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  • Invited Speakers of CCCIS 2024

Prof. Sandeep Joshi, Manipal University Jaipur, India

Speech Title: Efficient and secure routing in mobile ad-hoc networks using Metaheuristics optimization

Abstract: A new trust generation mechanism for security, as it has become an essential issue during communication among mobile nodes in unfavourable conditions. The mobile node’s property is dynamic, so it isn’t easy to manage security policies. These difficulties prevent building multi-level security arrangements that accomplish both assurance and attractive network execution. The mutual authentication-based protocol helps the handshake between two nodes. After the secure connection, nodes can interchange the required information. We are a monitoring node that will maintain the access list of the authorized nodes. The monitoring node will keep the nodes’ list based on the Medium Access Control (MAC) address of nodes and digital signature key. The key is generated by combining the hash code of the MAC address with the variety of the user’s fingerprint file acting as a node. The combination of both will verify the entity. Secure Hash Algorithm (SHA) is a cryptographic hashing algorithm used to decide a specific bit of information’s integrity. In the proposed method, we used different types of keys with additional entropy to check the trust level of password security. Trust-based Ad hoc On-demand Distance Vector routing algorithm (TRU-AODV) was developed to achieve security and efficiency in the MANET.

Biography: Dr. Sandeep Joshi, A qualified academician with B.E., MTech., Ph.D. He is working as a professor at the Department of Computer Science & Engineering at Manipal University Jaipur (MUJ), Jaipur, India. He has a rich academic experience of 22+years along with administrative experience as Head of the department and Deputy Director -Society Connect.
He is a senior member of IEEE and a member of ACM. He has served as session chair of reputed conferences. He has organized many conferences and symposiums. He is serving as general chair for the ICCT (www.icct.co.in) and SpacSec (www.spacsec.com) conference series. Apart from that he has organized many faculty development programs on various emerging topics of Computer Science & Engineering.
He has served as guest editor of the special issue of IJCS (Scopus Index –Taylor & Francis). He secured the best paper award presented at the World Conference On Applied Sciences, Engineering and Technology (WCSET 2015) at GSST, Kumamoto University, Japan He has hosted the post of Keynote Speaker at many conferences, such as the 21st and 22nd International Conferences on Information and Systems at Jorge Basadre Grohmann National University, Tacna Peru and 1st Global Conference on Artificial Intelligence and Applications GCAIA 2020 at Jaipur, India.
He has presented and published more than 60 papers in reputed journals and conferences of international repute. He has reviewed many research papers for reputed journals and conferences. His research interest covers security, network, and cloud computing. He is well connected with societal work through various agencies and is very much concerned about the uplifting of society and a green environment.

Prof. Abhijit Sen, Kwantlen Polytechnic University, Canada

Speech Title: Generative AI for IoT: Opportunities and Challenges

Abstract: Designed for technical enthusiasts and professionals across diverse backgrounds, thispresentation aims to illuminate the transformative potential of Generative AI in shaping theInternet of Things (IoT) landscape. We will explore its applications, including optimizing energyefficiency, predictive maintenance, and secure device authentication, while also navigating thechallenges of privacy preservation and security considerations. This session promises to unveilexciting opportunities and complexities at the intersection of Generative AI and IoT, deliveringinsights for both seasoned experts and those venturing into these realms. The session willconclude with an interactive Q&A, fostering discussions on the distinctive opportunities andchallenges that Generative AI introduces in the IoT space.

Biography: Dr. Abhijit Sen is a Professor of Computing Science and Information Technology at KwantlenPolytechnic University in BC, Canada, holding a Ph.D. from McMaster University, an M.S. degreefrom the University of California, Berkeley, and a B.Tech in Electrical Engineering from the IndianInstitute of Technology, Kharagpur. With over 30 years of experience, Dr. Sen has played pivotalroles in organizations like Canadian Aviation Electronics and Microtel Pacific Research.
His international impact includes positions as a visiting professor at institutions in New Zealand,Germany, India, and China. Dr. Sen is a renowned keynote speaker at international conferences,showcasing thought leadership. He actively contributes to academia, serving as a reviewer andtechnical committee member for various conferences, along with editorial board roles forconference proceedings publications. As an external examiner, he evaluates Ph.D. theses atmultiple universities.
Dr. Sen's research interests encompass Wireless Networking, Security, RFID, ComputingEducation, Distributed Systems, DevOps, and Artificial Intelligence. Recognized for hisdedication, he received the Distinguished Teaching Award from Kwantlen Polytechnic University.A Life Member of IEEE, he has served in the Executive Committee of IEEE, Vancouver Chapter.His contributions have been recognized by the IEEE, Vancouver Chapter, highlighting hisunwavering commitment and individual contributions to the organization.

Prof. Ghulam Abbas, GIK Institute of Engineering Sciences and Technology, Pakistan

Speech Title: Physical Layer Security Analysis in 6G Vehicular Communication using Radio Frequency Fingerprinting
Abstract: The evolution of sixth-generation (6G) systems introduces new security challenges alongside enhanced features, guiding vehicular communication towards new dimensions. This paradigm shift necessitates adaptive and context-aware security protocols, paving the way for innovative solutions. Physical layer security, acknowledged for its low complexity, low delay, and adaptable nature, emerges as a competitive contender in this arena. This invited talk will delve into the realm of physical layer security, specifically focusing on the utilization of radio frequency fingerprinting (RF-FP) for location estimation. By exploring the conceptual underpinnings of RF-FP, the talk emphasizes its potential to enhance security controls. In-depth analysis of the proposed approach extends to examining its impact on secrecy capacity (SC) and secrecy outage probability (SOP) in the presence of multiple eavesdroppers over time. The talk will navigate through the intricacies of leveraging physical layer security to address the evolving security landscape of 6G vehicular communication. It will also explore how the incorporation of RF-FP for location estimation contributes to the adaptability, extensibility, and context-awareness of security schemes, promising a resilient and efficient security framework for the future of communication systems.

Biography: GHULAM ABBAS received the B.S. degree in computer science from University of Peshawar, Pakistan, in 2003, and the M.S. degree in distributed systems and the Ph.D. degree in computer networks from University of Liverpool, U.K., in 2005 and 2010, respectively. From 2006 to 2010, he was Research Associate with Liverpool Hope University, U.K., where he was associated with the Intelligent & Distributed Systems Laboratory. Since 2011, he has been with the Faculty of Computer Science & Engineering, GIK Institute of Engineering Sciences and Technology, Pakistan. He is currently working as a full Professor, Head of Cybersecurity and Software Engineering Departments, and Director ICT Academy. Dr. Abbas is a co-founding member of the Telecommunications and Networking (TeleCoN) Research Center at GIK Institute. He is a Fellow of the Institute of Science & Technology, U.K., a Fellow of the British Computer Society, and a Senior Member of the IEEE. His research interests include computer networks and wireless and mobile communications.

Assoc. Prof. Poompat Saengudomlert, Bangkok University, Thailand

Speech Title:Visible Light Communications with Recent Advances in Modulation Techniques

Abstract: This talk introduces visible light communications (VLC), its benefits compared to radio frequency (RF) based alternatives, and potential applications. Basic properties of VLC will be discussed, leading to requirements on signal modulation. Then, an overview of various modulation techniques will be given, including single-carrier and multi-carrier modulation techniques. Finally, various approaches to support light dimming during data transmissions for energy efficiency will be discussed.

Biography: Poompat Saengudomlert obtained the Ph.D. degree in Electrical Engineering and Computer Science from Massachusetts Institute of Technology, USA in 2002. From January 2005 to April 2013, he served as an Assistant and then Associate Professor in Telecommunications at Asian Institute of Technology, Thailand. Since May 2013, he has been serving as an Associate Professor in Telecommunication Engineering at BU-CROCCS (Bangkok University-Center of Research in Optoelectronics, Communications, and Computation Systems), Thailand. His research interest includes multi-carrier communication systems and visible light communications. In addition to basic research, he led several development projects whose aims are to create low-cost laboratory activities for the teaching of telecommunications in developing countries.

Assoc. Prof. Syed Mushhad M. Gilani, University of Agriculture, Pakistan

Speech Title: Blockchain and AI: The Future of Agriculture
Abstract: The rapidly increasing global population is raising environmental risk factors and challenges in agriculture, such as crop losses, unplanned production, severe temperatures, market fluctuations, and an increase in the world's food demand. The conventional techniques are insufficient to overcome these challenges. Therefore, integrating AI and Blockchain Technology can overcome these issues and enhance productivity. AI brings predictive analytics to agriculture, enabling data-driven decision-making. AI can analyze diverse datasets using machine learning algorithms encompassing weather patterns, soil conditions, crop health, and historical yield data. These advanced machine learning algorithms give accurate crop forecasting, disease detection, and optimized resource allocation and automate labor-intensive tasks such as planting, harvesting, and monitoring, reducing human error and labor costs. A practical solution for agricultural product sustainability, quality, and safety is blockchain technology. Blockchain technology addresses issues with trust, traceability, supply chain, and data integrity. Blockchain minimizes the need for intermediaries and distribution delays of any product and payment delays using rule-based smart contracts such as enforcing agreements between parties. Integrating blockchain and AI technology has incredible potential for increasing agricultural productivity.

Biography: Dr. Syed Mushhad Mustuzhar Gilani is an Associate Professor of the Department of Computer Science, an Associate Senior Tutor, a Postgraduate Research Advisor, and convener of the QEC committee and various other committees at the University of Agriculture Faisalabad. He was an Assistant Professor (Computer Sciences) / Research Advisor for Postgraduate Students at PMAS-Arid Agriculture University Rawalpindi from 2012 to 2022. He received his Ph.D. from the School of Computer Science at Chongqing University of Posts and Telecommunication, China.
He has published more than 60 papers in peer-reviewed international journals and conferences. He has successfully supervised postgraduate students. He has served as session chair of reputed conferences. He has reviewed many research papers for reputable journals and conferences. He received an excellent Speaker Award at (Ted Talk) Youth Festival 2017 of Chongqing University of Posts and Telecommunication, China. His research interests include Future Internet Architecture, Software Defined Wireless Networks, IoT, and Smart Environments.

Assoc. Prof. Moirangthem Marjit Singh, North Eastern Regional Institute of Science & Technology (NERIST),India

Speech Title: Machine Learning /Deep Learning -based Techniques for NIDs
Abstract: - This invited talk will focus on the use of Machine Learning (ML) and/or Deep Learning (DL) based techniques designed for Network Intrusion Detection Systems (NIDs). The talk will explore commonly used ML/DL techniques for NIDs highlighting issues and challenges. The talk will delve into elucidating the research landscape where ML/DL techniques are applied for NIDs. Overview of relevant problem domain and solution domain will also be discussed in this talk.

Biography: Dr. Moirangthem Marjit Singh is currently an Associate Professor in Computer Science & Engineering Department at North Eastern Regional Institute of Science & Technology (NERIST), Arunachal Pradesh,India. He received B.Tech. and M.Tech. in Computer Science & Engineering degrees from NERIST and was awarded Gold Medal for securing top position in M.Tech. He received his PhD (Engineering) degree in computer Science and Engineering from University of Kalyani, West Bengal,India. He was the Head of the Department of Computer Science and Engineering, NERIST during 2018 to 2022. He was also the founder Honorary Joint Secretary of the Institution of Engineers, Arunachal Pradesh State Centre, India during 2019-2021. Dr. Marjit is a Fellow of IETE New Delhi, India and Fellow of the Institutions of Engineers (India) and the senior member IEEE, USA. Dr. Marjit was honoured with “Academic Excellence Award” by Taylor’s University, Malaysia in recognition of his outstanding academic performance on 13 September 2023 at Taylor’s University in association International Conference on Evolutionary Artificial Intelligence (ICEAI 2023). He was awarded the IE(I) Young Engineers Award 2014–2015 from the Computer Engineering Division, Institution of Engineers, India. He received the Best Paper Awards at international conferences namely the ICEAI 2023(held at Taylors’ University, Malaysia) and the ICACCT 2016, (held at APIIT, India) published by springer.
Dr. Marjit secured First Position in X and Second Position in XII Examinations conducted by CBSE, New Delhi, India, amongst the candidates sent up from Jawahar Navodaya Vidyalayas (JNVs) of North Eastern region states of India, in 1995 and 1997, respectively. He was awarded the Gold Medal for getting top position in the M.Tech.(CSE) at NERIST in 2010 He has more than 20 years of teaching and research experience. He has published several research papers in journals and conferences of repute. He has organized/associated with several technical conferences held in India and abroad. His research interests include mobile adhoc networks, wireless sensor networks, network security, AI, machine learning, and deep learning.

Assoc. Prof. Chavis Srichan, Khon Kaen University, Thailand

Speech Title: 3D Graphene: From Nanosensors to Environmental Sensing and Mitigations
Abstract: This invited talk explores the versatile applications of 3D graphene, highlighting its role as aSurface Enhanced Raman Spectroscopic (SERS) substrate, a sensing electrode for arsenic (As III),and a biosensor for a protein marker associated with acute kidney injury. The presentation willdelve into the promising properties of 3D graphene and its practical use in real-world scenarios.Furthermore, the talk will discuss the environmental application of 3D graphene as a material forglyphosate removal, showcasing its potential impact in addressing environmental challenges. Theaudience can expect a comprehensive overview of the diverse applications and the excitingprospects of 3D graphene across various fields.

Biography: Chavis Srichan, D.Eng., M.Sc., B.Eng., worked on various fieldsincluding machine vision, artificial intelligence, graphene-basednanomaterials, biosensors, nanoelectronics, quantum informationprocessing, and IC design. He had 8-year contributions as areviewer for highly reputed journals. His work and study in Germany,supported by a DAAD-Siemens scholarship, involvedmagnetoresistance properties and developed a nowaday-usedautomatic defect detector. His doctoral work focused on aGraphene-based Surface-Enhanced Raman scattering substratetowards single molecule detection. His research areas also includenanomaterials, nanophotonics, biosensors, IC Design, andquantum information theory. In addition, he developed a telemedicine health kiosk, tested,and implemented to reduce national costs and mitigate airborne disease exposure, suchas SARS-CoV-2. Currently, he holds an Assistant Professor position at Khon KaenUniversity, Thailand. Notably, he attained international research funding from NIH (UnitedStates), ASEAN IVO (NICT, Japan), and DAAD-Siemens (Germany).

Assoc. Prof. Bambang Leo Handoko, Bina Nusantara University of Indonesia, Indonesia

Speech Title: Socio Technical System Model for Auditor Intention to Adopt Artificial Intelligence

Abstract: Artificial intelligence (AI) has entered almost all aspects of business, including auditors. AI can improve efficiency, accuracy, risk detection and more. However, despite the many benefits of AI for auditors, adoption of AI among auditors in Indonesia is still low. This is our basis for conducting research on auditor intention to adopt AI, analyzed using a socio-technical system theory approach. Our research is quantitative research, we use primary data obtained through distributing questionnaires to auditors who work in public accounting firms. We used non-probability sampling with a sampling technique using snowball sampling. We conduct data analysis uses structural equation modeling partial least squares (SEM PLS) analysis using SMARTPLS 4 software. The results of our data analysis find that the social subsystem, technical subsystem and environmental subsystem each have a significant influence on auditor intention to adopt artificial intelligence.

Biography: Bambang Leo Handoko, academics and practitioners in the field of accounting, specialty in Auditing. Experience as auditor in public accounting firm, internal auditor for corporation and auditor for securing vital objects of National Police Headquarters. He is an expert in financial audit, cryptocurrencies, financial technology, stock market and e-business. He has had many international publications in reputable journals and proceeding with high index from many citation and acknowledgement from international researchers. He had won a lot of research grant from institution and government. Currently work as Subject Content Coordinator Auditing in Accounting Department, School of Accounting, Bina Nusantara University of Indonesia. He also technical committee in many reputable journal and conference. He is also reviewer for many of Elsevier Journal and professional member of world class reputable research organization, Association of Computer Machinery (ACM).

Assoc. Prof. Dmitrii Kaplun, China University of Mining and Technology, China

Speech Title: Efficient FPGA-based implementation of different CNN architectures and transformers

Abstract: The purpose of this work was to reduce the inference time when implementing ResNet50, YoLO, BERT and ViT neural networks on FPGA. As a result of the analysis of the considered networks architectures, it was decided to divide the hardware blocks of computers (DPU - deep learning processing unit) for convolutional networks (YoLO, ResNet) and transformers (ViT and BERT). This decision was dictated by the fact that the main computational load in convolutional networks lies on the calculation of 2D convolution and in transformers - on the calculation of the product of matrices. Both operations require a large number of multipliers involved, and their joint implementation in one small DPU is not advisable. We implemented ResNet50, YoLO and transformers on a standard DPU from Xilinx, implemented ResNet50, YoLO and transformers on the designed DPU that was modified during our work. We compared accuracy and inference time for different implementations. We also tried to provide FPGA-based training for different architectures of neural networks. The work presents results on integer training. We were able to confirm that completely integer training in int8 is possible for simple networks.

Biography: KAPLUN DMITRII I. PhD (2009), Associate Professor (2015), Lead Researcher (2020) at Saint Petersburg Electrotechnical University “LETI” (Saint Petersburg, Russia), Full Professor (2023) at China University of Mining and Technology. In 2009 he defended his PhD thesis in digital signal processing at Saint Petersburg Electrotechnical University “LETI”. The current research and academic work are related with digital signal and image processing, embedded and reconfigurable systems, computer vision and machine learning. D. Kaplun regularly takes part in various interdisciplinary projects related to the use of computer vision and machine learning for biomedical data processing. The most substantial results are in the fields of digital signal and image processing, embedded systems and machine learning. Author of more than 100 papers in journals, including leading journals, and conference proceedings. He is an Associate/Guest Editor/Editorial Board Member such journals as Frontiers in Neuroinformatics, Industrial Artificial Intelligence, Scientific Reports..


Assoc. Prof. Mohammed M. Bait-Suwailam, Sultan Qaboos University, Oman

Speech Title: Role of Deep Learning Models for Performance Prediction of Metasurface Absorbers
Abstract: Metasurface absorbers have gained much attention recently due to their unique ability to take advantage of incoming electromagnetic waves based on the deployed structure’s design. The role of deep learning techniques in the design and prediction have been investigated in many engineering and science applications. However, the potential deployment of such techniques in the design and synthesis of renewable energy solutions based on engineered absorbers needs a revisit. In this talk, the basics behind deep learning techniques will be introduced. Furthermore, the role and integration of such techniques to aid in the optimal metasurface absorbers design will be explored. A case study comprising a selected metasurface structure will be numerically investigated. A summary of the findings and effectiveness of deep learning models in achieving optimal performance of metasurface energy absorbers will be drawn.

Biography: Mohammed M. Bait-Suwailam (Senior Member, IEEE) received the B.Eng. degree in Electrical and Computer Engineering from Sultan Qaboos University, Muscat, Oman, in 2001, the MSc. degree in electrical and computer engineering from Dalhousie University, Halifax, NS, Canada, in 2004, and the Ph.D. degree in Electrical and Computer Engineering from the University of Waterloo, in 2011. From 2018 to 2019, he spent his sabbatical research leave at the School of Electronic Engineering and Computer Science, Queen Mary University of London, London, U.K. He is currently an Associate Professor with the Department of Electrical and Computer Engineering, Sultan Qaboos University. He is also working as the Director of Communication and Information Research Center, Sultan Qaboos University. He has authored/co-authored more than 60 refereed journals and conference papers. His research interests include antenna theory and design, metamaterials, EMI/EMC, electromagnetic energy harvesting and flexible sensors for healthcare applications, deployment of artificial intelligence and remote sensing for food inspection and renewable energy solutions. Dr. M. Bait-Suwailam was the recipient of several scholarships and awards, including the Best Paper Award from The Research Council of Oman in 2017 and the Best Teacher Award from Sultan Qaboos University in 2015. He is also serving as an Associate Editor for IEEE Access and the Journal of Engineering Research.


Dr. Paulo Batista, University of Évora, Portugal

Speech Title: The Age of Information
Abstract: Following the Second World War an explosion in the quantity of documentation led to a dramatic change inArchiving, or the profession referred to as records managers/records management and archivists/archives.Starting in the 1980s, however, archivists in Quebec began to make great progress by changing their approachand looking at the entire documentary cycle from current to definitive information. Carol Couture and JeanYves Rousseau made a crucial contribution towards the understanding of the Three Age Theory that viewedArchiving as an integrated discipline centered on a structural understanding of archives. In 1994, their workLes Fondements de la Discipline Archivistique, presented a new interpretation of Theodore Schellenberg'sThree Age Theory. They called attention to the fact that the three phases of archival documents are notseparate but, on the contrary, integrated. They argued that these three stages can even be looked at in asegmented way, provided the union between them is ensured. Their great innovation relative toSchellenberg's work lay, precisely, in critiquing the division and separation between the three ages of archivaldocuments. Couture and Rousseau thereby brought together all the phases of the lifecycle of records, fromproduction to dissemination, in opposition to the sterile distinction advocated by traditional archivists anddocument managers. In my opinion, however, the best approach to integrating information management isknown as records continuum, which places archives in a post-custodial, informational and scientific paradigm.This Australian concept arose in the 1990s amid the huge explosion of information, communicationtechnologies and new media. This context forced Information Science to redefine its object of study. Recordscontinuum is closely related to the integrated management model of Couture and Rousseau, while it carriestheir innovation further, perfecting it and replacing it with systemic dynamics and providing continuitybetween archives. In fact, records continuum means, literally, continuous management. It looks at the wholeprocess from the production of records to their final archiving. Otherwise, we cannot speak of continuousmanagement. That is why, when we speak of rigid archives – current, intermediate and definitive, thisapproach is more theoretical than practical. There is, in fact, no separation between these phases, even less sofrom the point of view of the value of documents. The traditional distinction between information withprobative and historical value ceases to exist. The information is simultaneous and is, in fact, the same.

Biography: Paulo Batista is PhD Researcher at CIDEHUS.UÉ-Interdisciplinary Center for History, Cultures andSocieties of the University of Évora, Portugal, where is the coordinator of the research group 2:Heritage and Literacies. Currently works as professor at the Iscte-IUL, in the Master inArchitecture and Visual Culture in Lisbon, and at the Autonomous University of Lisbon, where iscoordinator and professor of the Postgraduate in Promotion and Cultural and EducationalDynamization of Archives and Libraries, and the Postgraduate in Architectural Archives.
He has lectured in the Master in Information Science and Documentation at Universidade NOVAde Lisboa (UNL) and has held senior technician positions at the Portuguese Institute of CulturalHeritage, the Portuguese Institute of Architectural Heritage, and the Torre do Tombo Archives.He has also worked as researcher at the Center for the Study of History and Ancient Cartographyof the Institute of Tropical Scientific Research.
Paulo Batista holds a Ph.D. in Documentation (University of Alcalá, Madrid-UAH), a Master inInformation Science and Documentation - Archival Studies (UNL). As part of his doctorate he alsoreceived a Diploma of Advanced Studies in Bibliography and Documentation Retrospective inHumanities (UAH), and a Master in Documentation (UAH). He also holds a postgraduate degree inInformation Society Law (University of Lisbon) and Information and Documentation Science -Librarianship and Archival Studies (UNL), and a specialization in Good Practices in PatrimonialManagement (UNL) and Information Science and Documentation - Archival Studies (UNL). Heholds an undergraduate degree in History (University of Lisbon).
Paulo Batista is author of a number of books and about 80 papers published in internationaljournals and conference proceedings. He was also keynote speaker and invited speaker at variousinternational conferences (Argentina, Brazil, China, Ecuador, Egypt, India, Portugal, South Africa,South Korea, Thailand and Vietnam).

Dr. Abhimanyu Mukerji, Amazon.com, Inc., United States

Speech Title: Implementing Machine Learning Systems at Scale
Abstract: This talk will discuss the implementation of deep learning and machine learning systems at scale using distributed computing paradigms. We will focus on data storage, machine learning pipelines, tracking model runs and experimentation, and implementation using Spark.

Biography: Abhimanyu is a Senior Economist at Amazon working on dynamic causal models and causal machine learning. His prior research has used methods from machine learning, deep learning and natural language processing combined with econometric approaches to study problems in applied microeconomics and empirical corporate finance. He holds a PhD in financial economics from Stanford University.

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