRAPHY

Chanchal K. Roy is Director of the industry-stream, multi-University NSERC CREATE graduate program on Software Analytics Research (SOAR) and Software Research Lab (SRLab), and Professor of Software Engineering/Computer Science at the University of Saskatchewan (USask), Canada. Dr. Roy works in the broad area of software engineering, with particular emphasis on software clone detection and management, software evolution and maintenance, recommender systems in software engineering, automated software debugging, and big data analytics in software engineering. His contributions to the software maintenance community, and particularly to the software clones community have been highly influential, winning four 10-year Most Influential Paper awards at international conferences (ICPC 2018, SANER 2018, SANER 2021 and SCAM 2025). Recently, he was awarded with the Clones Lifetime Achievement Award, and became only the second person to receive this award. He has been recognized with the New Scientist Research Award of the College of Arts and Science at USask, the University wide New Researcher Award, GSA Advising Excellence Award and an Outstanding Young Computer Science Researcher Award by Canada's computing research community, CS-Can/Info-Can. He has attracted over $6M in external funding since joining the USask, gave invited/keynote talks at numerous conferences, extensively served as organizing chairs and in program committees of international conferences and guest editors for journals. As the lead author of the widely used NiCad code clone detection system, he has published more than 250 refereed publications, with many of them in premier software engineering conferences and journals that have been cited more than 15,000 times with an h-index of 58 (Google Scholar). Dr. Roy has been (co-)supervising or has (co-)supervised over 114 highly qualified personnel including 24 PhD, 37 MSc and 7 postdocs

Keynote Talk

Long duration energy storage with advanced materials: Role of Al in optimization of synthesis and storage

by Dr. Saidur Rahman

Speaker

Dr. Saidur Rahman

Professor & Head

Research Centre for Nano-Materials and Energy Technology (RCNMET) Sunway University, Malaysia

ABSTRACT

Long-Duration Energy Storage (LDES) is critical for grid stability, bridging the gap between intermittent renewable generation and continuous demand. Advanced materials (i.e. MXene, graphene, CNTs) are at the forefront of this shift, enhancing efficiency, cycle life, and cost-effectiveness far beyond the capabilities of traditional lithium-ion batteries. In this speech, advanced materials that has shown outstanding energy storage behaviour will be explored and cost reduction to the development of these materials will be highlighted. Al in optimization of synthesis parameters, storage behaviour will also be explored.

BIOGRAPHY

Professor Saidur Rahman is currently working as a Distinguished Research Professor and Head of the Research Centre for Nano-Materials and Energy Technology (RCNMET) at Sunway University. He is also working with Lancaster University as a full Professor. Previously, he worked as a Chair Professor at the Center of Research Excellence in Renewable Energy at King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia. Prior to joining KFUPM, Prof. Saidur worked 18 years in University of Malaya, a premier University in Malaysia. He is ranked 1 in Malaysia according to top 2% Scientist by Stanford/Elsevier Analysis. He is also number 1 Scientist in Malaysia according to AD scientific, research.com and GPS scholar. Clarivate Analytics/Thomson Reuters awarded him highly cited researcher for being among the top 1% researchers for most cited documents in his research field for the eight consecutive years (2014-2021). In 2019 and 2024, Prof. Saidur won Vice Chancellor's award for achievement in Research, Sunway University. Prof. Saidur published more than 900 journal and conference papers. Majority of them are in top ranking high impact journals. His publications are cited more than 88,000 times with an h-index of 148 according to Google Scholar citation. He has supervised more than 80 postgraduate students so far and has secured and managed more than 25 million ringgit research grants as a Pl and member. Prof. Saidur is working in the area of emerging nano-materials and their applications in energy storage, heat transfer, solar energy harvesting and environmental remediation.

Keynote Talk

Digital Deception: Fake Vs. Real

by Prof. Tariq R. Soomro, PhD

Speaker

Prof. Tariq R. Soomro, PhD

Rector, Institute of Business Management (IoBM), Karachi, Pakistan

IEEE CS R10 Regional Coordinator | Senior Member IEEE, CS, & EdSoc | Distinguished Contributor (2021) & Visitor (2021-23) | Former Chair IEEE Karachi (2024-25)

ABSTRACT

To be added.

BIOGRAPHY

To be added.

Keynote Talk

The Art of Sparsity for Higher Order Tensors

by Dr. K. M. Azharul Hasan

Speaker

Dr. K. M. Azharul Hasan

Professor

Department of Computer Science and Engineering, Khulna University of Engineering & Technology, Bangladesh

ABSTRACT

Higher-order tensors have emerged as a powerful and expressive framework for modeling multi-dimensional and multi-modal data across domains such as Machine learning, recommender systems, natural language processing, and computer vision. Despite their representational richness, their practical adoption is often limited by the exponential growth in storage and computational requirements-commonly known as the curse of dimensionality. This talk explores the art of sparsity as a principled and transformative approach to overcoming these challenges. By leveraging the inherent structure, redundancy, and low-dimensional patterns within real-world data, sparsity enables efficient representation and scalable learning in higher-order tensor models. Sparsity-driven techniques can be seamlessly integrated into modern machine learning frameworks, particularly in applications such as recommender systems and information filtering. Empirical evidence demonstrates that sparsity-aware tensor models not only reduce computational complexity but also achieve competitive, and often superior, performance compared to dense approaches. Beyond efficiency, this talk argues that sparsity should be viewed not merely as a constraint, but as a fundamental design paradigm-one that balances expressiveness, interpretability, and scalability in high-dimensional learning.

BIOGRAPHY

Dr. K. M. Azharul Hasan is a Professor in the Department of Computer Science and Engineering at Khulna University of Engineering & Technology (KUET), Bangladesh. With extensive academic and administrative experience, he previously served as the Head of the Department and Dean of the Faculty. He also served as the director of the Institute of Information and Communication Technology and Institutional Quality Assurance Cell. Dr. Hasan's research interests span machine learning, data analytics, natural language processing, and high-dimensional data modeling, with a particular focus on tensor-based methods and scalable learning techniques. His work explores innovative approaches to handling complex, multi-modal data, including sparsity-aware models and efficient representations for large-scale systems. He has contributed to numerous research publications in reputable journals and conferences and has been actively involved in supervising undergraduate and postgraduate research. He is deeply engaged in academic leadership, curriculum development, and fostering collaborative research environments.

Keynote Talk

Enhancing Online Learning Through Al-Based Student Engagement Detection

by Dr. Ali Dewan

Speaker

Dr. Ali Dewan

Associate Professor

School of Computing and Information Systems, Faculty of Science and Technology, Athabasca University, Canada.

ABSTRACT

In this presentation, I will discuss some Al-driven solutions that aim to improve student engagement in online learning. Student engagement detection systems identify the type and level of engagement using various modalities. I will discuss several ways in which Al and machine learning techniques are being applied in these systems to support online learners, along with the associated challenges and future research opportunities. The role of explainable Al and the impact of bias in training data used for machine learning techniques will also be examined in the context of these applications in online education.

BIOGRAPHY

Dr. Ali Dewan is an Associate Professor in the School of Computing and Information Systems, Faculty of Science and Technology, Athabasca University, Canada. He served as Chair of the School of Computing and Information Systems from 2019 to 2022. Before joining the University, he was a postdoctoral researcher at École de Technologie Supérieure (Montreal, Canada) from 2012 to 2014 and at Concordia University (Montreal, Canada) from 2009 to 2012. He also served as a Lecturer (2003-2005) and later as an Assistant Professor (2009) at Chittagong University of Engineering and Technology, Bangladesh. He received his PhD degree in Computer Engineering from Kyung Hee University, South Korea, in 2009, and his BSc degree in Computer Science and Engineering from Khulna University, Bangladesh, in 2003. His research interests include artificial intelligence in education, educational data mining, machine learning, affective computing, computer vision, information visualization and medical image analysis. He received the Dean's Award and the Excellent Research Achievement Award for his academic performance and research achievements during his PhD studies in South Korea. He served as chair/co-chair, program committee member, and reviewer for many prestigious conferences and journals. He is an Associate Editor of Circuit Systems and Signal Processing and Computers Journals. He is a member of IEEE. He is a recipient of the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant for the period 2020-2026. In this research project, he is investigating student engagement detection and designing pedagogical intervention to support online learners.

Invited Talk

Augmented and Virtual Reality in Education: From Research Insights to Real-World Impact and Future Directions

by Md. Sabir Hossain

Speaker

Md. Sabir Hossain

Assistant Professor

Department of Computer Science and Engineering Chittagong University of Engineering and Technology, Bangladesh

ABSTRACT

Augmented Reality (AR) and Virtual Reality (VR) are transforming education by enabling immersive, interactive, and learner-centered experiences. This invited talk presents a comprehensive overview of AR/VR in education, focusing on bridging the gap between research innovations and real-world deployment. The talk highlights empirical insights from AR-based educational applications developed for early learning, where controlled studies demonstrate significant improvements in learning outcomes, achieving approximately 30-33% performance gains alongside enhanced student engagement and motivation. It further introduces the integration of AR with machine learning through systems such as Learn2Write, which enables real-time handwriting evaluation using deep learning and marker-less AR, illustrating the potential of intelligent and adaptive learning systems. From a technical perspective, the session discusses system architectures, design principles, and implementation strategies for developing scalable AR/VR-based educational environments. Key challenges-including scalability, device constraints, usability, and adoption barriers are critically examined, particularly in the context of developing regions. Finally, the talk outlines future research directions, emphasizing the convergence of AR/VR with artificial intelligence, multimodal learning, and explainable Al (XAI). It also highlights the importance of collaborative platforms and ecosystem-driven deployment models to translate research into scalable, real-world educational impact, fostering the next generation of intelligent and immersive learning systems.

BIOGRAPHY

Md. Sabir Hossain is a PhD researcher in Information and Computer Science at King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia, and an Assistant Professor (on higher study leave) in the Department of Computer Science and Engineering at Chittagong University of Engineering and Technology (CUET), Bangladesh. His research focuses on multimodal Al systems, explainable artificial intelligence (XAI), privacy-preserving machine learning, federated learning, and AR/VR-driven educational technologies. He has authored 40+ research publications in international journals, conferences, and book chapters. He serves as an Editor (Regional) of the Sigma Journal of Engineering and Natural Sciences (SCOPUS & WoS indexed), Turkey, and an Editorial Board Member of the Babylonian Journal of Artificial Intelligence (SCOPUS indexed), Iraq, and regularly reviews for leading publishers including Elsevier, Wiley, and IEEE. He is also a member of the Interdisciplinary Research Center for Intelligent Secure Systems (IRC-ISS) at KFUPM. Beyond research, he is the founder of Be Researcher World Forum (BRWF) and Be Researcher BD (BRBD), initiatives that have guided thousands of students toward research and international publications. His work bridges research innovation and real- world impact, particularly in intelligent and immersive learning systems.

Invited Talk

LLM Applications in Software Engineering and Greening Them for a Sustainable Future

by Dr. Banani Roy

Speaker

Dr. Banani Roy

Associate Professor

Department of Computer Science and Engineering University of Saskatchewan, Canada

ABSTRACT

Large Language Models (LLMs) are transforming software engineering by supporting program comprehension, code summarization, and knowledge transfer across developers and systems. However, their high computational cost raises concerns about scalability and environmental sustainability. We advocate a green LLM pipeline that compresses large models into efficient student models while preserving their core capabilities. The pipeline integrates knowledge distillation, structured pruning, and low-bit quantization to reduce model size, energy consumption, and deployment overhead. This approach demonstrates that LLMs can remain effective for software engineering tasks while significantly lowering their environmental footprint, making sustainable Al a practical goal rather than a trade-off.

BIOGRAPHY

Dr. Banani Roy is an Associate Professor in Computer Science at the University of Saskatchewan, Co-Director of the NSERC CREATE SOAR program, and Director of the Interactive Software Engineering and Analytics Lab. She received her Ph.D. from Queen's University. Her research focuses on human-centric software engineering, software analytics, and sustainable, scalable tools for program comprehension and scientific workflows. She collaborates widely with academia and industry and publishes in top venues such as ICSE, ASE, and FSE. She is an award-winning mentor dedicated to advancing inclusive and impactful research.

International Conference on Electrical, Computer and Communication Technologies (ECCT 2026)

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About The Conference

Theme: Technology for a Transformative Future

Networking Opportunities

Knowledge Exchange

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Call For Papers

Topics of Interest

Track 1: Smart Electrical and Power Systems

Track 2: Advanced Computing and Software Technologies

Track 3: Communication Systems and Networking

Track 4: Signal Processing, Embedded Systems and VLSI Design

Track 5: Cybersecurity, Data Analytics, and Emerging Applications

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Keynote and Invited Talks

Keynote Speakers

Al And Advances in The Medical Sector (An Incomplete Tale)

Generative Al and Large Language Models (LLMs) for Cyber-Security and Political Sciences Transportation Security and Resiliency

Cultivating Global Talent: Mentorship and Research Pipelines from Bangladesh

Long duration energy storage with advanced materials: Role of Al in optimization of synthesis and storage

Digital Deception: Fake Vs. Real

The Art of Sparsity for Higher Order Tensors

Enhancing Online Learning Through Al-Based Student Engagement Detection

Invited Talks

Augmented and Virtual Reality in Education: From Research Insights to Real-World Impact and Future Directions

LLM Applications in Software Engineering and Greening Them for a Sustainable Future

Al And Advances in The Medical Sector (An Incomplete Tale)

Dr. M. Sohel Rahman

ABSTRACT

BIOGRAPHY

Generative Al and Large Language Models (LLMs) for Cyber-Security and Political Sciences Transportation Security and Resiliency

Professor Latifur Khan

ABSTRACT

BIOGRAPHY

Cultivating Global Talent: Mentorship and Research Pipelines from Bangladesh

Dr. Chanchal Roy

ABSTRACT

BIOGRAPHY

Long duration energy storage with advanced materials: Role of Al in optimization of synthesis and storage

Dr. Saidur Rahman

ABSTRACT

BIOGRAPHY

Digital Deception: Fake Vs. Real

Prof. Tariq R. Soomro, PhD

ABSTRACT

BIOGRAPHY

The Art of Sparsity for Higher Order Tensors

Dr. K. M. Azharul Hasan

ABSTRACT

BIOGRAPHY

Enhancing Online Learning Through Al-Based Student Engagement Detection

Dr. Ali Dewan

ABSTRACT

BIOGRAPHY

Augmented and Virtual Reality in Education: From Research Insights to Real-World Impact and Future Directions

Md. Sabir Hossain

ABSTRACT

BIOGRAPHY

LLM Applications in Software Engineering and Greening Them for a Sustainable Future

Dr. Banani Roy

ABSTRACT

BIOGRAPHY

Important Dates

Paper Submission Deadline

Paper Submission Deadline

Notification of Acceptance

Camera-Ready Submission

Camera-Ready Submission

Registration Deadline

Conference Dates