Name and Affiliation:
Prof. Dr. S. B. Goyal
Director, Faculty of Information Technology
City University, Petaling Jaya, 46100, MALAYSIA
Editor for international journals and Scopus-indexed books published by IEEE, Inderscience, IGI Global, and Springer

BIO: Professor Dr. S. B. Goyal has established a reputation in Computer Science & Engineering, earning his PhD from Banasthali University, Rajasthan, India in 2012. With over two decades of professional experience in various academic and administrative roles, he has become a key figure in integrating Industry Revolution (IR) 4.0 technologies, such as Big Data, Data Science, Artificial Intelligence, Blockchain, and Cloud Computing into the curricula of Malaysian universities. As a pioneer in this field, Dr. Goyal has actively participated as a speaker at prestigious events including Bloconomic 2019 and the World AI Show 2021. He is also a frequent panelist on IR 4.0 technologies at academic and industry forums. His editorial contributions are extensive, serving as a reviewer, guest editor, and editor for international journals and Scopus-indexed books published by IEEE, Inderscience, IGI Global, and Springer. He has contributed more than 300+ articles in SCIE/Scopus journals and conferences. An IEEE Senior Member since 2013, Dr. Goyal’s research spans several cutting-edge areas including Cyber Security, Internet of Things, and Data Mining. He is the holder of ten international patents and copyrights from Australia, Germany, Japan, and India, and his scholarly work has been widely recognized in Scopus/SCI journals and EI Comdex/Scopus-indexed conferences. Currently, Dr. Goyal is the Director of the Faculty of Information Technology at City University, Malaysia. His outstanding contributions have been acknowledged with multiple academic excellence awards at national and international levels.

Keynote Speaker Title: Blockchain and AI: Driving Innovations in Energy Efficiency and Sustainability

Abstract: On top of this conjunction, the energy industry is also experiencing an entirely new wave of innovation emerging from two powerful innovations in other sectors: blockchain and artificial intelligence (AI) for optimized energy efficiency. As the need for clean, sustainable and economical energy solutions increases so is the range of operating conditions required to make efficient use possible – these advanced technologies represent a potent solution. In this keynote, I will explore the convergence of AI and Blockchain, providing an overview of how these technologies are fundamentally changing the way energy is generated, managed, and consumed. Powered by blockchain and its decentralized, transparent ledger system, the integration of AI’s predictive and optimization capabilities provides a strong foundation for improving energy efficiency across multiple sectors. The potential applications are immense and revolutionary, from smart grids capable of handling electricity flow more wisely to decentralized energy markets that empower consumers and producers alike. This talk will explore concrete examples of Blockchain and AI applications in the field, potentially showing how these technologies can help reduce energy waste and enhance grid resilience in practice as we transition to renewable sources. Additionally, the keynote will discuss how these technologies support sustainability and how they can help reach global energy objectives, such as reducing carbon emissions and integrating renewable resources into current infrastructures. This presentation will ultimately give insights that demonstrate not only how Blockchain and AI are improving energy efficiency but also offer a trajectory toward a sustainable, resilient energy future. It will focus on the crucial role of cross-disciplinary collaboration and breakthrough approaches in advancing new energy paradigms.

Name and Affiliation:
Prof. Satish Kumar
Professor, Finance and Accounting Area
Indian Institute of Management Nagpur
Plot No. 1, Sector 20, MIHAN
Nagpur – 441108, Maharashtra
India

BIO: Dr. Satish Kumar is a Professor in the Finance and Accounting Area at Indian Institute of Management Nagpur (IIMN), India. He has over 18 years of teaching and research experience at management institutes of repute in India and abroad. Dr. Kumar has obtained his doctorate from the Indian Institute of Technology (IIT) Roorkee in 2012. He also qualified Junior Research Fellowship (JRF) in 2007. His teaching and research interests include Corporate Finance/Financial Management, Supply chain Finance, Small Business Finance, Corporate Governance, Consumer Economics, Systematic Literature review, and Bibliometric analysis.

He has over 200 research publications in his credit with work appearing in journals such as FT 50, A*, A category of ABDC journal ranking, and high impact factor journals. His research has appeared top tier journals such as Contemporary Accounting Research (FT 50), Review of Accounting Studies (FT50), International Journal of Research in Marketing (A*), Journal of Service Research (A*), British Journal of Management (A), Journal of Corporate Finance (A*), International Journal of Information Management (A*), Corporate Governance- An International Review (A) International Marketing Review (A), European Financial Management (A), Management International Review (A), Journal of Business Research (A), Financial Review(A), Journal of Small Business Management (A), Small Business Economics (A), International Journal of Advertising (A), European Journal of Finance (A), International Journal of Accounting Information System (A), Public Management Review(A), Small Group Research (A), Journal of Consumer Affairs (A), International Journal of Bank Management (A) and International Journal of Managerial Finance (A) amongst others.

Professor Kumar is the winner of the prestigious Basant Kumar Birla Distinguished Research Scholar Awards for Social Science and Management 2023 in the Government Institute Category with a cash prize of 3 Lakhs INR

Professor Kumar also won the prestigious ‘Careers360 2nd Faculty Research Award 2023 for the Most Outstanding Researcher in the country in Economics, Econometrics, and Finance. The award carries a citation and a Cash prize of 50,000 INR.

Besides the above, AIMS International awarded Professor Kumar “𝐀𝐈𝐌𝐒 𝐈𝐧𝐭𝐞𝐫𝐧𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐎𝐮𝐭𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡𝐞𝐫 𝐀𝐰𝐚𝐫𝐝” on March 1, 2024.

Keynote Speaker Title:

Abstract:

Name and Affiliation:
Dr. Umberto Berardi
Canada Research Chair in Building Science
Professor and BeTOP Lab Director
Toronto Metropolitan University, Ontario, Canada.
Member of the Royal Society of Canada (RSC)
President of the Canadian Acoustical Association
President of the International Association of Building Physics
Chair of IBPC 2024, Int. Building Physics Conference, July 2024. Toronto
BIO:
Keynote Speaker Title:
Abstract:

 

Name and Affiliation:
Dr Sudeep Tanwar, SMIEEE
Professor and Head | Department of Computer Science and Engineering | Institute of Technology, Nirma University, S-G Highway, Post-Chandlodia, Ahmedabad, 382481, Gujarat, India |
Visiting Professor | Jan Wyzykowski University, Polkowice, Poland | University of Pitesti, Pitesti, Romania I WSG University in Bydgoszcz, Poland.
Associate Editor, IJCS, Wiley (SCI, IF:2.047)
Associate Editor, Cyber Security and Applications, Elsevier, COMCOM, Elsevier, Security and Privacy (ESCI, SCOPUS), Wiley, Frontiers in Blockchain, Journal of Surveillance, Security and Safety, and Journal of Digital Transformation.

BIO: Sudeep Tanwar (Senior Member, IEEE) is working as a professor at the Nirma University, India. He is also a Visiting Professor with WSG University, Bydgoszczy, Poland, Jan Wyzykowski University, Poland, and the University of Pitesti, Romania. He is senior member of IEEE and also Vice Chair of IEEE Computer Society Gujarat Section. He received B.Tech in 2002 from Kurukshetra University, India, M.Tech (Honor’s) in 2009 from Guru Gobind Singh Indraprastha University, Delhi, India and Ph.D. in 2016 with specialization in Wireless Sensor Network. He has authored 05 books and edited 25 books, more than 400 technical articles, including top cited journals and conferences, such as IEEE TNSE, IEEE TVT, IEEE TII, IEEE TGCN, IEEE TCSC, IEEE IoTJ, IEEE NETWORKS, IEEE WCM, ICC, IWCMC, GLOBECOM, CITS, and INFOCOM. He initiated the research field of blockchain technology adoption in various verticals in the year 2017. His H-index as per Google Scholar and Scopus is 73 and 61, respectively. His research interests include blockchain technology, D2D communication, Deep Learning/machine Learning, wireless sensor networks, fog computing, smart grid, and the IoT. He is a member of the Technical Committee on Tactile Internet of IEEE Communication Society. Recently, He has been awarded cash prize of Rs, 50,000 for publishing papers with 5+ Impact factor and publication of books with Springer, IET & CRC under the scheme of “Faculty Awards and Incentives” of Nirma University for the year 2019-2020. He has been awarded the Best Research Paper Awards from IEEE SCIoT 2022, IEEE IWCMC-2021, IEEE ICCCA-2021, IEEE GLOBECOM 2018, IEEE ICC 2019, and Springer ICRIC-2019. He has won Dr KW Wong Annual Best Paper Prize (with 750 USD) for 2021 sponsored by Elsevier (publishers of JISA). He has served many international conferences as a member of the Organizing Committee, such as the Publication Chair for FTNCT-2020, ICCIC 2020, and WiMob2019, and a General Chair for IC4S 2019, 2020, 2021, 2022, ICCSDF 2020, FTNCT 2021. He is also serving the editorial boards of COMCOM-Elsevier, IJCS-Wiley, Cyber Security and Applications- Elsevier, Frontiers of blockchain, SPY, Wiley, IJMIS journal of Inderscience, JCCE, and JSSS. He is also leading the ST Research Laboratory, where group members are working on the latest cutting-edge technologies.

Keynote Speaker Title: Blockchain for 5G and Beyond Applications

Abstract: The convergence of Blockchain and Artificial Intelligence (AI) with 5G and beyond networks promises transformative advancements in telecommunications. This integration enhances security, trust, and efficiency in data management while optimizing network performance. Blockchain’s decentralized ledger and AI’s advanced analytics create a robust framework for managing 5G environments. This talk discusses opportunities including improved cybersecurity, efficient spectrum management, and autonomous network operations. Also, highlight challenges such as high computational demands, latency, interoperability, and standardization must be addressed. Discussed opportunities and challenges, providing insights into future research and practical implementations to achieve secure, intelligent, and efficient next-generation networks.

Name and Affiliation:
Dimitrios Karamanis
Professor
University of Patras
RES & Cool Environment Group
Seferi 2, 30100 Agrinio Greece
Associate Editor: Green Technologies & Sustainability (Elsevier/KeAi)
Editorial Board: Clean Energy and Sustainability (SCIEPublish)
Guest Editor: Energy & Buildings (Elsevier)

BIO: Professor of Alternative Energy Sources at the University of Patras leading the group of Renewable Energy Sources and Cool Environment. He studied Physics at the University of Ioannina (1986-1990) where he submitted his doctoral thesis (1990-1997). With Postdoctoral Fellowships at CEN Bordeaux (Marie Curie 1999-2001) and University of Ioannina (Marie Curie 2001-2002 and until 2008), Prof. Karamanis has thirty-five years of research experience in the fields of alternative energy sources with special emphasis on wind and solar energy utilization technologies in the last fifteen years. Participating in competitive National and International research programs as scientific coordinator and researcher, he has published over 110 scientific papers in scientific journals, patents and chapters in books with >3600 citations and h-index 38 (Scopus). He serves as Associate Editor of Green Technologies and Sustainability (Elsevier/KeAi) and Guest Editor of Energy & Building (Elsevier). Prof. Karamanis teaches courses on renewable energy sources, energy efficiency and RES applications in Departments of the Universities of Ioannina and Patras since 2006.

Keynote Speaker Title: Expanding BIPV City Deployment through intelligent knowledge systems against Urban and climate change-related temperature increases
Abstract:

Name and Affiliation:
Jaheer Mukthar KP
Assistant Professor
Department of Economics
Kristu Jayanti College, Autonomous, Bengaluru. India
Associate Editor:International Journal of Business Ethics and Governance
Associate Editor : Journal of Intelligence Technology and Innovation
Editorial Review Board Member: Journal of Organisational and End User Computing
Editorial Review Board Member: International Journal of Information Technologies and Systems Approach
Editorial Board Member: International Journal of E-Business Research (IJEBR),
International Journal of Cyber Behaviour, Psychology and Learning (IJCBPL)
International Journal of Asian Business and Information Management(IJBAIM)
Malaysian Journal of Consumer and Family Economics(MAJCAFE)
Associate Editor; Kristu Jayanti Journal of Management Sciences (KJMS)

BIO:
Keynote Speaker Title:
Abstract:

Name and Affiliation:
Mir Sayed Shah DANISH (Ph.D., MBA, CEng., SMIEEE, MIET)
Research and Innovation Chair (RIC)
Research and Education Promotion Association (REPA)
1401 21st St, Sacramento, CA 95811, USA

BIO: Dr. Danish Mir Sayed Shah is a recognized expert in engineering and technology with extensive experience in both academia and industry. Known for his clear and accessible communication style, he excels in transforming complex concepts into actionable goals. His multidisciplinary expertise spans energy, environment, business, and management, enabling him to offer integrated solutions that bridge the gap between academia and industry.
Since 2004, Dr. Danish has led numerous projects and research initiatives, serving as an assistant professor at Kabul University, the University of the Ryukyus, and Nagoya University. He founded the IEEE-Sustainable Energy and Intelligent Engineering Society (SEIES-PES & FRID joint chapter) and has collaborated with various organizations in roles such as urban electric power planner, technical advisor, and director.
A Chartered Engineer (CEng) and Senior Member of the IEEE, Dr. Danish holds multiple academic degrees, including a B.Sc., M.Sc., MBA, and two doctorates in Sustainable Energy and AI Applications in Energy Systems. He has published over 100 papers and authored several academic and technical books, focusing on areas like sustainable energy, hydrogen energy, smart cities, AI, and machine learning.

Keynote Speaker Title: The Ethics of Artificial Intelligence: Navigating the Grey Areas

Abstract: As Artificial Intelligence (AI) continues to advance rapidly, ethical considerations have become increasingly significant, particularly in navigating the complex and often ambiguous ethical grey areas. This paper explores these challenges by drawing on established guidelines from leading organizations, including the European Commission’s Ethics Guidelines for Trustworthy AI, the IEEE’s Ethically Aligned Design, the OECD’s AI Principles, and the Montreal Declaration for a Responsible Development of Artificial Intelligence. Through a synthesis of these authoritative sources, this paper examines critical ethical issues such as transparency, accountability, fairness, privacy, and human agency within AI systems. The analysis focuses on how these ethical principles can be applied to real-world AI applications, highlighting the ongoing efforts to develop responsible AI technologies that align with societal values. The paper concludes by proposing strategies for navigating the ethical grey areas in AI, emphasizing the need for continuous evaluation, robust governance frameworks, and interdisciplinary collaboration to ensure that AI developments contribute positively to society while minimizing potential harm.

Name and Affiliation:
Biju Baburajan
Huztle. AI, Longwood University, USA

BIO: Mr. Biju Baburajan brings over 20 years of experience in software engineering and more than a decade in technology leadership. With extensive experience in the U.S. healthcare systems and financial services sectors, he has helped companies build innovative solutions that drive growth and efficiency. As an expert in software engineering, product strategy, and artificial intelligence, he is currently focused on building a startup that develops an AI platform to digitalize small businesses, fostering innovation and operational efficiency. Biju holds a BS in Information Technology and is currently pursuing an MBA at Longwood University, USA. He has a personal interest in AI-based research, machine learning, data analytics, and creating solutions that address real-world challenges. He also dedicates time to mentoring startups focused on AI solutions and advocating for responsible AI.

Keynote Speaker Title:
Abstract:

Name and Affiliation:
Gokul Pandy
Accenture – Manager / IEEE Senior / Fellow IETE and BCS
USA

Short Biography: Gokul Pandy is an Application Development Manager at Accenture with over 16 years of experience in IT and automation. He specializes in Robotics Process Automation (RPA), Selenium Automation, and Agile methodologies, with a strong focus on optimizing business processes in healthcare and finance. Gokul has led multiple high-impact projects, including the development of advanced automation frameworks that have resulted in significant efficiency improvements and cost savings for clients. He holds an M.B.A. in Project Management and a B.E. in Electronics & Communication Engineering, and is an active senior member of IEEE and a Fellow Member of IETE and BCS along with Royal Fellow FRIOASD and SAS Eminent Fellow. His work has earned him recognition as a thought leader in intelligent automation, with numerous peer-reviewed publications and certifications in AWS and Pega Robotics.

Keynote Speaker Title: Advancing Robotic Process Automation: Leveraging AI and Machine Learning for Intelligent Business Operations

Abstract: Robotics Process Automation (RPA) is revolutionizing business operations by significantly enhancing efficiency, productivity, and operational excellence across various industries. This manuscript delivers a comprehensive review of recent advancements in RPA technologies and proposes a novel model designed to elevate RPA capabilities. Incorporating cutting-edge artificial intelligence (AI) techniques, advanced machine learning algorithms, and strategic integration frameworks, the proposed model aims to push RPA’s boundaries. The paper includes a detailed analysis of functionalities, implementation strategies, and expanded empirical validation through rigorous testing across multiple industries. Theoretical insights underpin the model’s design, offering a robust framework for its application. Limitations of current models are critically discussed, and future research directions are outlined to guide the next wave of RPA innovation. This study offers valuable guidance for practitioners and researchers aiming to advance RPA technology and its applications.

Niladri S Bose
Consulting Architect, Cloud & Hybrid Infrastructure
India
BIO: Niladri Bose is currently working with Kyndryl Pvt ltd as a consulting Architect in Cloud and Hybrid infrastructure. He received his Master of Engineering degree from the University of Texas at Tyler, USA in 2005. He has over 19 years of industry experience and has driven multiple strategic solutions for major clients in the industry and helped them in driving their application and infrastructure modernization. A versatile professional with subject knowledge on design, development and implementation of Business Intelligence, AI, Big Data & migration projects. He has been a member of IEEE since 2004 and had reviewed numerous research papers for various symposiums. His field of interest is mostly image processing, artificial intelligence and machine learning. He has also authored previous publications in IEEE. Currently in his job role he is helping various customers in application integration and orchestration using artificial intelligence.
Keynote Speaker Title:  GenAI – new lingo to Industries
Abstract: Artificial intelligence has been with researchers as early as 1950s and since then the technology has been advancing generations after generations. Earlier times artificial intelligence has been used to analyse and enhance images and the same has been done for speech and text recognitions. In the recent past with large data sets available for Data engineers the evolution of GenAI is witnessing the next iteration of emerging technology. This presentation will show the evolution of Artificial intelligence to Generative AI. A comparison between OpenAI, GenAI and Predictive AI to show how comparative GenAI is. In this pretext we would be discussing a few of the use cases for GenAI which is currently being practiced across various industries and how as Kyndryl we are helping our clients. Finally, the future for GenAI and what more can be achieved. We expect that this presentation will give our listeners an insight to GenAI as to where we are in the industry front and how we are helping our customers to achieve their digital performances. 

Name and Affiliation:
SHENSON JOSEPH
UNIVERSITY OF TEXAS TECH/IEEE SENIOR MEMBER
USA

BIO: Shenson Joseph is a distinguished AI researcher and data science expert. With expertise in Data Science, Analytics, and Artificial Intelligence, he has authored 2 books and authored more than 6 research papers. Shenson has judged over many national and international events and actively contributes to editorial boards and conferences. He has earned a master’s degree in Data Science and second master’s degree in Electrical & Computer Engineering. He is an IEEE senior member and associated with ACM, AAAI (association for the advancement of artificial intelligence) and IETE fellow member.

Keynote Speaker Title: INTERPLAY BETWEEN ARTIFICIAL INTELLIGENCE AND FOG COMPUTING
Abstract:

Name and Affiliation:
Shunli Wang
(Li, Chunmei)
Inner Mongolia University of Technology

BIO: Professor, Doctoral Supervisor, Executive Vice President of Smart Energy Storage Institute, Academic Dean of Electric Power College at Inner Mongolia University of Technology, Academician of Russian Academy of Natural Sciences, IET Fellow, Provincial Senior Overseas Talent, Tianfu Qingcheng Provincial Scientific and Technological Talent, Academic Leader of the National Electrical Safety and Quality Testing Center, Provincial Tianfu Talent, Academic and Technical Leader of China Science and Technology City, Top 2% Worldwide Scientist.

Keynote Speaker Title:
Abstract:

Name and Affiliation:
Vinitha Hannah Subburaj
West Texas A&M University
United States of America

BIO: Dr. Subburaj is the Associate Dean of the College of Engineering at West Texas A&M University (WTAMU), where she has been a faculty member since 2017. She earned her M.S. in Computer Science in 2010 and her Ph.D. in Computer Science in 2013, both from Texas Tech University. Before joining WTAMU, Dr. Subburaj served as an Assistant Professor in the Department of Computer Science at Baldwin Wallace University, Ohio.
With a strong passion for teaching software engineering and advocating for women in computing, Dr. Subburaj has published over 15 technical papers and authored textbook chapters. Her research interests span software specification languages, reliable software development, software security, automated software systems, and machine learning/AI. She has had papers in these areas and is actively pursuing research, including work on formal methods for grid data analysis using machine learning and studies on cyber-secure resilient micro-grids.
Dr. Subburaj has successfully secured and administered several grants aimed at advancing research in machine learning, AI, cybersecurity, formal specifications, and software engineering. Her STEM-focused grants have significantly contributed to creating inclusive educational environments for underrepresented minorities in the Texas Panhandle. Additionally, she plays a pivotal role in multi-institutional initiatives, strengthening cyberinfrastructure for computational and AI research. Her engagement with the Wagner-Peyser 7(b) grant program includes collaborations with local companies, developing targeted initiatives to empower traditionally underrepresented groups in specific occupations.

Keynote Speaker Title: AI & Intelligent Systems: Revolutionizing Smart Grids for Optimal Efficiency and Reliability
Abstract:

Name and Affiliation:
Dr. Saurav Dixit
Pro-Vice-Chancellor, Chitkara University, Rajpura, Punjab 140401, India
Keynote Speaker Title: Edge-Based LLMs for Decentralized Structural Health Monitoring in Civil Engineering
Abstract: Civil engineering developments are in boom due to the enhancement of global structures and real-estate flourishment around the world. The traditional stand-alone monitoring systems for civil engineering development face problems due to the tendency of bias and manipulation. Artificial intelligence (AI) on the other hand has opened a new horizon of smoothness in different engineering processes and also extends itself towards Large Language Model (LLM) to shape our smart future. The proposed research investigates the application of edge-based Large Language Models (LLMs) for decentralized Structural Health Monitoring (SHM) of civil engineering infrastructures. The study aims to enhance the current SHM frameworks by integrating LLMs with edge computing, enabling autonomous, real-time processing and analysis of sensor data distributed across structural components. By deploying LLMs on edge devices, the system can locally process vast amounts of heterogeneous data from accelerometers, strain gauges, and environmental sensors, facilitating early detection of structural anomalies without the need for centralized data processing. The research objectifies to focus on developing lightweight, resource-efficient LLM architectures optimized for edge environments, ensuring minimal latency and power consumption while maintaining high predictive accuracy. Additionally, the study will explore federated learning techniques to enable continuous model updates directly on edge devices, leveraging localized data to refine anomaly detection models without compromising data privacy or security. Furthermore, the decentralized approach will also address communication bottlenecks by reducing the dependency on cloud-based systems, enabling real-time decision-making even in bandwidth-constrained environments. The outcome of this research is expected to be a robust, scalable SHM system that enhances the resilience and longevity of critical infrastructure by providing timely and precise identification of structural issues, thereby enabling proactive maintenance and reducing the risk of catastrophic failures.

 

 

Sumitro Ghatak
Lead Data Scientist @IBM, Product Architect, IBM Inventor, IEEE Senior Member
USA
BIO: Mr. Sumitro Ghatak is currently working at IBM as a Lead Data Scientist and architect, invested in creating AI-enabled products and leading initiatives in the development of trustworthy AI systems, for one of their largest telecom clients. His experience, spanning over a decade, has been dedicated to developing and architecting efficient solutions that integrate AI technologies into business operations while ensuring ethical considerations and compliance with governance frameworks, for some of IBM’s major clients across India, Europe and the US, and helping them adopt intelligent ways to streamline and achieve their organizational goals. Mr. Ghatak’s scope of work and area of expertise lies at the intersection of natural language processing and HCI and mainly revolves around developing capable models to process natural language and further utilize the potential of foundation models and LLMs to generate significant insights around various aspects of data and human-machine interaction. He holds an IEEE senior membership and has published in various IEEE conferences. His inventions beyond traditional AI boundaries, focussed on innovative AI solutions across industries, have resulted in the filing of multiple patents with the USPTO. He has been the recipient of multiple significant awards from IBM which include two major Invention Achievement awards, Service Excellence awards, and Eminence and Excellence awards. Apart from this, his research interest cuts across the areas of computer vision, reinforcement learning, causal inference, and intelligent knowledge systems. He has conducted Python programming language and machine learning enablement sessions, for a wide variety of audiences within the organization and has also been involved in developing an AI curriculum for employee upskill programs within IBM, along with contributions to various industrial whitepapers on solutions for intelligent virtual agents. Before joining IBM, Mr. Ghatak received his B.Tech in Computer Science and Engineering at the West Bengal University of Technology, India, with his bachelor’s thesis “Development of a keyboardless social networking website for visually impaired” getting published in the IEEE Global Humanitarian Technology Conference – SAS
Keynote Speaker Title: TBA
Abstract: TBA

 

 

Guda Ramachandra Kaladhara Sarma
Director of Global Enterprise AI
India
BIO: Ram is currently serving as a Director in Enterprise AI (Generative AI) in India. With an impressive 15 years of industry experience, Ram has developed extensive expertise in building solutions, practices, and teams within the AI/ML/DL domain.
Ram’s scholarly contributions are significant, with over 20 research papers published in prestigious journals such as IEEE and Springer, establishing his reputation in artificial intelligence and advanced computing. He has also shared his insights at renowned global AI summits, including the NVIDIA GTC AI conference and Intel AI Summit.
In his previous roles, Ram has led strategic AI/ML solutions in customer and business analytics across various industries. His distinguished tenure at HCLTech, L&T Infotech, and IBM research firms has provided him with invaluable leadership experience, particularly in driving AI strategy and implementing ML/DL solutions for prominent clients.
Ram’s passion for technological advancement is deeply rooted in his Master’s engineering background and his involvement in the Advanced Analytics Expert track of the Indian Statistical Institute (ISI). Additionally, he has been instrumental in mentoring and guiding teams, fostering innovation, and driving digital transformation initiatives.
Keynote Speaker Title: Decentralized Intelligence: Federated Learning Meets Edge Computing
Abstract: TBA

 

Mr: Bongumsa Mendu
(I) National Transmission Company South Africa SOC Ltd and (II) University of South Africa (Independent contractor)
South Africa
BIO: BONGUMSA MENDU was born in Mount Ayliff, South Africa. He received his Master of Philosophy in Electrical Engineering and Electronics from University of Johannesburg in 2019. His major field of study is Electrical Engineering, and research interests include power reliability and quality of supply, asset management and maintenance, statistics and machine learning applications in power systems big data analysis, and smart cities and grid. He is currently working as Senior Technologist for National Transmission Company South Africa SOC Ltd with over 10 years industry experience in maintenance and operations. He also work as an independent contractor with the University of South Africa. Previous publications involvements include journals published in (Energy Reports and Przeglad Elektrotechniczny) and conference papers published in (IEEE). He is a senior member of South African Institute of Electrical Engineers (SAIEE), and currently serves as chairperson of smart cities chapter within the institution. He is registered as a Professional Engineer (Pr Eng) with Engineering Council of South Africa (ECSA). He was a 2022 SAIEE Keith Plowden Young Achiever Award Winner (most outstanding young achiever of the year in Electrical/Electronic engineering). Together with involved co-authors, received best paper award from 7th International Conference on Power and Energy Systems Engineering (CPESE 2020), 26-29 September 2020, Fukuoka, Japan. He is currently serving as peer reviewer in IEEE Transactions on Power Systems, IET Generation, Transmission, and Distribution, and Elsevier under various journals.
Title of the Keynote Speech: Unlocking the Future of Power System Asset Management: Harnessing Predictive Analytics and Data-Driven Decision-Making for Sustainable Operations
Abstract: TBA

 

Mr: Deven Panchal (MS, BE, SMIEEE, FM Sigma Xi)
AT&T Labs and IEEE
USA
BIO: Deven Panchal (MS, BE, SMIEEE, FM Sigma Xi) is a highly accomplished and widely recognized expert in the fields of AI, Networking, Software and Open-Source.  He has helped build the World’s 1^st Open-Source AI marketplace, was involved with AT&T’s 1^st 5G VRAN/CRAN trials and has delivered solutions that today power many Global Telco Networks. His work has been widely cited around the world, has directly benefited millions of people around the world and has been featured in International media like Forbes, TechCrunch, Light Reading, TelecomTV etc. He is the author of multiple International publications, Open-source projects, and filed US patent applications. For spearheading the development of Industry-defining platforms like ONAP and Acumos AI, Deven has been the recipient of multiple ‘Best Paper’,  ‘Best Presenter’  awards, other important Industry awards in AI and Open Source. Deven is a Keynote speaker at many International conferences, has served as a TPC Member, Editorial Board Member, Reviewer, etc. for more than 15 International Conferences and Journals in the field of AI/ML and participates in many IEEE Standards committees in the areas of AI, Generative AI, Safe and Trustworthy AI.  For his research contributions that have led to groundbreaking advancements in AI democratization and network automation, Deven has been elected to Senior Member position of IEEE and Full Member position of Sigma Xi. He is currently with AT&T Labs, USA.  In the past Deven has been associated with Georgia Institute of Technology, USA and SAMEER Research Labs.
Keynote Speaker Title: Generative AI and LLMs meet 6G
Abstract: The advent of 6G technology promises to revolutionize wireless communications, offering unprecedented speeds, ultra-low latency, and massive connectivity. Simultaneously, the rapid advancement of Generative AI and Large Language Models (LLMs) is transforming various sectors of technology and industry. This presentation explores the convergence of these two cutting-edge fields, examining how Generative AI and LLMs can be leveraged to enhance and optimize 6G networks. We will discuss potential applications including intelligent network management, adaptive resource allocation, predictive maintenance, enhanced security measures, and personalized user experiences. The talk will also address challenges such as privacy concerns, computational requirements, and the need for explainable AI in critical communications infrastructure. By the end of this presentation, attendees will gain insights into the synergistic potential of Generative AI, LLMs, and 6G technology, and understand the implications for future wireless communication systems.

 

Mr: Chris Whittington
crossPORT IX
Canada
BIO: TBA
Keynote Speaker Title: Beyond Mechanical Determinism, The Evolution of Interconnected Intelligence
Abstract: By constructing intelligently interconnected systems we can cut more than 40% of energy and processing delays in the most modern computing platforms. A break from over 300 years of scientific tradition, this method is both simpler to construct and more powerful. By engineering systems that leverage interconnected processing capabilities, we eliminate many of the Von Newman challenges facing large system development; unlocking massively parallel and asynchronous computing. Beyond mechanical implementations of neomorphism, this organic approach truly unleashes core compute capabilities with instantaneous and scalable data exchange. Present designs demonstrate 1000X performance improvements in energy efficiency and latency over today’s leading data exchange platforms. It also reverses traditional data insecurity and introduces unique data privacy capabilities.

 

 

Prof. P. SUBRAMANIAN
Department of Renewable Energy Engineering
Tamil Nadu Agricultural University, Coimbatore
Tamil Nadu – 641 003, India
India
BIO: Having professional experience of more than 27 years in the field of Renewable Energy Engineering. Major professional domains are teaching, research, and technology dissemination in Renewable Energy Technologies. Having 7 design patents and developed five technologies, published more than 50 research papers, handling more than 40 subjects, conducted more than 200 training programs are some of my professional achievements during my career. Major areas of research are thermal gasification, biomethanation, biodiesel, bioethanol, biocrude and its downstream processes, carbonaceous value-added products (biographene, carbon molecular sieve, activated carbon, carbon dots, etc.) through biomass pyrolysis, solar energy technology, and energy management.
Keynote Speaker Title: Advancements and Scope for Intelligent Knowledge System in Renewable Energy Technologies.
Abstract: TBA

 

Mr. JATINKUMAR SONI
National Institute of Technology Delhi, NIT Delhi.
India
BIO: Mr. Jatin Soni is an emerging researcher in the field of Electrical Engineering, currently pursuing his Ph.D. part-time at the Institute of Technology, Nirma University. With a strong academic and professional background, he serves as a Technical Assistant at the National Institute of Technology (NIT) Delhi. He has previously worked as a Junior Lab Assistant at IIT Gandhinagar and as an Assistant Professor at Ganpat University, Mehsana. Mr. Soni holds a B.E. degree from Birla Vishvakarma Mahavidyalaya (BVM) Engineering College and an M.E. degree from Lukhdhirji Engineering College, Gujarat. His research interests include Power System Optimization, Power System Operation and Control, Optimization Techniques, and Hydro-Thermal Scheduling Problems. He has published numerous research papers in reputed journal on the topic of Economic Load Dispatch and soft computing techniques.
Keynote Speaker Title: Optimizing Economic Load Dispatch with Integrated Renewable Energy Sources Using Soft Computing Techniques
Abstract: The rapid integration of renewable energy sources (RES) like wind and solar into modern power systems poses significant challenges to traditional Economic Load Dispatch (ELD) methods. These challenges primarily arise from the inherent variability and unpredictability of renewable energy, necessitating more sophisticated and adaptive optimization techniques. In this context, soft computing approaches offer promising solutions by providing flexible and efficient methods to address the complexities of ELD in the presence of RES. This study focuses on the application of advanced soft computing techniques to optimize ELD while incorporating renewable energy sources. The techniques explored in this research include the Artificial Electric Field Algorithm (AEFA), Artificial Ecosystem-Based Optimization (AEO), Sine Cosine Algorithm (SCA), and Equilibrium Optimizer (EO). These algorithms have shown great potential in solving complex, nonlinear optimization problems in power systems with diverse and dynamic constraints. The Artificial Electric Field Algorithm (AEFA) is inspired by the electric field theory, where charged particles interact through electric forces. AEFA leverages the concept of Coulomb’s law to model the optimization process, making it highly effective in finding global optima in complex landscapes. It is particularly suited for handling the nonlinear and non-convex nature of the ELD problem when RES are involved. Artificial Ecosystem-Based Optimization (AEO) mimics the natural interactions within an ecosystem, such as symbiosis, predation, and competition, to search for optimal solutions. This algorithm is advantageous for ELD optimization as it balances exploration and exploitation, which is crucial in systems with high levels of uncertainty and variability introduced by renewable energy sources. The Sine Cosine Algorithm (SCA) is another powerful optimization technique that utilizes trigonometric functions to explore the search space efficiently. Its ability to dynamically adjust the search pattern makes it well-suited for tackling the fluctuating power outputs from wind and solar energy in the ELD problem. Finally, the Equilibrium Optimizer (EO) is inspired by the dynamic balance within physical systems and utilizes the concept of dynamic mass balance to reach equilibrium. EO is particularly effective in dealing with multi-objective optimization problems, such as minimizing cost and emissions in ELD while integrating RES. In this study, the performance of these soft computing techniques is evaluated on a power system model that includes both conventional power generation units and renewable energy sources. The objective is to minimize the total generation cost while adhering to system constraints, including power balance, generator limits, and renewable generation uncertainties. The algorithms are tested on benchmark systems, and their results are compared in terms of solution quality, convergence speed, and robustness. The findings demonstrate that the application of these advanced soft computing techniques provides significant improvements in solving the ELD problem with RES integration. The study not only highlights the individual strengths of AEFA, AEO, SCA, and EO but also suggests potential hybrid approaches that could further enhance the optimization process. This research contributes to the ongoing development of intelligent systems for power system operation and control, offering a pathway to more efficient and sustainable energy management in the era of increasing reliance on renewable energy. The insights gained from this study are expected to inform future strategies for optimizing power systems and support the broader adoption of renewable energy technologies.

 

Dr. Sasmita Bal
Alliance University, Bangalore
India
BIO: Dr. Sasmita Bal is an Associate Professor at Alliance University, Bangalore, with over 20 years of academic experience. She holds a Ph.D. in Mechanical Engineering from KIIT University and an M.Tech in Thermal Engineering from NIT Rourkela. She is also leading Institution’s innovation council (IIC) as convener. Apart from this she is serving the university IPR cell as member of advisory board.
Dr. Bal is a member of professional societies such as The Institution of Engineers (India) and the Institution of Engineering and Technology (IET). She actively participates in academic development, having coordinated faculty development programs and conferences, and serves as a reviewer for several journals in her field. Recently her journal Paper with ICE Publishing, UK has won a best-Paper award in nanomaterials and energy category.
Dr. Bal continues to contribute significantly to research and education in mechanical engineering and related fields. Dr. Bal’s research interests include microfluidics, jet and spray impingement, CFD analysis, electronic cooling technologies, composites, additive manufacturing, Energy optimization. She has published numerous research papers in reputed international journals and conferences, and holds two patents. As an experienced educator, Dr. Bal has taught a wide range of subjects at both undergraduate and postgraduate levels, including thermodynamics, fluid mechanics, heat transfer, and advanced topics like microfluidics and mechatronics.
Keynote Speaker Title: AI-Enabled Breakthroughs in Clean Energy Technologies.
Abstract: The ongoing energy transition necessitates a paradigm shift toward cleaner, more sustainable technologies. In this keynote speech, we are going to explore the profound impact of artificial intelligence (AI) in driving breakthroughs in clean energy. AI is not only optimizing existing renewable energy systems but also enabling novel approaches to energy generation, storage, and distribution. By implementing AI-driven data analytics, machine learning algorithms, and predictive modeling, significant advancements are witnessed in solar, wind, and energy storage technologies. These innovations are enhancing efficiency, reducing costs, and minimizing environmental impact.
The speech delves into real-world applications where AI is revolutionizing smart grid management, facilitating the integration of distributed energy resources, and improving energy forecasting. The ethical and societal implications of AI deployment in the energy sector will also be addressed, emphasizing the need for responsible innovation. This keynote aims to provide insights into the future of clean energy technologies, powered by AI, and to inspire collaboration across industries, academia, and policy-making to accelerate the global shift toward a sustainable energy future.

 

 

Dr. Balamurugan Mudhanai Sanjeevirayar
Vellore Institute of Technology
India
BIO: Dr. Bala Murugan MS is a Associate Professor at the Vellore Institute of Technology (VIT) in Chennai. He’s not just an alumnus but also a product of VIT’s rigorous academic culture, having earned his PhD from the institution. His specialization, “An Adaptive Geo-Localized Weather Forecasting Cyber Physical System,” is a testament to his innovative thinking. A major highlight of his doctoral research was the adept use of LoRaWAN for collecting weather data, showcasing his acumen in leveraging cutting-edge technology for practical applications.
Outside the realm of pure academics, Dr. Bala Murugan MS has carved a niche for himself in research and development. He currently heads the FG-AI4A study group and is a pivotal contributor to several key initiatives. Notably, he’s actively engaged in the Telecom Engineering Centre’s working groups, focusing on transformative projects like Smart City, Smart Village, and the Internet of Things (IoT) under the aegis of the Government of India.
While his credentials in technology and academia are impressive, his research interests are even more diverse. Medical electronics and quantum computing are two fields where Dr. Bala Murugan MS is currently channeling his energy, spearheading multiple projects that promise to shape the future.
His prolific nature is evident in his extensive list of publications. With over 25 research articles to his name in renowned journals, he has made significant contributions to the scientific community. Additionally, he holds two patents, underscoring his innovative spirit and ability to transform ideas into tangible solutions.
Among his creations, “MyVitals” stands out. This groundbreaking device is more than just a piece of technology; it’s a beacon of hope in challenging times. Designed to assess public health, MyVitals efficiently identifies vital signs that are indicative of the COVID-19 condition. It’s a reflection of Dr. Bala Murugan MS’s commitment not just to innovation, but to leveraging technology for the greater good. In summary, Dr. Bala Murugan MS, with his academic prowess and inventive mindset, is a true asset to VIT and the broader scientific community.
Keynote Speaker Title: AI-Driven Energy Optimization in Smart Grids: Application of Dimming Streetlight Systems for Enhanced Grid Efficiency
Abstract: TBA

 

 

Dr. Dehui Kong
KRS/Sanechips(State Key Laboratory of Mobile Network and Mobile Multimedia Technology)
China
BIO: Dr. Kong is currently a core researcher of State Key Laboratory of Mobile Network and Mobile Multimedia Technology. He is a senior expert IC architecture engineer in KRS（Sanechips）. He received the PhD degree in signal and information processing from the University of Electronic Science and Technology of China, Chengdu, China, in 2017. His research interests include AI algorithm and hardware accelerator, LLM applicaiton. He was responsible for the design of several chips, which have been shipped for over 50 million units. Some of their product are leading in world shipments, such as IPTV and PON CPE. By combining the optimization of demand-algorithm-architecture-design-backend together, he led his team to achieve an 80% reduction in power consumption without increasing area. In the field of AP, his team achieved a technological breakthrough in the cockpit field, and through chip architecture innovation, software-defined-chip was used to efficiently make ultra-multi-screen and high-definition images a reality in the car.
Keynote Speaker Title: The development from traditional AI to LLM and its acceleration in the view of SISR.
Abstract: TBA

 

 

Dr. Mo Zhang
Educational Testing Service
USA
BIO: Mo Zhang is a senior research scientist in the Research division at ETS. She holds a Ph.D. in educational psychology from Washington State University. Her scientific work at ETS focuses on writing research, AI scoring, STEM assessments, and test design and validation. She currently holds seven U.S. patents and has published extensively in the field of educational measurement.
Keynote Speaker Title: Leveraging AI Approaches and Process Data for Assessing Computer Programming Skills.
Abstract: TBA

 

Dr. Praveen Kumar Malik
School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab, India
India
BIO: Dr. Praveen Malik is a Professor in the School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab, India. He received his Ph.D. in with a specialization in Wireless Communication and Antenna Design. He has authored or coauthored more than 150 technical research papers published in leading journals and conferences from the IEEE, Elsevier, Springer, Wiley, etc. Some of his research findings are published in top-cited journals. He has also published ten edited/authored books with International Publishers. He has guided many students leading to M.E./M.Tech and guiding students leading to Ph.D. He is an Associate Editor of different Journals. His current interest includes Microstrip Antenna Design, MIMO, Vehicular Communication, and IoT. He was invited as Guest Editors/Editorial Board Members of many International Journals, invited for keynote Speaker in many International Conferences held in Asia and invited as Program Chair, Publications Chair, Publicity Chair, and Session Chair in many International Conferences. He has been granted two design patents and a few are in pipelines.
Keynote Speaker Title: Flexible antennas for IoT and next-generation communication systems.
Abstract: The next generation communication networks would transform not only the way people communicate, but also how they access physical entities. Conventional solutions cannot fully realize dense, diverse and heterogeneous dimensions expected in unified connectivity of “things” over the “Internet” (IoT). At the same time, emerging wireless communication networks improvement in spectrum availability, ubiquitous connectivity, overall throughput and energy efficiency. However, to encompass the dynamics of human-centric and machine-centric communication, it is important to explore wireless technologies for flexibility and scalability. Flexible systems are quickly advancing and have the potential to transform and improve many facets of life. A wide variety of applications, including biological sensors, WBANs, and IoT, can be supported by flexible technology in terms of wearable devices. The flexible antennas are used in many wearable devices as smart glasses, fitness bands, activity trackers, body monitor devices, smart watches, and many fashion electronics devices which are now an integral part of the next generation communication system and IoT applications. These antennas are widely used for on-body and off-body communication, as a wearable sensor, RFID, in wireless body area network (WBAN), and for ingestible and implantable applications. Flexible antennas can be fabricated with silver-nanoparticle inks, thin glasses, textile materials, metal foils, conductive polymers, graphene, plastics, or polymer substrates.

Prof. R.KANTHAVEL
School of Electrical and Communication Engineering, PNG University of Technology
Papua New Guinea
BIO: Prof. Dr. R. Kanthavel has been in the academic and administrative domain for the last 27 years, along with proven teaching and rich research experience. He has held various academic and administrative leadership positions, such as Professor, Dean, Research Dean for Computing Sciences, Head of the Institution, and Dean of the School of Computing and Digital Initiatives in globally renowned public universities. He has published 10 engineering books, 23 book chapters, 82 Scopus-indexed journals, and 32 SCI-indexed journals. He has supervised 32 PG students and 11 Ph.D. scholars so far. He has also published more than 100 papers at refereed international conferences. His fields of interest are artificial intelligence, machine learning, deep learning, predictive analysis technologies, high-performance communication networks, the Internet of Things, cognitive radio, data science, computer graphics, big data, cloud computing, mobile security, security management, information systems, and cryptography. He has completed nine major government-funded research projects in India and seven major research projects in the Kingdom of Saudi Arabia. In addition, he has served as the editor for several chapter books, including Computer-Assisted Learning for Engaging Varying Aptitudes: From Theory to Practice, published by IGI Global Publisher in the USA in 2022; Internet of Behavior’s (IoB), published by CRC Press in the UK in 2022; AI Techniques for Wireless Communication Networking, published by CRC Press in the UK in 2022; Springer Nature in 2024; and Hyper Personalization: Exploring the Next Frontier in Customer Experience using AI and Real-Time Data, published by Wiley Scrivener in 2024. Currently, he is working as a full professor of computer engineering at PNG University of Technology, Lae, Papua New Guinea.
Keynote Speaker Title: AI in Environmental Monitoring Analysis – An Exploration.
Abstract: Artificial intelligence is described as a form of intelligence manifested by systems. More specifically, through those processes, such as supervised and unsupervised learning, and reinforcement required aspects for engineering applications to be sustainable all systems in real-time are performed by computer systems. This abstract is delineating the various aspects of AI in environmental monitoring. To this extent, AI and intelligent systems are applying a number of leading techniques in the effort to enhance environmental monitoring. Real-time data collection and analysis allow AI-powered sensors and IoT devices to continuously collect environmental data in relation to temperature, humidity, and air and water quality. Real-time AI systems analyze data in regard to trends, changes, and actionable insights that may be drawn. Predictive analytics powered by artificial intelligence can predict potential risks and determine environmental trends using historical and current data. In this regard, machine learning models may be further developed to predict episodes of water contamination or air pollution for proper resource allocation and prevention. With the strengthening of artificial intelligence, enhanced remote sensing will be able to analyze vast amounts of data and images, thereby extending capabilities to function beyond current satellite- and drone-based remote sensing. It can provide leading measures of the natural environment changes, deforestation, and city expansions using computer vision and deep learning. AI systems in Pollution Detection and Management track the dispersion pattern to identify the sources of pollution, with deep analysis of data gained from air quality monitors among other sources. Such focused actions in dealing with water and air pollutant handling turn out to be easier. These may be used in tracking animal populations and behaviors under wildlife monitoring and conservation. It aids in better conservation strategies, species monitoring, localization of poaching acts, and habitat conditions using the technologies of image recognition and the appraisal of sounds. There is an improvement in climate models and their simulation that is greatly improved by the integration of complex data sets and raises the prediction through AI in modeling climate. Approaches based on machine learning allow simulation of the scenarios of climate change in a more accurate way, an understanding of the underlying implications of climate change better, and an assessment of better mitigation solutions. Artificial intelligence in waste management analyzes trends in refuse generation and sortation improvements for a smart and effective collection process and recycled operation. Such intelligent systems can reduce most of their impact on the environment by automatic segregation of trash and monitoring the conditions within the landfill. That AI system helps predict disasters and their response by creating a forecast based on data about the environment, whether hurricanes, wildfires, or floods.