Special Sessions

ICCIIoT-2024 invites eminent academicians, scientists, researchers, industrialists, technocrats, government representatives, social visionaries, and experts from all strata of society to work together for more meaningful and professional outcomes. The ICCIIoT 2024 team plans to hold workshops/special sessions on various areas of expertise, in any of the tracks based on related themes.

The Workshops/Special Sessions will be chaired by experts from different fields. The presentation of the papers will be scheduled on any day of the conference.

Session Tracks

Artificial Intelligence Innovations for Applications of Internet of Things (AII-AIoT)

Session Chair:
Dr. Thangavel Murugan; United Arab Emirates University, Al Ain, Abu Dhabi, United Arab Emirates.
Session Co-Chair:
Dr. Muthumanikandan V; Vellore Institute of Technology, Chennai, Tamilnadu, India.
Dr. Julius Fusic; Thiagarajar College of Engineering, Madurai, Tamilnadu, India.
e-Mail:
thangavelm@uaeu.ac.ae, muthumanikandan.v@vit.ac.in, sjf@tce.edu

Blockchain and its Multidisciplinary Applications

Session Chair:
Dr Naveed Ahmad; Prince Sultan University, Riyadh Saudi Arabia.
Session Co-Chair:
Dr. Sumaira Johar; Institute of Management Sciences, Peshawar, Pakistan.
Dr Afsheen Khalid; Institute of Management Sciences, Peshawar, Pakistan.
Miss Ayesha Khattak; Institute of Management Sciences, Peshawar, Pakistan.
e-Mail:
nahmed@psu.edu.pk, sumaira.johar@imsciences.edu.pk, afsheen.khalid@imsciences.edu.pk, ayesha.khattak@imsciences.edu.pk

Keynote Speaker

Prof. Dr. Md. Mamun Bin Ibne Reaz

Prof. Dr. Md. Mamun Bin Ibne Reaz is working as Dean and Professor at Independent University Bangladesh and has shown interest in being a Keynote Speaker for the conference to be hosted by the University of Engineering and Technology Peshawar in collaboration with Cardiff and Sinhgad Institutes. Prior, he served at the University Kebangsaan Malaysia in the Department of Electrical, Electronic, and Systems Engineering for many years. In 2020 he was ranked in the top 2 % of scientists in the world as per the release by Stanford. University.

ICCIIoT Keynote Speech

Title:

Integrating Modern Hardware and Machine Learning for Next-Generation Vehicular Systems

Synopsis

This keynote address explores the essential role of modern hardware in advancing Intelligent Vehicular Systems (IVS), including Connected and Autonomous Electric Vehicles (CAEVs) and Intelligent Transportation Systems (ITS), driven by machine learning. With a focus on the integration of advanced GPUs, CPUs, FPGAs, and hybrid devices within On-board Computational Units (OBCUs), the talk highlights their significant impact on applications such as energy-efficient operations, traffic management, vehicle control, real-time data processing, autonomous driving, traffic monitoring, and cooperative driving support.

Key topics include state-of-the-art hardware technologies, a performance evaluation framework for optimal machine learning deployment, and the challenges of dense user equipment and real-time communication needs. Attendees will gain insights into the latest innovations, best practices, and future directions essential for developing efficient, safe, and reliable IVS.

Session Chair:
Programme Director for BSc (Hons) Computer Science
Session Co-Chair:
Co-Director for the Centre for Engineering Research in Intelligent Sensors and Systems (CeRISS)
Personal Website:
Email:
IDamaj@cardiffmet.ac.uk
Vehicular Systems Image
Issam W. Damaj, PhD ME BE SMIEEE MASEE

Senior Lecturer in Computer Science

Dr. Aftab Khan

Title:

Harmony in Conversational AI: ChatGPT's Enabling Force, Creative Dilemmas, and the Imperative of Human Judgment in Computing

Dr. Aftab Khan, MIET

Dr. Aftab Khan, an Associate Professor at Allama Iqbal Open University (AIOU), Islamabad, Pakistan is a distinguished expert in the field computer science, specializing in digital image processing, machine learning, and remote sensing. Holding a Ph.D. from The University of Manchester, UK his research focuses on efficient methodologies for single-image blind deconvolution and deblurring. As a Postdoctoral Researcher at the University of Nottingham, UK he advanced computing technologies for detection and localisation of urban heat islands via remote sensing. Dr. Khan's research extends to various domains, including digital image compression and restoration, signal processing and machine learning. With a rich academic background and diverse professional experience, Dr. Khan has contributed significantly to the fields of computer science and information technology.

Vehicular Systems Image
Dr. Aftab Khan, MIET

Associate Professor at Allama Iqbal Open University

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