University of South Wales
Upskilling medical professionals in developing economies through Virtual Reality (VR) training presents a opportunity to address long-standing disparities in healthcare education and access to quality training. In regions where healthcare systems often struggle with a shortage of resources, limited infrastructure, and insufficient access to advanced medical tools, VR technology can offer an innovative solution by creating immersive, hands-on learning environments. Medical practitioners can engage in realistic simulations of complex procedures, practice emergency interventions, and refine diagnostic skills in a controlled and risk-free space. This allows healthcare workers to repeatedly hone their techniques without the need for costly equipment, live patients, or even the proximity of expert mentors—elements that are often lacking in underserved regions. Moreover, VR training can be customized to meet the specific needs of local health challenges, enabling professionals to practice and prepare for scenarios they are most likely to encounter. Whether it is mastering life-saving techniques in trauma care, improving neonatal care in regions with high infant mortality rates, or staying updated on new surgical innovations, VR offers flexible and scalable learning opportunities that can be tailored to different specialties. In addition, VR training democratizes medical education by removing the barriers imposed by geography or economic limitations. Medical professionals in rural or remote areas, who might otherwise be excluded from continuous learning opportunities, can now access the same high-calibre training as their counterparts in urban centres. This can enhance the overall competency of healthcare workers across developing economies, bringing them up to par with global standards. Ultimately, the integration of VR in medical training not only helps to bridge the skills gap but also empowers healthcare systems in developing economies to better serve their populations.
Andrew is Professor of Computing at the University of South Wales in the United Kingdom. His research interest centre on the use of intelligent computer systems (Artificial Intelligence and Data Science oriented solutions) to help solve real-world problems. Andrew is currently working on AI-related projects with several industrial and commercial partners that include Tata Steel, National Health Service Wales Informatics Service, and Wye Education. Andrew is also Director of Aurora International Consulting Ltd, an innovative software-as-a-service company that provides AI-enabled review software to the construction industry. Andrew is Director of Research for the Welsh Institute of Digital Information, a collaboration between the University of South Wales, the University of Wales Trinity Saint David, and the NHS Wales Informatics Service (NWIS). Andrew is a Regional Director of Techno Camps, an innovative and ambitious project that seeks to engage young people with computing and its cognate subjects. Moreover, Andrew is Editor in Chief of the journal Annals of Emerging Technologies in Computing (AETiC). Professor Ware teaches various computing courses including artificial intelligence, data mining and computer programming. Moreover, Andrew has successfully supervised nearly forty PhD students and has been an active participant in several international research and teaching projects.
Chairman and Central Project Director of Pakistan National Center of Artificial Intelligence (NCAI), Pakistan
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Prof Dr Yasar Ayaz is the Founding Chairman and Central Project Director of Pakistan National Center of Artificial Intelligence (NCAI) headquartered at National University of Sciences and Technology (NUST) in Islamabad. He also founded Pakistan first Department of Robotics & Artificial Intelligence at NUST in 2010 where he is also currently a full Professor. He holds international Adjunct Professor titles at Tohoku University, Japan and China University of Mining and Technology, Beijing. He is the author of over 150 international publications and has won international best paper awards in London, UK and Sydney, Australia in 2018 and 2013 respectively. He also has 3 product design patents registered in his name with several more under review. He has delivered more than 60 invited and keynote talks at prominent venues including USA, Japan, UK, South Korea, China, Italy, Belarus, Norway etc and has won and developed projects of well over Two Billion Pakistan Rupees including international grants and national consortium based projects. In addition to winning President Gold Medal, University Best Teacher Award and SMME Best Researcher Award and university Top Performer award at NUST, Prof Yasar has also won Pakistan Engineering Council (PEC) Engineers Excellence Award. He has been awarded Lifetime Achievement Award by IEEE Islamabad Section and is also a recipient of President Award for Pride of Performance which is one of the highest Civil Awards of Pakistan conferred by the Honorable President of Pakistan himself in 2021.
Queen Mary University of London
The current dominant trend for AI is for a small number of organisations, either industrial, institutional or national, but seldom customer or citizen-driven ones, to amass big data, and to apply increasingly sophisticated (e.g., deep machine learning) AI algorithms, executed in remote centralised (cloud-based) high-energy & high-computation resources, to help solve real world problems that are more general, hence, the term AGI (where G=General)I. And yes, some problems are able to be solved better this way but is this always the most suitable way to support and solve the many outstanding critical environmental & human societal issues? In this talk, some reflections will be offered to counter and complement the current dominant (big data, deep ML) AI model trend. This includes: the motivation for distributed, small data edge-computing driven AI, the distributed heterogenous AI interoperability challenges, a discussion of some models that underpin some applications to enable this, and the future outlook.
Stefan Poslad leads the IoT2US (Internet of Things to Ubiquitous, Computer, Science) Lab at Queen Mary University of London, where he is a fellow of the Digital Environment Research Institute (DERI), and Cognitive Science research group. He is regarded by Stanford University as being in the top 2% of scientists worldwide. His current research and innovation focus is AI-driven, data science-driven and geoscience-driven models, to enhance how we physically sense and analyse human location and motion behaviour shifts, and physical environment changes, both outdoors and indoors. He has been the lead researcher for QMUL in over 15 international collaborative projects with industry. He is the sole author of a leading book on Ubiquitous Computing: Smart Devices, Environments and Interaction that has over 1000 research citations that is in use for teaching by over 70 institutes worldwide, across 6 continents.
Universiti Putra, Malaysia
Mobile communication changes transmission capability and speed every year with the passage of time and generation. 5G is the modern way of mobile communication which is using across the world. As 5G is being used by different numerous people, it is required to implement security mechanisms that safe the transmission of data to the client. The 5G Mobile communication utilize various nodes to offer secure and on-demand connectivity to other devices. The authentication of nodes in 5G networks based on classical cryptography, are exposed to eavesdropping in communication. The emergence of quantum authentication has attracted significant interest and has become active research in the Post-quantum Cryptography (PQC) area. The PQC is strengthened by the unconditional security in quantum mechanics law as proven by the non-cloning theorem and Heisenberg Uncertainty theory. Quantum key distribution (QKD) is a method of securely exchanging encryption keys between communicating parties. Communication in QKD involves two different channels: the Quantum Channel for photon transmission and the Classical Channel for post-data processing. However, the post-processing stage requires authenticated classical communication to thwart security threats like eavesdropping and man-in-the-middle attacks. Currently, classical channel authentication relies on classical cryptographic methods which are inefficient and vulnerable to quantum attacks. Post-Quantum Cryptography (PQC) can solve encryption and authentication issues in the classical channel due to its quantum-safe nature and strong computational security.
Zuriati Ahmad Zukarnain has received her Doctor of Philosophy in the area of Quantum Computing from University of Bradford, UK in the year 2006. She has been appointed as the head of department for the department of Communication Technology and Networks from 2006 until 2011. She became an Associate Professor in 2011 and a full professor in the year 2017. She has been appointed as the deputy dean of the Faculty of Computer Science and Information Technology in the year 2017. Subsequently, she has been appointed as the deputy dean of School of Graduate Studies UPM in the year 2019. Dr. Zuriati has pursued an in depth research in the area of Quantum Communication and Wireless Networks. She has carried out her research work including the Authentication Multi photon over secured direct communication, Authentication of Single photon for multi party Quantum Key Distribution Protocols, Quantum Key Distribution for Quantum Cryptography and Quantum Communication, Cashless Payment System using Blockchain Technology, Quantum Processor Unit for Quantum Computers and Intra-domain Mobility Handling Scheme for Wireless Networks. Her research has been given recognition in its significance and impact with her publications in high impact journals. Dr. Zuriati has extensive research experience and has published widely in Quantum Communication and wireless networking research. Most of the research conducted are supported by Ministry of Higher Education(MOHE) and Ministry of Science, Technology and Innovation(MOSTI). She managed to extend her Science fund project into the Prototype Research Grant Project(PRGS). The research involved a basic setup Quantum experiment which aims to produce a software designing tool for Quantum Communications known as the Quantum Communication Simulator(QuCS). Apart from doing research, she has also involved as a member of the editorial board of several international peer-reviewed and cited journals. At the international level, Zuriati has been awarded as the Distinguished Woman In Computer Science award at the 4th Venus International Women Awards(VIWA), 2019. More importantly the software, QuCS that she developed won a gold award and a special award at the 2016 International Invention Innovation, Canada.
Quaid-i-Azam University, Islamabad
Deep learning is widely used in numerous applications ranging from speech recognition, natural language understanding and computer vision etc. No single algorithm paradigm has even been so broadly and successfully used as deep nets. Invited talk will focus on history of deep learning, its applications and research trends.
Ayyaz Hussain is currently working as Professor of Computer Science at Quaid-i-Azam University Islamabad. From 2010 to 2020 he was Associate Professor and Chair of the Department of Computer Science & Software Engineering at International Islamic University Islamabad. He worked as Research Professor at Gwangju Institute of Science and Technology South Korea from 2013-2014. During 2000 to 2010 he served as Software Engineer at National Engineering and Scientific Commission. Dr. Hussain received his PhD from National University of Computer and Emerging Sciences (NUCES-FAST) in 2009. His research interests include Image processing, computer vision, machine learning and deep learning. He has published more than 40 journal articles along with number of conference papers. He has supervised more than 10 PhD and 25 MS students.
Higher Colleges of technology, UAE
Information security is increasingly concerning due to the growing sophistication of social engineering threats, with tactics continuously evolving. A key issue is the lack of awareness regarding social engineering, which heightens human cyber security risks. Developing knowledge to combat these attacks presents several challenges. As social engineering becomes more prevalent, raising awareness about security breaches is crucial to reducing cyber incidents and preventing potential financial and human losses. Social engineering awareness tools offer users a convenient way to learn, accessible anytime and anywhere, unlike traditional training sessions that require scheduling. These tools make it easier for individuals to understand and recognize social engineering attacks, allowing them to revisit the material as needed and at their own pace. As such gamification strategies contribute to fostering a security-aware culture within organizations, ultimately reducing risks linked to social engineering attacks.
Dr. Vasaki Ponnusamy is an Assistant Professor at Higher Colleges of Technology UAE. She obtained her Bachelor of Computer Science and MSc (Computer Science) from Science University of Malaysia and her PhD in IT from Universiti Teknologi PETRONAS (UTP), Malaysia (2013). She is currently working on cybersecurity, IoT security trends and digital governance. She has great International exposure as Keynote Speaker, Visiting Professor and several Fellowships. She has been teaching information and network security, wireless security and data communication and networking. She is specialized in handling Cisco devices for routing and security. It is her passion to share her technical knowledge with the community. Her area of specializations are Networking, Communication, Penetrating Testing and Cybersecurity.
HITEC University Taxila, Pakistan
The diagnosis of human diseases using the artificial intelligence techniques is evolving and is a hot research area. Manual detection and classification are tedious, time-consuming and errorprone, therefore, automated techniques are required. Timely detection and classification of these diseases can save human life or help the practitioners/doctors to take precautionary measures for cure of the disease. Artificial intelligence techniques especially deep learning has revolutionized the medical field. It provides the aide to the practitioners in terms of diagnosis and helps them better understand as well as timely identification of disease. The talk is related to deep learning and its applications for medical image diagnosis, identifies the current trends as well as future challenges related to the domain.
A highly motivated professional having 20+ years’ experience in teaching in public and private universities in Pakistan. Successfully published 50+ research articles in reputable journals, conferences, and book chapters. Worked on numerous research projects in machine learning, deep learning, and computer vision. Worth mentioning research topics explored are related to gastrointestinal disease detection and classification, facial expression recognition, brain tumor segmentation and classification, skin disease classification, blood cell disease classification, signature verification, lung nodule detection and classification. Ambitious to work in a challenging environment while being part of a prestigious organization/team for its ample growth.
Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia
Autism spectrum disorder (ASD) affects a significant portion of the population. Very less respondents in developing countries demonstrated awareness of ASD. The purpose of this work is to create a comprehensive study that aims to develop a multimodal ensemble model for the early detection of autism spectrum disorder (ASD). It involves utilizing both facial and MRI image datasets that are publicly available, as well as can be locally collected data. The successful implementation of this research will align with the Sustainable Development Goal for mental health, enabling early detection and intervention for individuals with ASD. This will provide caregivers, parents, and educators with the ability to offer more effective support, ultimately fostering the socialization and cognitive development of autistic individuals. The outcomes of this study will promise a brighter and more inclusive future for the ASD community in Saudi Arabia and beyond.
Sheeraz Akram is working as Associate Professor at Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia. Sheeraz is actively leading and coordinating research activities at Intelligent Data Visual Computing Research (IDVCR). He worked as Associate Professor at Faculty of Computer Science & Information Technology, Superior University Lahore, Pakistan. Sheeraz completed his Postdoctoral Research Training from University of Pittsburgh, USA. He also completed his STEM training offered by Center of Integrated Research in Teaching and Learning (CIRTL) at University of Pittsburgh, USA. Sheeraz completed his Ph.D. in software engineering from National University of Sciences and Technology (NUST), Islamabad, Pakistan and Master of Science in Computer Science from Lahore University of Management Sciences (LUMS), Lahore, Pakistan.
Information Technology University of the Punjab (ITU), Lahore
Accidental oil spills or dumping by oil tankers in the open waters is a threat to marine and coastal ecosystems. Synthetic-Aperture Radar (SAR) is a useful tool for analysing oil spills, because it operates in all-day, all-weather conditions. An oil spill can typically be seen as a dark stretch in SAR images and can often be detected through visual inspection. The major challenge is to differentiate oil spills from look-alikes, i.e., low-wind areas, algae blooms and grease ice, etc., that have a dark signature similar to that of an oil spill. It has been noted over time that oil spill events in Pakistan’s territorial waters often remain undetected until the oil reaches the coastal regions or it is located by concerned authorities during patrolling. A formal remote sensing-based operational framework for oil spills detection in Pakistan’s Exclusive Economic Zone (EEZ) in the Arabian Sea is urgently needed. In this talk, we present our methodology based on the use of an encoder–decoder-based convolutional neural network trained on an annotated dataset comprising selected oil spill events verified by the European Maritime Safety Agency (EMSA). The dataset encompasses multiple classes, viz., sea surface, oil spill, look-alikes, ships and land. We processed Sentinel-1 acquisitions over the EEZ from January 2017 to December 2023, and we thereby prepared a repository of SAR images for the aforementioned duration. This repository contained images that had been vetted by experts, to trace and confirm oil spills. We tested the repository using the trained model, and, to our surprise, we detected 92 major previously unreported oil spill events within those seven years. In 2020, our model detected 26 oil spills in the EEZ, which corresponds to the highest number of spills detected in a single year; whereas in 2023, our model detected 10 oil spill events. In terms of the total surface area covered by the spills, the worst year was 2021, with a cumulative 395 sq. km covered in oil or an oil-like substance. On the whole, these are alarming figures.
Dr. Muhammad Adnan Siddique is currently an Assistant Professor & Director of the Remote Sensing & Spatial Analytics Lab, at Information Technology University of the Punjab (ITU), Lahore, Pakistan. His research generally revolves around signal processing and machine learning for various geoscience applications, such as monitoring land surface deformation using space-borne radar imaging, observing glacier dynamics with active or passive sensors, detection of marine pollution, etc. He is assimilating pattern recognition & learning inspired approaches with traditional remote sensing. He also works in geospatial analytics. Dr. Siddique received the B.E. degree in electronics engineering from the National University of Sciences and Technology (NUST), Pakistan in 2006. He obtained the European Master of Research in Information and Communications Technology (MERIT) joint degree from Karlsruhe Institute of Technology (KIT), Germany and Universitat Politecnica de Cataluyna (UPC), Spain, in 2010. He did doctorate/post-doc at the Chair of Earth Observation & Remote Sensing, Swiss Federal Institute of Technology, ETH Zurich, Switzerland, from 2013 – 2018. Thereafter, he joined the National University of Computer and Emerging Sciences (NUCES) in 2019, and spent two semesters there as an Assistant Professor before moving to ITU in June 2020. In the long run, his aim is to contribute towards environmental protection by enabling the right technology-based interventions!
National University of Sciences and Technology (NUST), Islamabad
The convergence of artificial intelligence (AI) and robotics is ushering in a new era of automation, revolutionizing industries and reshaping our world. In this keynote, we are going to explore the cutting-edge advancements in AI-powered robotics, highlighting their transformative potential. We will delve into the key technologies driving these innovations, including machine learning, computer vision, and reinforcement learning. These technologies are enabling robots to perceive their environments, learn from experiences, and make intelligent decisions, leading to unprecedented levels of autonomy and adaptability. We are going to see how these technologies are being used in projects being carried out in Intelligent Robotics Lab (IRL) at the National Centre of Artificial Intelligence. By exploring the latest advancements, applications, and challenges, we aim to inspire and inform the audience about the transformative potential of this technology.
Dr. Khawaja Fahad Iqbal is an Assistant Professor at the Department of Robotics and Artificial Intelligence at the National University of Sciences and Technology (NUST). He is also serving as the Co-Principal Investigator for the Intelligent Robotics Lab at the National Centre of Artificial Intelligence (NCAI). He has been entrusted with the responsibilities of being a Treasurer for IEEE Robotics and Automation Society, Pakistan, and Finance Secretary of MEXT Alumni Association of Pakistan (MAAP) for 2024-25. Dr. Fahad is the founding CEO of Rise AI Pvt. Ltd. which is a spin-off of NUST registered with the National Science and Technology Park (NSTP). It provides consultancy and training to the traditional institutes, local industries, and SMEs and helps them automate their products and services Dr. Fahad obtained his PhD degree in Robotics in 2022 and MS degree in Bioengineering and Robotics degrees in 2017 from Tohoku University, Japan. He received the Japanese Government (MEXT) scholarship for both his MS and PhD. He completed his BE degree in Mechatronics Engineering from NUST in 2011. He has authored over 25 research papers in well-reputed international journals and peer-reviewed conferences. His research interests include Collaborative Robots, Motion Planning, Reinforcement Learning, Generative AI, Augmented Reality, and Robot Control.
Habib University, Karachi
As data centers scale to meet increasing digital demands, power consumption and operational reliability have become critical concerns. Power electronics plays a central role in optimizing energy conversion and management, directly impacting the efficiency and resilience of data center infrastructure. In this talk, I shall be highlighting key power electronics technologies that enable enhanced energy efficiency and reliability in data centers. I will focus on discussing the advancements in power conversion and management systems for realization of energy efficient and reliable data centers. I shall also be discussing the role of energy-saving techniques in power conversion, the integration of energy storage systems, power quality management, and resilient designs. The talk will also highlight the emerging trends in wide-bandgap semiconductors and modular power systems, showing how they contribute to both energy optimization and robustness.
Dr. Ahmad Usman is currently working as an Assistant Professor in the Electrical and Computer Engineering Program at Habib University, Karachi, Pakistan. He has received his B.Sc. and M.Sc. from the University of Engineering and Technology (UET), Lahore, Pakistan in 2008 and 2011, respectively. He has received his M.Sc. in Electrical Engineering (majors in Optics and Microsystems), M.Sc. in Mechanical Engineering (majors in MEMS, Packaging, and Nanotechnology), and Ph.D. in 2014, 2016, and 2018 from the Georgia Institute of Technology, respectively. He is a recipient of the prestigious US Fulbright scholarship. He also holds the certification of Microelectromechanical Systems (MEMS) from the Georgia Institute of Technology. Dr. Usman is involved with the academic research and development for last fifteen years with teaching and research experience in Renewable Energy, Power Electronics, Biosensors, Silicon Photonics, Integrated Optics, and Semiconductor Packaging. He has been involved in multiple research grants and projects during his Ph.D. with various US funding agencies primarily National Science Foundation (NSF), DARPA, US Naval Research, and National Institute of Health (NIH). Dr. Usman has also worked as a visiting researcher at Korean Advanced Institute of Science and Technology (KAIST). He is a Senior Member of IEEE and a member of the IEEE Power Electronics Society, Photonics Society, Power and Energy Society, and Engineering in Medicine and Biology Society. He is also a life member of the Pakistan Engineering Council (PEC).
Allama Iqbal Medical College, Lahore
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Dr. Amjad Zafar holds a Fellowship in Medical Oncology from Pakistan and has received specialized training in Bone Marrow Transplantation from Germany. He is currently working as a Community Oncologist in Lahore, Pakistan. He holds the position of Assistant Professor at Jinnah Hospital, Lahore, and serves as a visiting consultant at several hospitals, including PKLI and Hameed Latif. Dr. Zafar has numerous publications at both national and international levels, with specific research interests in Hepatocellular Carcinoma (HCC), Gastrointestinal (GI) Oncology, Breast Cancer, and Leukemia/Lymphomas.
Punjab Safe Cities Authority (PSCA)
Robotics is a cutting edge technology that is changing the future of the world. The world of tomorrow cannot be imagined without robots as its integral part. Pakistan should not stay behind in this race and use robotics to solve its problems. Agriculture is the backbone of the country. Yet it has degraded over the years compared to its neighbors. AI has the potential to help humans in improving agricultural yields from their farms. We have been running several projects using AI and robots in different areas of agriculture.
Dr. Yasir Niaz Khan obtained his Ph.D. at the University of Tubingen in 2013. During his Ph.D. he conducted research on detection of terrain (ground surfaces) using a camera mounted on a flying and a ground robot. Upon completing his graduate studies, Dr. Khan started teaching robotics at FAST-NU, Lahore, Pakistan. He started a new robotics Lab at FAST-NU for robotics students to promote robotics in Pakistan. Dr. Khan supervised many national and international level robotic events held at FAST-NU where professors and students from different universities presented their works in robotics field. Dr. Khan joined The University of Lahore, the largest private sector university in Pakistan, and has started to extend his work further. He is now Director of Research Group on Robotics and AI that he established at the university. He has been involved in multiple projects on Agricultural Automation funded by DAAD Germany. He has been working as a consultant with Engro Corp, etc. He worked as a Software Architect AI in 10Pearls for about an year. Currently he is working at Chief Technological Officer at Punjab Safe Cities Authority and as a Senior Research Fellow at LUMS.
Superior University, Lahore
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