GIKI, Topi, Pakistan | December 02-04, 2025

invited speakers

Title: Artificial Intelligence (AI) and the Fourth Industrial Revolution (4IR): Exploring Social and Ethical Implications
Dr. Ahmed S Khan
Professor of Electrical Engineering, Fulbright Specialist Scholar
Ex. Dean of the College of Engineering & Information Sciences
DeVry University, Addison, Illinois, USA
Abstract:
The emerging technologies of the Fourth Industrial Revolution (4IR) are reshaping the way we live, work, interact, and educate. Innovations such as Artificial Intelligence (AI), Big Data, the Internet of Things (IoT), Augmented Reality, Blockchain, Robotics, Drones, Nanotechnology, Genomics and Gene Editing, Quantum Computing, and Smart Manufacturing are driving rapid transformation across every sector of society. Unlike previous industrial revolutions—where change unfolded over centuries or decades—4IR is accelerating at an unprecedented pace. The time required to reshape global systems is now measured in months, not years. This shift marks a dramatic departure from:
Dr. Ahmed S Khan

1st Industrial Revolution: Steam and water-powered mechanization (centuries)
2nd Industrial Revolution: Mass production and electrical power (multiple decades)
3rd Industrial Revolution: Electronics and IT (decades)
Among these technologies, Artificial Intelligence (AI) stands out as the most transformative force in human history. It is essential that today’s and tomorrow’s stakeholders—policymakers, educators, and leaders—are equipped not only with technical knowledge of AI, but also with a deep understanding of its social, ethical, and unintended consequences. This awareness is critical to guiding its responsible use, identifying its failures, and shaping a humane and visionary future.
The talk will explore AI’s intended and unintended consequences through the following critical domains:
1. Ethics: Ensuring AI development aligns with moral principles and avoids reinforcing biases.
2. Privacy: Protecting user data and maintaining confidentiality in AI systems.
3. Transparency: Making AI decision-making processes understandable and accountable.
4. Public Trust: Building informed public confidence in AI technologies.
5. Safety: Designing AI systems that are secure and minimize risks.
6. Legal Frameworks: Establishing regulations that keep pace with technological advancement.
Engaging with these domains is essential for all stakeholders to responsibly navigate the complexities of AI adoption—maximizing its benefits while minimizing its risks.
Speaker Biography:
Dr. Ahmed S. Khan is a Fulbright Specialist Scholar selected by U.S. Department of State’s Bureau of Educational and Cultural Affairs (ECA). Dr. Khan has more than 40 years of progressively responsible experience in instruction (online and onsite), applied research, curriculum development, program and institutional accreditation (ABET & NCA/HLC), management, and supervision of academic programs at DeVry University. Dr. Khan held many academic positions that include Senior Processor, Chair, and Dean of the College of Engineering & Information, DeVry University, Addison, Illinois, USA. Dr. Khan also served as the National Curriculum Manager at the national headquarters of DeVry University, where he provided leadership by supervising and managing curriculum development and implementation of BSEEt, MSEE & MBA online & onsite programs at 25 DeVry campuses located in the United States and Canada. Dr. Khan received an MSEE from Michigan Technological University, an MBA from Keller Graduate School of Management, and his Ph.D. from Colorado State University. His research interests are in the areas of Nanotechnology, New Teaching & Learning Techniques, and Social and Ethical Implications of Technology. He is the author of many educational papers and presentations. He has authored/co-authored many technical books, including the Science, Technology & Society (STS) series of books (used globally in the academic programs of more than 200 Universities) that include Technology and Society: Issues for the 21st Century & Beyond, and Nanotechnology: Ethical and Social Implications, to stimulate, inspire, and provoke awareness of technology’s impact on society. Dr. Khan is a life senior member of the Institute of Electrical and Electronics Engineering (IEEE), and a life member of American Society of Engineering Education (ASEE). Dr. Khan also served as program evaluator for the accreditation agency ABET.

Title: Securing the Edge: An AI-Driven Detection of Intrinsic Cyber Threats via Current-Profiling in IoT Networks
Dr. Uvais Qidwai
Associate Professor of Computer Engineering
Qatar University, Qatar
Abstract:
With the rapid proliferation of IoT and edge computing in critical infrastructures—ranging from agriculture to smart surveillance—the attack surface has expanded, and so have the stealth and sophistication of cyber threats. Traditional signature-based detection systems often fall short in resource-constrained environments, failing to detect subtle, hardware-level manipulations. This talk presents a novel intrusion detection approach that utilizes profiling the current consumption in real-time combined with AI-based classification techniques to identify and respond to hardware intrinsic cyberattacks.
Dr. Uvais Qidwai
The presented work is a funded grant from Qatar Research Development and Innovation Council (QRDI) and evaluates a subset of targeted attacks in the forms of hardware trojans or hardware intrinsic attacks. Those that have been successfully implemented as part of the project, while more are being encoded, include Covert Channel Attacks (CCA), Power Depletion Attacks (PDA), Denial-of-Service Attack (DoSA), and Man-in-the-Middle Attack (MIMA)—deployed on an experimental testbed of ESP32 microcontrollers based IoT nodes and a Raspberry Pi 5-based edge node. The AI-driven intrusion detection system (IDS), analyzes current profiles and sensor data transmitted via UDP protocol to detect anomalies using a suite of ML classifiers such as Ensemble

Learning, LDA, Decision Trees, k-NN, and SVM, for comparison and selection of best technique. The results demonstrate high detection accuracy and low false positive rates, validating the approach for practical deployment in real-time, mission-critical IoT environments. By deploying machine learning classifiers, including Ensemble Learning (Bagging and LPBoost), the system effectively classified cyberattacks such as Covert Channel Attack (CCA), Power Depletion Attack (PDA), Denial-of-Service Attack (DoSA), and Man-in-the-Middle Attack (MIMA). The classification results indicate that ensemble learning techniques (Bagging and LPBoost) provided the highest accuracy, with Bagging achieving 99.78% accuracy and LPBoost reaching 98.03% accuracy, demonstrating their robustness in real-time threat detection scenarios.
Speaker Biography:
Uvais Qidwai received his Ph.D(EE). from the University of Massachusetts–Dartmouth USA in 2001. He taught in the EECS Department at Tulane University in New Orleans USA as Assistant Professor, and was in-charge of the Robotics lab as well as a research member of Missile Defense Center, during June 2001 to June 2005. His current affiliation (since September 2005) is with the Department of Computer Science & Engineering at Qatar University, Qatar where he is Associate Professor of Computer Engineering at present. His research interests include Smart system design and AI-based embedded systems and techniques in Robotics applied to healthcare and industrial applications. He has participated in several government- and industry-funded projects in the United States, Saudi Arabia, Qatar, UAE, Singapore, Malaysia, and Pakistan. He has published over 150 papers in reputable journals and conference proceedings, and has been granted two US and one GCC patents.


Title: Shaping a Sustainable Future: Harnessing Laser-Driven Synthesis of Advanced Materials for Renewable Energy Generation, Energy Storage, and Green Hydrogen

Dr. M. A. Gondal
Professor of Physics
IRC-Hydrogen & Energy Storage and K.A.CARE Energy Research and Innovation Center King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia
Abstract:
The ability to tailor the properties of materials by modifying their size, structure, and composition is crucial for the development of functional materials. Nanoscale materials, in particular, exhibit unique physical, chemical, and optical characteristics that make them ideal building blocks for advanced applications. Our research group has developed a simple, environmentally friendly, and versatile method - Pulsed Laser Ablation in Liquids (PLAL) - to synthesize functional nanocomposite materials with tailored properties.
Dr. M. A. Gondal
The PLAL process involves the irradiation of precursor materials in a liquid medium with a pulsed laser beam, enabling precise control over particle size and structure through photo-induced fragmentation, chemical reactions, and defect engineering. This keynote speech will highlight our recent advances in the PLAL-based synthesis of advanced functional materials and their applications in sustainable energy and environmental remediation.

Selected examples from our research group's work will be presented, demonstrating the potential of this technique to drive innovation in these critical area.

*The author is thankful to KFUPM for supporting this work under project ##INHT2513


Title: Enabling the AI Revolution ⎼ Advancing Hybrid Packaging Technology for Next Generation Multi-Die Systems for AI-Chip Manufacturing
Dr. Khizar M. Bhutta
Abstract:
Hybrid packaging is fundamentally transforming the semiconductor industry, driven by the rapidly escalating demands of next-generation artificial intelligence (AI) chips. This invited keynote address will examine the pivotal role of advanced packaging technologies in addressing the limitations of conventional chip fabrication, thereby unlocking unprecedented levels of performance, integration, and functionality. The talk will first revisit the evolution from traditional packaging technology originally developed for high-power microelectronics applications such as WBG deep-UV photonic engines and high power modular electronics to today’s state-of-the-art hybrid bonding paradigm. The presentation will delve into the technical underpinnings of flip chip packaging technology, with an emphasis on the direct die-to-substrate interconnection via solder bump arrays, shortens interconnect paths, thereby reducing parasitic inductance and capacitance, mitigating signal propagation delays, and enhancing high-frequency signal integrity, capabilities essential to meeting the bandwidth and latency demands of AI-accelerated computing workloads. Its direct thermal path enables efficient heat dissipation, essential for managing the elevated power densities of AI processors.
Dr. Khizar M. Bhutta
Program Leader – Manufacturing & Apprenticeship Solutions
Kinexus Group, Benton Harbor, Michigan, USA 
Furthermore, flip chip packaging supports high I/O density for massive data throughput, with underfill materials enhancing long-term reliability by mitigating thermal and mechanical stresses on solder joints. The transition to hybrid flip-chip bonding enables ultra-fine interconnect pitches of 10 μm and below, a critical enabler for high-density, multi-die integration in modern AI systems. The presentation will explore recent innovations in hybrid packaging highlighting strategies for multi-die integration. Various architectural approaches for die stacking and co-location within a single package will be discussed, with emphasis on optimizing performance, power efficiency, and system-level form factor. Particular attention will be given to 2.5D and 3D multi-die packaging, where Through-Silicon Vias (TSVs) enable vertical and lateral integration of multiple dies, enhancing bandwidth, reducing power consumption, and minimizing footprint through dense chiplet integration on shared substrates or within vertically stacked configurations. This keynote will also address the challenges in advanced TSV packaging, including cost structures, thermal management, and process complexity. Ongoing R&D from leading industry and academic institutions will be highlighted, underscoring global advancements in micro- and nanoelectronics packaging integration and scaling. Finally, the presentation will highlight how AI is actively shaping packaging development itself through AI-driven co-optimization for chiplet placement and interconnect routing, and applications such as machine learning for enhanced process control in multi-die advanced flip-chip and hybrid bonding techniques. Attendees will leave with a comprehensive perspective on how hybrid packaging is enabling the future of AI hardware from cloud-scale datacenter accelerators to energy-efficient edge inference systems and how AI, in turn, is accelerating progress in the packaging domain.
Speaker Biography:
Driving innovation at the nexus of advanced manufacturing and emerging semiconductor technologies, Dr. Khizar M. Bhutta is a distinguished Innovation Director with over 15 years of experience spanning corporate R&D, high-tech manufacturing, and academic research. He has led complex, cross-sector initiatives that deliver scalable technologies, accelerate digital transformation, and strengthen industrial competitiveness.
Renowned for bridging strategic vision with deep technical execution, Dr. Khizar has consistently translated cutting-edge science into market-ready solutions advancing organizational growth and fostering innovation ecosystems across public-private partnerships. His core expertise includes innovation engineering, new product development, high-volume manufacturing, and large-scale program leadership. As Manufacturing and Apprenticeship Solution Program Leader at Kinexus Group, Dr. Bhutta drives Industry 4.0 integration by aligning emerging digital technologies with modern manufacturing practices. In collaboration with the Michigan Manufacturing Technology Center, Tooling U-SME, and Nanoridge Materials, he leads national efforts to expand smart manufacturing adoption and cultivate a sustainable semiconductor talent pipeline through innovative apprenticeship models. Dr. Khizar’s technical portfolio spans tactile and disruptive innovation, additive manufacturing, intellectual property strategy, and consumer-driven product design. He partners closely with C-suite leadership to convert complex capabilities into measurable business value. His innovations include micro- and nanoelectronic semiconductor devices, silicon photonics, wide bandgap semiconductors for AI-integrated sensing, functional nanomaterials, cold plasma therapeutics, and circular economy solutions for advanced manufacturing.
Earlier in his career, he launched several high-impact R&D programs, including the development of a high-purity germanium detector research facility at the University of South Dakota in partnership with The Sanford Underground Research Facility, and The Lawrence Berkeley National Laboratory, CA. He also served as Research Professor at the Center for Optoelectronics and Optical Communications at UNC Charlotte, and began his career in Silicon Valley as Lead Scientist, pioneering photonic devices and solid-state light engines for aerospace, biomedical, defense, and consumer applications. Dr. Khizar holds a Ph.D. and completed postdoctoral research in Optical Sciences and Engineering from the University of North Carolina, with a focused specialization in photonic architectures and reconfigurable semiconductor device platforms for high-performance optoelectronic applications. He is the inventor of more than 45 patents, author of over 100 scientific publications, and a frequent keynote speaker at global technology forums and industry symposia.