Abstract of Talk:

Cybersickness, or sickness caused by virtual reality (VR), represents a significant threat to the usability of VR applications. Repeated exposure to the same VR stimulus causes a reduction in cybersickness, referred to as Cybersickness Abatement from Repeated Exposure (CARE). This talk presents recent results from efforts to inoculate VR users against cybersickness using specific CARE regimens. This work funded by the US. National Science Foundation and co-led by Jonathan Kelly and Michael Dorneich. 

Brief Profile:

Professor Stephen B. Gilbert is Faculty Director for Undergraduate Research and Creative Activities at Iowa State University as well as for its Honors program. He is also a professor in the Industrial and Manufacturing Systems Engineering department. Previously he led ISU's program in Human Computer Interaction. His research focuses on human-AI teaming and virtual reality cybersickness. He works closely with industry, NSF, and DoD and has also worked in commercial software development and started a company. He earned a BSE in civil engineering and operations research from Princeton and a PhD from MIT in brain and cognitive sciences.

Abstract of Talk:

Metaverse term has different aspects and concepts for the readers. The easy understanding of a reader’s metaverse is a new way of hue cyberspace. Metaverse does not refer to any specific technology but several cutting-edge technologies and how those will be used under specific conditions. Mainly it focuses on social networks in 3D virtual reality mode. It creates a virtual space by the combination of virtually enhanced physical and digital reality. This virtual world provides a lot within its virtual cyberspace, including digital currency, digital and virtual economy, and multiple owners can own it. Users can be able to buy and sell their goods and properties, and even users can sell and purchase other livelihood items including cars, clothes, and other living items. Metaverse claims even more at the next level to use the NFTs technology for digital assets. We expect many opportunities from Metaverse and its related technologies in the near future. Besides of these opportunities, the expected cybersecurity challenges are there as well, some of them such as NFTs, Darkverse, Financial fraud, Privacy issues, Cyber-physical threats, Virtual/augmented/mixed/extended reality threats, social engineering, and other related threats.

Brief Profile:

Professor Dr. Noor Zaman Jhanjhi, often referred to as N.Z. Jhanjhi, holds the esteemed position of Professor in Computer Science with specializations in Cybersecurity and Artificial Intelligence. He currently serves as the Program Director for Postgraduate Research Degree Programmes in Computer Science and Director of the Center for Smart Society (CSS5) at Taylor’s University, Malaysia. Recognized as one of the world’s top 2% research scientists for consecutive years in 2022 and 2023, he is esteemed as one of Malaysia's top three computer science researchers. Notably, he was honored as an Outstanding Faculty Member by MDEC Malaysia in 2022.

Prof. Jhanjhi boasts a prolific publication record with numerous highly indexed works in WoS/ISI/SCI/SCIE/Scopus, accumulating a collective research impact factor exceeding 1000 points. His Google Scholar H-index stands at an impressive 65, with an I-10 Index approaching 291, and a Scopus H-index of 42. With over 600 publications to his credit, including several international patents in Australia, Germany, the UK, and Japan, Prof. Jhanjhi has significantly contributed to the academic discourse.

An accomplished editor and author, he has curated over 50 research books published by esteemed publishers such as Springer, IGI Global USA, Taylor & Francis, IET, Elsevier, Wiley, Bentham, and Intech Open. Prof. Jhanjhi excels in mentoring postgraduate scholars, with over 38 scholars graduating under his tutelage. He also serves as Associate Editor and Editorial Assistant Board member for reputable journals and has received accolades such as the Outstanding Associate Editor award for IEEE ACCESS.

Renowned as a top-tier reviewer by Publons (Web of Science), Prof. Jhanjhi has evaluated over 60 theses as an external Ph.D./Master thesis examiner for universities worldwide. His extensive academic qualifications span 10 years and encompass accreditation bodies such as ABET, NCAAA, and NCEAC. Prof. Jhanjhi's diverse research interests encompass Cybersecurity, AI, IoT Security, Wireless Security, Data Science, Software Engineering, and Unmanned Aerial Vehicles (UAVs). Additionally, he has been invited as a keynote speaker for over 60 international conferences and has chaired numerous international conference sessions.

https://expert.taylors.edu.my/cv/noorzaman.jhanjhi
https://scholar.google.com/citations?hl=en&user=J6QVIncAAAAJ&view_op=list_works

Abstract of Talk:

Africa stands at a pivotal moment in its energy transition. Rapid urbanization, expanding electrification, increasing penetration of renewable energy resources, growth in distributed energy systems, and the need for resilient and affordable electricity are creating both significant challenges and unprecedented opportunities. Simultaneously, the modern era of Artificial Intelligence (AI)—driven by machine learning, deep learning, generative AI, foundation models, edge intelligence, and advanced computational capabilities—is redefining how complex infrastructures are designed, operated, and optimized. For electric power systems, AI presents transformative opportunities to leapfrog traditional approaches and accelerate the development of intelligent, resilient, and sustainable energy systems.

This keynote will present a forward-looking perspective on the opportunities and challenges of the modern AI era with applications to electric power systems, emphasizing their relevance to emerging and developing economies, particularly in Africa. The keynote will explore how AI can enable smarter grid operations, renewable energy integration, intelligent monitoring, forecasting, adaptive protection and control, predictive maintenance, energy management, digital twins, cybersecurity, and autonomous grid-edge intelligence for distributed energy resources, microgrids, and electric transportation.

The keynote will also address critical challenges that must be overcome for responsible and effective deployment of AI in mission-critical infrastructures. These include issues of trustworthiness, explainability, robustness, data scarcity and quality, cyber resilience, infrastructure limitations including energy sustainability for AI data centers, workforce preparedness, policy and regulation, and the integration of human expertise with intelligent decision-making systems. Opportunities for AI-enabled innovation that can support universal energy access, improve grid reliability, and foster sustainable economic development across the African continent will be discussed.

Drawing from decades of pioneering research and global experiences in computational intelligence and intelligent power systems, this keynote will provide insights into the future of AI-driven energy systems and inspire pathways for research, education, innovation, and international collaboration to build the next generation of intelligent and resilient power infrastructures.

Brief Profile:

Professor G. Kumar Venayagamoorthy is an internationally recognized leader in artificial intelligence, intelligent power systems, and smart grid technologies. He is the Duke Energy Distinguished Professor of Power Engineering and Professor of Electrical and Computer Engineering at Clemson University, USA, where he has served since 2012. He is also the Founder and Director of the Real-Time Power and Intelligent Systems Laboratory, a globally recognized research laboratory advancing next-generation intelligent energy systems. In addition, he holds the position of Extraordinary Professor in the Department of Electrical, Electronic and Computer Engineering at the University of Pretoria, South Africa.

A globally respected scholar, innovator, and thought leader, Professor Venayagamoorthy’s work has significantly shaped the field of computational intelligence applications in power and energy systems, helping pioneer advances in intelligent power systems, smart grids, and AI-driven energy technologies. His research spans artificial intelligence, machine learning, smart grids, power system dynamics and control, renewable energy integration, cybersecurity, and scalable computational intelligence for complex engineering systems. He is an inventor of transformative technologies in scalable computational intelligence and dynamic stochastic optimal power flow, contributing to the evolution of modern intelligent energy infrastructures.

Professor Venayagamoorthy earned his PhD and MScEng degrees in Electrical Engineering from the University of Natal, Durban, South Africa. He received his BEng degree with First-Class Honors in Electrical and Electronics Engineering from Abubakar Tafawa Balewa University, Nigeria, and later earned an MBA in Entrepreneurship and Innovation from Clemson University, USA—reflecting his unique blend of deep technical expertise and innovation leadership.

His pioneering contributions have earned international recognition, including the prestigious U.S. National Science Foundation (NSF) CAREER Award and the U.S. Office of Naval Research Young Investigator Award. He has authored more than 600 refereed technical publications, with over 26,000 citations, an h-index of 76, and an i10-index exceeding 300, underscoring the global influence of his scholarship.

An engaging and sought-after speaker, Professor Venayagamoorthy has delivered over 500 technical presentations, including more than 40 keynote and plenary lectures, in over 50 countries worldwide. His ability to bridge cutting-edge research with practical solutions for real-world energy challenges has made him a prominent voice on the future of AI and sustainable energy systems.

Professor Venayagamoorthy is a Fellow of the IEEE, IET (UK), the South African Institute of Electrical Engineers (SAIEE), and the Asia-Pacific Artificial Intelligence Association (AAIA), and a Senior Member of the International Neural Network Society (INNS), where he serves as the 2026 President-Elect. He founded and chairs the IEEE Power & Energy Society Working Group on Intelligent Control Systems and the IEEE Computational Intelligence Society Task Force on Smart Grid, shaping global research and practice at the intersection of AI and energy. He serves in editorial leadership roles across leading IEEE and Elsevier journals and is the Editor of the IEEE Press Series on Power and Energy Systems.

A distinguished global ambassador for engineering and innovation, Professor Venayagamoorthy is a current and past Distinguished Lecturer/Visitor of five IEEE societies—Computer Society, Computational Intelligence, Industry Applications, Industrial Electronics, and Power & Energy. He was a 2024 U.S. Fulbright Scholar to South Africa and will serve as General Chair of the 2027 International Joint Conference on Neural Networks (IJCNN) in Cape Town, South Africa, one of the world’s premier conferences in artificial intelligence and neural networks.

Abstract of Talk:

Smart contracts are utilized widely in developing safe, secure, and efficient decentralized applications. Smart contracts hold a significant amount of cryptocurrencies, and upgrading or changing them after deployment on the blockchain is difficult. Therefore, it is essential to analyze the integrity of contracts to design secure contracts before deploying them. As a result, the effective detection of various class vulnerabilities in smart contracts is a significant concern. While human specialists are still necessary for vulnerability detection methods that utilize machine learning and deep learning, these approaches often miss numerous vulnerabilities, leading to a significant false-negative rate. Hence there is a need for methods that significantly improve Ethereum smart contracts to circumvent these limitations. The best way to do this is using Deep learning. This talk explores about the role and future of DL in achieving it.

Brief Profile:

Dr. Meenakshi Tripathi is an Associate Professor in the Department of Computer Science and Engineering at Malaviya National Institute of Technology (MNIT), Jaipur. She earned her Ph.D. in Computer Science and Engineering from MNIT and brings over two decades of teaching and research experience in the fields of computer science and information security. Dr. Tripathi has authored more than 150 research papers published in reputed journals, conference proceedings, and edited volumes, including IEEE Transactions, International Journal of Computer Science, Computer Networks, and Journal of Supercomputing, among others. She has successfully supervised four Ph.D. scholars and is currently guiding five more. Dr. Tripathi actively contributes to several government-sponsored research projects funded by agencies such as DST, MEITY, DSIR, and DST Rajasthan, among others. She also holds two patents in her name: "A Bluetooth-Based Anti-Theft System" and "Blockchain-Integrated Device for Network Security." In addition to her academic contributions, she holds several prominent professional roles, including Dean at Vishwakarma Skill University, Jaipur; Board of Studies (BoS) member at the University of Kota and the Central University of Rajasthan; and former Chairperson of the CSI Jaipur Chapter. She was honored with the Active Participation Woman Award for Research by CSI-India in 2018. She has served as the Organizing Chair for numerous national and international conferences, faculty development programs (FDPs), and workshops, such as ICCIS 2023, ANTS 2023, ETNCC 2023 & 2024 (Namibia), ICDLAIR 2019, the ATAL FDP on "Cyber Security", as well as FDPs on "Software Defined Networks" and "Technical Writing: Tools and Techniques". She has also received funding from IEEE CIS to organize Summer Schools in 2022, 2023, and 2024. Dr. Tripathi is a Senior Member of IEEE, a member of ACM, and a life member of CSI. Her research interests include Cybersecurity & Adversarial Learning, Blockchain, Internet of Things (IoT) & Edge Security, Wireless Sensor Netwokrs, AI-generated Content and Deepfakes , Drone Swarms and their issues.

Abstract of Talk:

Today, Smartphones have quality high resolution cameras, and taking a photo or video and sharing it has never been easier, resulting in the incredible growth of modern social networks like Facebook and Instagram. YouTube might be the second largest search engine and hundreds of hours of video are uploaded every minute and billions of videos are watched every day. The internet is comprised of text and images. It is relatively straightforward to index and search text, but in order to index and search images, algorithms need to know what the images contain. To get the most out of image and video data, we need computers to “see” an image and understand the content. In this talk, we introduce Computer vision with a brief about some machine learning processes. Then, we will discuss “Amazon Rekognition” for images and video of AWS and the algorithms for searchable image and video libraries. We also discuss some cases of Image moderation and sentiment analysis

Brief Profile:

Dr. Durgesh Kumar Mishra has received M.Tech. degree in Computer Science from DAVV, Indore in 1994 and a Ph.D. degree in Computer Engineering in 2008. Presently, he has been working as a Director and Professor SCSIT, Symbiosis University of Applied Sciences, Indore. He was founder Director, Microsoft Innovation Centre at SAIT, Indore, India. He is associated with Namibia University of Science and Technology as the Program Advisory Committee for Doctor of Philosophy Computer Science (NQF level 10). Ex-visiting faculty at IIT-Indore. He has 30 years of teaching and 15 years of research experience with a good number of citations with h-index and i-index. He has four patents granted and twelve published jointly with Ph.D. students and more than 100 papers in refereed journals and conferences in his research field. His Ph.D. is in Secure Multi-Party Computation for Preserving Privacy. He has organized a number of IEEE, ACM, and Springer conferences in the capacity of conference General Chair and editor of conference proceedings. He is a Sr Member of IEEE, ACM, and CSI and held many positions like Chairman, IEEE Computer Society Madhya Pradesh Section(2022 to 2023),IEEE MP-Subsection (2011-2012), and Chairman IEEE Computer Society Bombay Chapter (2009-2010). Chairman CSI Division IV Communication at National Level (2014-2018). National Treasurer Computer Society of India (2019-2021). At Present he is the Chairman IEEE Madhya Pradesh Section and Chairman of ACM Indore Chapter. Dr. Mishra visited and delivered his invited talk in Taiwan, Bangladesh, Singapore, Indonesia, Sri Lanka, Nepal, the USA, UK, and France. He has authored two books on “Database Management Systems” and “Programming in C and C++”. He edited 12 international books of Springer publication in his domain of Computer Science. He has been a consultant to industries and government organizations like the sales tax and labor department of the government of Madhya Pradesh, India. He has been awarded the “Paper Presenter award at International Level” by the Computer Society of India. He visited MIT Boston and presented his presentation on Security and Privacy he has also Chaired a panel on “Digital Monozukuri” at “Norbert Winner in 21st century” at BOSTON. He became a Member of the Bureau of Indian Standards (BIS), Govt of India for the Information Security domain. Recently, Microsoft invited him for his felicitation and to deliver his Innovation at Xi’an China. He has the recipient of many awards from the largest professional society CSI. Recently VDGOOD Society India, Awarded him as International Scientist Award for Engineering, Science, and Medicine.

Abstract of Talk:

Metaverse is an evolving paradigm that intends to provide 3D immersive experiences and self-sustaining virtual shared space that people can access via the Internet. Technologies like virtual reality (VR) and augmented reality (AR) are combined in the metaverse to create a sense of 'virtual presence – Internet in its 3D form’. To achieve its full potential, Metaverse must satisfy specific requirements, including low latency, high resource demands, robust network infrastructure, handling massive data volume, high data rate, security concerns, application interoperability to mention a few. 5G networks cannot support all these requirements to realize the true potential of Metaverse. It is envisioned that future 6G networks can help the different Metaverse applications to flourish to their full potential. This talk will discuss recent advancements in Metaverse and 6G networks, including how Artificial Intelligence and Machine Learning are changing Metaverse applications. Different research challenges will be highlighted as well. 

Brief Profile:

Prof. Dr Sayan Kumar Ray is currently the Head of School of Computer Science and an Professor at Taylor’s University, Malaysia. Prior to this, he worked at Manukau Institute of Technology in Auckland, New Zealand, in different positions including the Head of School of Digital Technologies, Associate Dean of Faculty of Business and Information Technology, Head of Networking programmes, and Academic Leader of Research and Curriculum Development of Digital Technologies. Sayan also worked as Design Engineer at Tait Communications Ltd. In New Zealand and as consultant for other organizations in New Zealand. He completed his Ph.D in Computer Science from University of Canterbury in New Zealand, and Master of Technology and Bachelor of Engineering degrees both in Computer Science and Engineering, respectively, from the University of Calcutta and Gulbarga University in India. As an active researcher, Sayan’s research covers a broad range of topics, like Security and Trusts in Internet of Things (IoT), Intrusion Detection System in IoT, IoT applications in Healthcare and Disaster Management, Cybersecurity of Metaverse, 5G/6G Networks, Mobility and Handover in Multi-tier networks, Dynamic Spectrum Sharing and Management, Private 5G Networks, and Applications of AI and Machine Learning in Healthcare. He regularly publishes in top-tier journals and international conferences and his co-authored papers have featured in reputed venues like IEEE JSAC, IEEE Communications Surveys and Tutorials, IEEE Access, Journal of Networks and Computer Applications, Computer Networks, Future Generation Computer Systems, Sensors, IEEE WCNC, IEEE LCN, PACIS, etc. Sayan’s coauthored papers have won Best Paper Awards in EAI SmartGift 2021 conference, IEEE IEMCON 2020 conference, Alison Young Best Paper Award at CITRENZ 2019 Conference, IEEE ICOIN 2017 conference, Gowri Memorial Best Paper Award in IETE Technical Review Journal, and a Commendation Award at CITRENZ 2022 conference. He has won Research Excellence Award, Outstanding Performance Achievement Award, and Teaching Excellence Award at Manukau Institute of Technology, New Zealand. Sayan regularly gets invited to deliver keynotes and invited talks and has won multiple research grants, and scholarships. He is also the coinventor of two UK patents.

Abstract of Talk:

Biomedical image processing has really gone through an unbelievable expansion process and has been a multiple faceted disciplinary research field engaging expertise from useful mathematics, computer sciences, engineering, statistics, physics, biology and medicine. Medical images play vital role to explore the Anatomy of the human body, to diagnose diseases & to examine various illnesses.  Image processing and its application in medical field include imaging modalities such as Ultrasound, Computed Tomography, Magnetic Resonance Imaging and Positron Emission Tomography. Mathematics of these modalities are using in Medical Imaging. By Visualization of 2-D medical ultrasonic images, filtering is done to remove noise. Main problem with ultrasonic images is occurrence of speckle noise and because of speckle noise the image resolution and contrast become concentrated, which affects the diagnostic appraisal of this imaging modality. It can affect picture quality. We will discuss how to remove speckle noise by applying image processing filters so radiologist can get better picture for good clinical results. In this talk we will also discuss about various methods and tools for speckle noise suppression for medical B-scan ultrasonic images, denoising with wavelets, reduction of speckle noise by using image processing filters. 

Brief Profile:

Prof. Manju Mandot is  Director and Professor in the Department of Computer Science and IT, JRN, Rajasthan Vidhyapeeth University, Udaipur, Rajasthan-India. She has more than 30 years of experience in teaching, administrative, research in the field of Computer Science. Dr. Mandot did her Ph.D in the Computer Science. She has been actively involved in research, development, and clinical application of medical imaging technologies for the past 15 years. She has supervised 16 research scholars. She has published more than 80 research articles, written five books, securing patents. She has invited as keynote speaker for National and International conferences and chaired numerous international conference sessions. Dr. Mandot has been consultant to industries and government organisations

Abstract of Talk:

Neurodegenerative diseases represent the new emergency because of the their exponential growth due primarly to increase of the size fo the general population and of the expectation of life in the whole world. These demographic factors are driving also the geographic distribution of this new emergency that is now primarly in East and South Asia. In the future this wave of diseases and cases will surely affect Sub-Saharian Africa. 

Alzheimer’s disease, the most common, has for the first time effective treatment with the recent approval of antiamyloid therapies in Asia, North America ad Europe. These therapies to be effective need early diagnosis and biological diagnosis with the use of imaging and fluid biomarkers. With the introduction of plasma based biomarkers for the first time we are going to have valid , easy access, transportable and cheap   biomarkers. With the introdcution of new Technologies for many biomarkers we are going to have large amounts of heterogeneous data for many variables with the key aims of providing diagnosis and prediction of status ( prognosis) with apersonilized medicine approach. The substitution of traditional statistical frequentistic approach   with tecniques like deep learning and random forest is needed both in research and in clinical medicine. The theoretical introduction of the digital twin model in this research setting will be discussed as a new tool determine the observed phenotype and predict the future status of complex dynamic systems as the brain and of compkex and interacting cognitive/behavioral/ motor functions. In the digital twins complex data (the physical twin) will be used to construct representative models ( the digital twin) with the use of nanotechonologies ( sensors for continous monitoring) and AI ( to build up  advanced self-supervised learning (SSL) algorithms). In this rapidly evolving fiels, the most important challenge is the scarsity of human usable data for AI application( metric and longitudinal data). The traditional clinical medical approach is useless in this context. A model from our center on neurodegenerative disease and the aging brain (CMNDG)  in South Italy will be presented with the sistematic collection of high quality, multidimensional,  and metric data.

Brief Profile:

Prof Giancarlo Logroscino, MD PhD is the director of the Neurodegenerative Diseases Unit of The University of Bari and Chair of the Department of Clinical Research in Neurology at Pia Fondazione Panico in Tricase (LE). He is full Professor of Neurology at University of Bari. He has been trained in Neurology (University of Bari) and Epidemiology (PhD, Columbia University NYC). He has been associate professor of epidemiology and neurology at Harvard University (2002-2008). His primary research interests are natural history of neurodegenerative diseases and environmental risk factors for neurodegenerative diseases related to aging.  He has conducted studies on Parkinson’s disease, Amyotrophic Lateral Sclerosis, Alzheimer’s disease, Fronto-temporal dementia, Lewy Body Diseases both in clinical settings and in population based settings.  He is leading projects and studies in Europe and outside Europe. He has studied the role of dietary factors and iron/iron (metals) metabolism in Parkinson’s disease and Alzheimer’s disease. He has established one of the first population-based registries of Amyotrophic Lateral Sclerosis in the world, (SLAP) based in Apulia, Southern Italy. He is a member of the steering committee of EURALS, the European project on descriptive and analytic factors of ALS. He is part of EUROMOTOR consortium. He is the co-PI of a Center for Disease Controls (CDC) founded, project to study ALS and cognitive impairment in ALS in South America. He has established a populationbased registry for Rare Neurodegenerative Diseases in Puglia (SLAP_Dem_Puglia_Registry). A similar project has been recently launched in Albania, Kossovo and Montenegro (Balcanic area) and Cambodia. He is focusing on the aging brain and risk/protective factors for cognitive decline and longevity with data from prospective cohorts both in the US and Europe. He is the PI of the Great Age study, a population-based study on aging, frailty neurodegeneration and diet in Castellana Grotte (BA), recently awarded by a special grant for aging research. In this study eight research groups are studying the complexities of the aging process.

He is working on methodological issues on studies of neurodegenerative diseases. In this context is a member of MELODEM (methods in longitudinal studies of dementia). He is part of the of the Global Burden of Diseases (GBD) and of the task force on neurology of the Global Burden of Disease (GBD) founded by World Bank and Bill and Melissa Gates Foundation.

Abstract of Talk:

The rapid growth of electric vehicles (EVs) worldwide is expected to increase the volume of second-life EV components, particularly electric motors, many of which retain significant functional value. This webinar focuses on the characterisation of second-life EV motors for stationary microgrid power generation, especially in the context of distributed renewable microgrids in Sub-Saharan Africa. Given the high torque density, efficiency and reliability of EV motors, especially permanent magnet synchronous motors (PMSMs) and induction motors (IMs), present a promising opportunity for second-life applications. Through motor analysis and reconfiguration strategies, this webinar aims to evaluate the technical viability, adaptation potential and integration pathways of retired EV motors for electricity generation. This work supports circular economy principles and localisation of technology, aligning with efforts under the UKRI-funded CEPREC project.

Brief Profile:

Dr Udochukwu B. Akuru is a Senior Lecturer in the Department of Electrical Engineering at Tshwane University of Technology and an NRF C1-rated researcher with expertise in the design and optimisation of electrical machines for renewable energy technologies and sustainable energy systems. He received the B.Eng. and M.Eng. degrees from the University of Nigeria, Nsukka, in 2008 and 2013, respectively, and the PhD degree in electrical engineering from Stellenbosch University, South Africa, in 2017. He held a Postdoctoral Research Fellowship with Stellenbosch University from 2018 to 2019 and was a Lecturer with the University of Nigeria from 2011 to 2019. He has authored or coauthored numerous papers and serves as a reviewer for several journals and conferences. He served as the General Chair of the 33rd Southern African Universities Power Engineering Conference (SAUPEC 2025). He is currently a Professional Registered Engineer with the Engineering Council of South Africa (ECSA) and the Council for the Regulation of Engineering in Nigeria (COREN), he is a Senior Member of IEEE & SAIEE, as well as a volunteer with various societies and committees, including IEEE IAS EMC, IEEE IES EMTC and SAIEE RMS. He is a recipient of several grants and awards, including the prestigious Jorma Luomi Student Forum Award at the 2018 International Conference on Electrical Machines (ICEM) and the 2020 TWAS-DFG Research Fellowship. He is also an Associate Editor of the IEEE Transactions on Industry Applications and IET Electric Power Applications, country lead for the UKRI-funded Circular Economy Powered Renewable Energy Centre (CEPREC) project, and the current Chairperson of the IEEE South Africa Section.

Abstract of Talk:

Generative Artificial Intelligence (GenAI) is fundamentally reshaping higher education worldwide, transforming how knowledge is created, accessed, and assessed. From AI-powered tutors and intelligent learning assistants to advanced large language models, these technologies are redefining the educational landscape and creating unprecedented opportunities for personalized learning and innovation. At the same time, they raise profound questions about academic integrity, assessment validity, learner authenticity, and the future credibility of university qualifications. This talk explores the emerging paradigm of Responsible Artificial Intelligence (RAI) as a strategic foundation for building trust in higher education. Rather than viewing AI as a threat that must be prohibited or outpaced, the session argues that institutions should embrace AI responsibly through ethical governance, transparent policies, human oversight, and the redesign of authentic assessment practices. The presentation introduces a practical framework that aligns AI innovation with the core values of fairness, accountability, transparency, inclusiveness, and educational quality. It discusses how competency-based assessment, reflective learning, project-based evaluation, and oral defence mechanisms can ensure that graduates continue to demonstrate genuine knowledge, critical thinking, creativity, and professional capability in an AI-enabled world. Drawing upon international developments in AI ethics, digital transformation, and quality assurance, this session will provide educators, researchers, policymakers, and institutional leaders with insights into creating resilient and trustworthy educational systems. The discussion will also consider the evolving role of universities in preparing graduates who can collaborate effectively with AI while maintaining human judgment, ethical reasoning, and lifelong learning capabilities. Ultimately, the session argues that the future of higher education depends not on resisting artificial intelligence, but on governing and integrating it responsibly. By embedding Responsible AI principles into teaching, learning, and assessment, institutions can strengthen public trust, safeguard academic integrity, and equip learners to thrive in the rapidly evolving global knowledge economy.

Keywords: Responsible Artificial Intelligence, Generative AI, Higher Education, Academic Integrity, Authentic Assessment, AI Governance, Trustworthy AI, Digital Transformation, Educational Innovation, Quality Assurance.

Brief Profile:

Dr. Saroj Hiranwal is the Course Director – IT Programs at the Australian Institute of Advanced Technologies (AIAT), Adelaide, Australia. She also serves as Program Coordinator for BITS and Sr, Lecturer (Higher Education) in the department of Information Technology & Security at the Victorian Institute of Technology, Adelaide Campus, South Australia. She has made significant academic and research contributions in the areas of machine learning, artificial intelligence, and real-time systems. Her research interests further extend to high-performance scientific computing, cloud computing, network security, image processing, data analytics, and edge computing. Her work supports the development of advanced technological solutions across diverse sectors including healthcare, agriculture, smart cities, education, marketing, and finance. Dr. Hiranwal has authored more than 50 research papers published in reputed international journals and conferences. Her research demonstrates a strong interdisciplinary focus, integrating theoretical foundations with applied and industry-relevant innovations. She began her academic career in 2006 as a Lecturer and progressed through senior academic roles including Senior Lecturer, Reader, and Professor, reflecting sustained excellence in teaching, research, and academic leadership. Dr. Hiranwal received her Bachelor of Engineering in Information Technology from the University of Rajasthan, Jaipur, India (2004). She completed her Master of Technology in Information Technology from the Allahabad Agricultural Institute, Allahabad, India (2006), and earned her Ph.D. in Computer Science & Engineering from Suresh Gyan Vihar University, Jaipur, India (2014).