Invited Speakers

Securing the Internet of Things in the Quantum Era: Threat Landscape, Timelines, and Transition Pathways

Abstract

As quantum computing advances toward practical reality, its profound impact on cybersecurity poses an urgent challenge for the Internet of Things (IoT) ecosystem. This talk examines the evolving threat landscape, highlighting how quantum-capable adversaries could undermine widely deployed cryptographic protocols central to IoT security. The presentation explores the realistic timelines for quantum threats to materialize, dispelling myths and providing evidence-based projections from both industry and academia. The session will outline essential transition pathways to post-quantum cryptography, emphasizing actionable strategies for IoT stakeholders, including device manufacturers, system integrators, and policymakers. Key considerations will include legacy device constraints, interoperability challenges, and the need for agile standards. Attendees will gain a roadmap for futureproofing their IoT deployments and understand the critical roles of research, standardization, and coordinated public-private efforts in ensuring the resilience of the connected world in a quantum-enabled future. The talk will also address the unique opportunities and challenges faced by emerging economies such as Bangladesh, where rapid IoT adoption is coupled with rising cybersecurity capacity and policy needs.

Biography

Dr. Fida Hasan is an entrepreneurial academic in Cyber Security, currently working at the University of New South Wales (UNSW), Australia. He is a Fellow of the Higher Education Academy (FHEA), UK, and a Senior Member of IEEE. Dr. Hasan is also a sought-after public speaker, known for delivering insightful and engaging talks on emerging cyber threats, post-quantum security, and digital transformation. As a speaker, he serves the broader mission of raising awareness, shaping policy discourse, and empowering organizations to navigate the evolving cybersecurity landscape. He holds a Ph.D. in Computer Science from the Queensland University of Technology (QUT) and has previously held research and leadership positions at institutions including QUT, RMIT University, and the University of the Sunshine Coast. He leads on the prominent SOCRATES project, which focuses on quantum threats in the Australian context. His research interests span cybersecurity, artificial intelligence, quantum computing, blockchain, and smart transportation systems. He has contributed to several government- and industry-funded initiatives, including projects supported by the Cyber Security Cooperative Research Centre, Department of Transport and Main Road, and the Australian Department of Education, Skills and Employment.

Blockchain Beyond Cryptocurrencies: Possibilities and Challenges

Abstract

Blockchain is often synonymous with cryptocurrencies, yet its potential extends far beyond digital finance. At its core, blockchain offers a distributed, tamper-resistant, and transparent infrastructure that can transform how organizations, governments, and individuals exchange and verify information. This talk explores blockchain as a trust-enabling technology with applications in diverse domains, including healthcare, supply chains, digital identity, and data sharing. I will discuss how blockchain's unique features—immutability, decentralisation, and programmable smart contracts—can address long-standing challenges of trust, accountability, and efficiency. At the same time, I will critically examine the technical, social, and regulatory hurdles that hinder large-scale adoption, including scalability, interoperability, privacy, and governance. Drawing on recent research and real-world case studies, I will highlight both the opportunities and limitations of blockchain in creating secure, sustainable, and inclusive digital ecosystems. By moving the conversation beyond cryptocurrencies, this talk aims to provide researchers, practitioners, and policymakers with a nuanced understanding of blockchain's transformative potential while encouraging thoughtful engagement with the challenges that must be overcome.

Biography

Dr. Rahma Mukta is an Assistant Professor in the Department of Computer Science and Engineering at Chittagong University of Engineering and Technology (CUET), and a Postdoctoral Research Fellow at UNSW Sydney, Australia. She received her PhD in Computer Science from UNSW. Her research interests span distributed systems, process automation, data privacy and security, blockchain architectures, and decentralised identity management. She has published extensively in leading international conferences and journals, receiving multiple best paper awards and recognition for her contributions to trustworthy computing and privacy-preserving technologies. She is an active member of the IEEE and the ACM, and regularly serves as a reviewer and technical committee member for top-tier conferences in computing and security (examples include PerCom, ICBC, TiFS).

Bridging Generative AI and Computer Vision: Models, Applications, and Future Directions

Abstract

Generative AI has emerged as one of the most transformative areas in artificial intelligence, redefining how we synthesize, enhance, and interpret visual data. In this talk, I will discuss my research on developing and applying generative models for computer vision tasks. A key focus will be the use of synthetic data generation for defect inspection in semiconductor manufacturing, where traditional datasets are limited and costly to collect. I will present framework for creating realistic defect images with generative models to improve diversity, controllability, and downstream detection accuracy. Beyond defect synthesis, I will highlight broader applications of generative AI in quality inspection and image enhancement. The talk will conclude with perspectives on future opportunities and challenges at the intersection of generative AI and real-world computer vision applications.

Biography

Dr. Lamia Alam is a computer vision and machine learning researcher with expertise in generative AI, image processing, and deep learning model development. She earned her Ph.D. in Computer Engineering from the University of Texas at Dallas in May 2025, where her research focused on synthetic defect generation using advanced generative models. During her Ph.D., she was recognized with multiple competitive fellowships, including the iREDEFINE Fellowship (2025), the ECE Last Mile Fellowship (2025), and the Louis Beecherl, Jr. Graduate Fellowship (2023–2025). She has her bachelor's and master's degrees in computer science and engineering (CSE) from Chittagong University of Engineering and Technology (CUET), Bangladesh, where she also served as a faculty member before moving to the United States in 2021 to pursue her Ph.D. Lamia also gained industry experience through her internship at Texas Instruments, where she developed hybrid deep learning models for semiconductor top package defect detection. Her research interests center on Generative AI, including generative adversarial networks (GANs), variational autoencoders (VAEs), and diffusion models, with applications in computer vision, quality inspection, and image enhancement. She has hands-on expertise with TensorFlow, PyTorch, and classical image processing methods, and has published and presented her work in leading journals and conferences. She is also passionate about STEM outreach and has actively contributed to initiatives promoting diversity in engineering