Abstract

This keynote explores how ATMOS Global™ is pioneering a new meta‑cognitive “operating system” that builds trust and inspires action for executive leadership. Conventional leadership models built for slower, centralized and largely human-mediated decision cycles, are increasingly misaligned (the Great Divergence) with a world where agentic hyperevolution and AI‑enabled perception, prediction and action occur at the network’s edge in milliseconds.

Drawing on insights from neuroscience and systems thinking, ATMOS Global™’ s breakthrough Operating System, ATMOS Global Panawareness Meta‑Cognitive Operating System for Executive Leadership™ (panawareness.ai) reframes the executive’s role from top‑down controller to expert architect and steward of distributed human-AI cognition, designed to inspire, scale and succeed. The keynote will showcase advanced leadership practices that executives can apply to “rewire” how they think, feel and decide in partnership with intelligent machines, to create value, positive impact and strategic advantage.

Ultimately, the session positions meta-cognition as the decisive lever of competitive advantage in the age of edge AI complexity, and challenges leaders to deliberately evolve their internal architecture before attempting to transform the external one.

Biography

Dr Orestis D. Valianatos is the Global President and CEO of ATMOS Global Pty Ltd (ATMOS Global ™), a highly accredited and accomplished professional company director, an astute investor in the capital markets, an established innovator, a role model, a visionary thinker with a diverse portfolio of formal qualifications (BSc, MSc, PhD in Atmospheric Physics, Climate & Sustainability, Master of Business Administration, Professional Doctorate in International Business and Sustainability, Corporate Governance training as a Professional Board Director, and soon a Diploma of Finance), experience, unique insight and influential global perspective across multiple domains including artificial intellignce, leadership, strategy and innovation, sustainability, ESG, climate-tech, thematic and sustainable investing. Entrepreneur and agent of change, he has authored more than 50 ground-breaking international research papers as a subject matter expert working in partnership with senior personnel from government departments, universities and major private clients from the mining, manufacturing and energy & utilities sectors.

Abstract

A time-dependent queueing system containing two stages in tandem has been considered. Carriers carry jobs by bulks of various sizes and arrive at the first stage according to a Poisson distribution. There is a possibility of balking and, hence, jobs attend with some probability at an infinite size buffer, located at the entrance of the first stage. As the jobs attend, they will be placed randomly in the buffer with some type of identification for later to be served based on that order, that is, first-come – first-served rule. For jobs to be served by batches, they will be grouped with a minimum and a maximum limit and will be moved to be served by a single server. However, before being served, jobs must go through a procedure that causes service to be performed with delay. There is also a possibility of a server breakdown that would require it to be repaired, which will affect arrivals, that cause another possible delay in service. As a batch exits the first stage, some may leave the system at that point with some probability. The rest of the batch attend an infinite buffer at the second stage with the complement of the probability of leaving. The attending batches will be numbered, and they will move to service as they are. As can be anticipated in a time-dependent case, the system is a complicated one. Nonetheless, the time-dependent probability generating function for the number of jobs at each stage and the system as a whole, as well as the first and the second moments are found. The probability generation function and convolution of exponential functions and generating functions have been used to obtain moments for each stage as well as the system. Several special cases have been illustrated to show the validity of the results.

Biography

Aliakbar Montazer Haghighi is a Regent Professor & Professor and former Head of the Mathematics Department at Prairie View A&M University, Texas, USA. He received his Ph.D. in Probability and Statistics from Case Western Reserve University, Cleveland, Ohio, USA, both his BA and MA in Mathematics from San Francisco State University, California, USA. His research publications, in probability, statistics, stochastic processes, queueing theory, and fuzzy set theory, are extensive and some are partially included in his mathematics books, a book-chapter, and lecture notes. He is the Co-Founder (2004) and part of the Editors-in-Chief Team of Application and Applied Mathematics: An International Journal (AAM).

Abstract

This talk will focus on the description of surface functionalized ultrafine CoFe2O4 nanoparticles (NPs), with mean diameter ~ 5 nm. The investigated properties include DC magnetization and AC susceptibility measurements over the temperature range of 4 – 400 K. All evaluated NPs present the same CoFe2O4 core, with different molecular surface coatings, increasing gradually the number of carbon atoms in the coating layer, in the following list: glycine (C2H5NO2), alanine (C3H7NO2), aminobutanoic acid (C4H9NO2), aminohexanoic acid (C6H13NO2), and aminododecanoic acid (C12H25NO2). Importantly, samples were intentionally fabricated in order to modulate the core-core magnetic dipolar interaction, as the thickness of the coating layer increases with the number of carbon atoms in the coating molecule. The magnetic data of the uncoated CoFe2O4 NPs it is also presented for comparison. All investigated CoFe2O4 NPs (coated and uncoated) are in magnetically blocked state at room temperature as evidenced by ZFC/FC measurements and the presence of hysteresis with ~700 Oe coercivity. Low temperature magnetization scans show slightly constricted hysteresis loops with coercivity decreasing systematically while the number of carbon atoms in the coating molecule decreases, possibly resulting from differences in magnetic dipole coupling between NPs. Large thermomagnetic irreversibility, slow monotonic increase in the FC magnetization and non-saturation of the magnetization give evidence for the cluster glass (CG) nature in the CoFe2O4 NPs. The out of phase part of the AC susceptibility for all samples shows a clear frequency dependent hump which is analyzed to distinguish superparamagnetic (SPM), cluster glass (CG) and spin glass (SG) behavior by using Néel-Arrhennius, Vogel-Fulcher, and power law fittings.

Biography

Professor Paulo César De Morais, PhD, was full Professor of Physics at the University of Brasilia (UnB) – Brazil up to 2013. Appointed as UnB’s (Brazil) Emeritus Professor (2014); Visiting Professor at the Huazhong University of Science and Technology (HUST) – China (2012-2015); Distinguished Professor at the Anhui University (AHU) – China (2016-2019); Full Professor at the Catholic University of Brasília (CUB) – Brazil (2018); CNPq-1A Research Fellow since 2010; 2007 Master Research Prize from UnB. He held two-years (1987-1988) post-doc position with Bell Communications Research, New Jersey – USA and received his Doctoral degree in Solid State Physics (1986) from the Federal University of Minas Gerais (UFMG) – Brazil. With more than 14,500 citations, He has published more than 500 papers (Web of Science), presented more than 250 invited talks worldwide (35 countries) and filed 16 patents.

Abstract

In the face of escalating cyber threats, the fusion of artificial intelligence (AI) with cybersecurity strategies has become a cornerstone for modern defense systems. This presentation, delivered by Dr. Farah Jemili, explores the pivotal role of generative AI in fortifying cybersecurity frameworks. As modern communication technologies generate vast amounts of data daily, the presentation addresses the pressing need to harness this data to safeguard Industry 4.0 infrastructures, which are increasingly vulnerable to cyber-attacks. With cyber-attack damages projected to reach $8 trillion in 2024 and escalate to $10.5 trillion by 2025, innovative solutions are essential.

The presentation outlines the current cybersecurity landscape, identifying key challenges such as data collection, storage, processing, and the accurate detection of cyber threats. It emphasizes the transformative potential of AI methodologies, including machine learning, deep learning, and generative learning, in developing robust intrusion detection systems and real-time threat response mechanisms.

A detailed examination of real-world AI applications in cybersecurity is provided, showcasing technologies like Cylance for malware prevention, AEG for automatic exploit generation, AI2 for predictive threat analysis, and IBM's Watson for IoT network analytics. The comparative study of various deep learning models highlights their distinct advantages and limitations in cybersecurity contexts.

Furthermore, the presentation discusses the integration of AI with other technological pillars such as cloud computing and big data, illustrating how these synergies enhance cybersecurity capabilities. The research contributes to understanding how AI can be leveraged to develop intelligent, adaptive, and resilient cybersecurity systems, ultimately aiming to mitigate the risks and impacts of cyber-attacks.

The presentation concludes with perspectives on future research directions and the evolving landscape of AI in cybersecurity, underscoring the critical role of continuous innovation and collaboration in this domain.

Biography

Farah JEMILI is an Associate Professor at the Higher Institute of Computer Science and Communication Technologies of Sousse (ISITCOM), Tunisia. She has completed her Ph.D. in 2010, from the National School of Computer Sciences (ENSI), Tunisia. She is a Scientific Referent at the Tunisian Agency of Evaluation and Accreditation (ATEA), and Internship Director at ISITCOM. She has been member of the Scientific Council of ISITCOM for 3 years (2011-2014), and Head of the Department of Computer Science at ISITCOM for 3 years (2017-2020). Her research interests include Artificial Intelligence, Cyber Security and Big Data Analysis. She served as a Reviewer for many international conferences and journals. She has published around 60 Research papers in international journals and conferences and has presented many invited and contributed Talks at international conferences.

Abstract

Multi-Agent Systems (MAS) represent a powerful paradigm in distributed artificial intelligence, where multiple autonomous agents interact to achieve individual or collective goals within a shared environment. The design of effective MAS hinges on robust mechanisms for collaboration, coordination, and conflict resolution, particularly in complex, dynamic, and resource-constrained domains. This work presents a comprehensive overview of the principles and design methodologies underlying collaborative and coordinated multi-agent architectures, emphasizing how agents communicate, negotiate, and adapt their behaviors to optimize system-level performance.

The study explores key coordination strategies, including task decomposition, role assignment, shared goals, and temporal synchronization, alongside formal interaction protocols such as contract-based coordination and negotiation models. Special attention is given to conflict detection and resolution mechanisms arising from resource contention, goal inconsistency, and communication ambiguity. Approaches such as negotiation, mediation, arbitration, and game-theoretic strategies are discussed to ensure fairness, efficiency, and system stability.

Furthermore, the abstract highlights the relevance of MAS design in real-world applications such as smart grids, autonomous traffic systems, supply chain optimization, cybersecurity, and collaborative AI assistants. By integrating learning-based techniques and adaptive decision-making, modern MAS can exhibit emergent intelligence and scalability while maintaining robustness in uncertain environments. Overall, this work underscores the importance of structured collaboration, efficient coordination, and principled conflict resolution in designing scalable, intelligent, and resilient multi-agent systems capable of addressing complex real-world challenges.

Biography

Dr.S.Balakrishnan is a Professor and Head of Department of Computer Science and Engineering, Aarupadai Veedu Institute of Technology, Vinayaka Mission’s Research Foundation (Deemed to be University), Paiyanoor, Chennai. He has 24 years of experience in teaching, research and administration. He has published over 39 books, 10 Book Chapters, 30 Technical articles in CSI Communications Magazine, 27 technical Blogs, 1 article in Electronics for You (EFY) magazine, 20 articles in Open Source for You Magazine and over 150+ publications in highly cited Journals and Conferences. He has completed 2 funded projects under DST TIDE and CSRI scheme in AI applications. Some of his professional awards include: Iconic Teacher in Research Award at Symbiosis University of Applied Sciences, Indore, Best Patent Award from IEEE Madras Section for the year 2024, Certificate of Award with cash prize $250 for 1st place in the International Poster Challenger by Peeref, Kalpa Acharya Award (Best researcher Award) Bharath Education Excellence Awards (BEEA) 2021-22 organized by BrainOVision, IEEE MAS Best Researcher Award - 2022 (Age 40 and Below 50) by IEEE Madras Section, AICTE Lilavati Award 2021-22 winner with 1 Lakh Cash Prize, Best Performer in the Poster Display at IIC Regional Meet held at Sathyabama Institute of Science and Technology Chennai on 21st July 2022, Best Model/Technology Presentation Award by IEEE-Nanotechnology Council Student Chapter IIT Indore, Yuva Mentor as a Changemaker Award, Faculty with Maximum Publishing in CSI Communications 2017-2019, International Data Science Writer of the Year 2019 by Data Science Foundation UK with cash prize €900, MTC Global Outstanding Researcher Award, Inspiring Authors of India, Deloitte Innovation Award Deloitte for Smart India Hackathon 2018, Patent Published Award, and Impactful Author of the Year 2017-18. He acted as a Mentor, Evaluator cum Jury Panel Member, Grand finale of SIH 2022 and MANTHAN, Mentor and Jury member in ASEAN-India Hackathon 2021, Primary SPOC and Evaluator for Toycathon 2021. He has received an appreciation certificate for Developing SIH Alumni Portal and SIH 2022 Portal for Ministry of Education's Innovation Cell by Ministry of Human Resource Development, Government of India and MHRD’s Innovation Cell 25th May 2022. He has delivered 110+ guest lectures/seminars in National & International levels, delivered 30+ keynote speech/invited speech and chaired 350+ sessions for various National and International Conferences. He is serving as a Reviewer and Editorial Board Member of many reputed Journals and acted as Technical Program Committee member of National conferences and International Conferences at Vietnam, China, America and Bangkok. His research interests are Artificial Intelligence, Cloud Computing and IoT. He has delivered various guest lecture under AI applications in power grid applications. Dr.Balakrishnan has acted as mentor in prestigious IndiaAI Fellowship under the IndiaAI Mission with a fellowship grant of ₹1,00,000. And he has acted as Mentor in Kavach 2023 Hackathon Title Winner with 1 Lakh Cash Prize, Mentor in Smart India Hackathon (SIH) 2020 Title Winner with 1 Lakh Cash Prize. He has 14 Granted International Patents, 45 Indian Patents on IoT Applications, 22 Design Patent Grants and 3 granted Copyrights. Dr. Balakrishnan has been appreciated under India Book of Records 2021 for filing 18 patents over a period of 15 months. He is acting as an Author at IEEE Teaching Excellence Hub, IEEE EduMentor Connect Program mentor, IEEE YESISI’12 2023 Publicity Ambassador, IEEE.TV Region 10 Global Ambassador, IEEE Brand Ambassador, IEEE Publicity Ambassador, IEEE Senior Member, T4 Ambassador and Bentham Science Publisher Brand Ambassador.

Abstract

The purpose of this study is to empirically examine the impact of artificial intelligence (AI) and value engineering (VE) tools on the effectiveness of continuous process improvement (CPI). A quantitative research approach was adopted using a structured survey administered to managers and process improvement specialists across industrial and service organizations. Structural equation modeling (SEM) was applied to analyze relationships between AI usage, value engineering practices, decision-making quality, and continuous improvement performance. The results confirm that AI significantly strengthens the effectiveness of value engineering and positively influences continuous improvement outcomes. The findings contribute empirical evidence to management science by demonstrating the synergistic role of AI and value engineering in enhancing process performance and organizational learning.

Keywords: continuous process improvement, artificial intelligence, value engineering, empirical study, process management

Biography

Eng. Renata Stasiak-Betlejewska PhD., works at Faculty of Management, Czestochowa University of Technology since 2000 as a teacher, scientist and coordinator of Erasmus+ programme and supervisor of Scientific Students Group. The main research areas: quality and production engineering, innovations management, industrial property management. Author and co-author of approximately 400 scientific publications. Holder of CEEPUS scholarship and several Erasmus+ teaching mobility scholarship. Member of the scientific team in the international research projects: European projects (Supporting Fraternity on entrepreneurship and education, ECO-SANDWICH – energy Efficient, Recycled Concrete Sandwich Façade Panel), VEGA 1/0067/11 Dynamics and content of decision taking processes in motivating of human potential, VEGA 1/0079/14 Competitiveness growth barriers (of organizations in Slovak Republic) in accordance with use and development of the innovative potential of human capital), an international scientific project under the auspices of the Ministry of National Education and Scientific Research in Romania, implemented by Transilvania University of Brasov (title of the project: Regional Network of Academic Success Centres (CRU), type of project: AUF ( Agence Universitaire de la Francophonie) – Francophone action plan.

Abstract

New very effective methods for 3d computergraphics is invented.

Object generation is most often a very tedious task since objects has to be modelled for the rendering machine.

Most common is to model the polygon mesh built objects in a modelling tool for triangular meshes.

An object can have a consistuent of  just a few up to many millions of triangular polygons.

Such constructions is mostly very problematic.

We propose invent and implement a much faster and efficient method by generationg object through algorithmic analysis of texture or topological height maps, collecting up to millions of polygons into just one single or a few basis polygon/s.

The algorithmic analysis is simple performed by the "pickup"-function coded by a simple mathematic equation.

The pickup then inserts a 3d height or depth coordinate into a two dimensional mesh of triangles or rectangles building the basis.

The simplification or speedup can be of a order up to factor 100-30000 times heightened efficiency.

Biography

Tony Barrera is a certified autodidact math genius. He have published more than 42 Ordinary high rated scientific papers And up to several hundred publications ,computer simulations and animations In different subjects, scientific papers in mathematics , computer graphics, numerical analysis, astrophysics and Particle Atomic physics. Tony does research general together with prof Ewert Bengtsson, Prof Anders Hast and Physicist Bo Thelin and the crew of Barrera Science Lab. Tony Barrera have been working for the company AB Consonant with implementation of the Fast Fourier Transform, FFT , and as a computergrahics researcher at Cycore AB (Webbgraphics). Constructor of about 10 - 20 different Graphics Engines , Assembler ,Basic, Pascal and/or C++ computer languages. Started with mahematics and science at age 3, got the first Astronomy book (from mother Elisabeth Mercadal) at 9, the first Chemistry set at 10 , Chief (head) of Barrera Science Lab.

Abstract

Multi-Agent Systems (MAS) represent a powerful paradigm in distributed artificial intelligence, where multiple autonomous agents interact to achieve individual or collective goals within a shared environment. The design of effective MAS hinges on robust mechanisms for collaboration, coordination, and conflict resolution, particularly in complex, dynamic, and resource-constrained domains. This work presents a comprehensive overview of the principles and design methodologies underlying collaborative and coordinated multi-agent architectures, emphasizing how agents communicate, negotiate, and adapt their behaviors to optimize system-level performance.

The study explores key coordination strategies, including task decomposition, role assignment, shared goals, and temporal synchronization, alongside formal interaction protocols such as contract-based coordination and negotiation models. Special attention is given to conflict detection and resolution mechanisms arising from resource contention, goal inconsistency, and communication ambiguity. Approaches such as negotiation, mediation, arbitration, and game-theoretic strategies are discussed to ensure fairness, efficiency, and system stability.

Furthermore, the abstract highlights the relevance of MAS design in real-world applications such as smart grids, autonomous traffic systems, supply chain optimization, cybersecurity, and collaborative AI assistants. By integrating learning-based techniques and adaptive decision-making, modern MAS can exhibit emergent intelligence and scalability while maintaining robustness in uncertain environments. Overall, this work underscores the importance of structured collaboration, efficient coordination, and principled conflict resolution in designing scalable, intelligent, and resilient multi-agent systems capable of addressing complex real-world challenges.

Biography

Dr.S.Balakrishnan is a Professor and Head of Department of Computer Science and Engineering, Aarupadai Veedu Institute of Technology, Vinayaka Mission’s Research Foundation (Deemed to be University), Paiyanoor, Chennai. He has 24 years of experience in teaching, research and administration. He has published over 39 books, 10 Book Chapters, 30 Technical articles in CSI Communications Magazine, 27 technical Blogs, 1 article in Electronics for You (EFY) magazine, 20 articles in Open Source for You Magazine and over 150+ publications in highly cited Journals and Conferences. He has completed 2 funded projects under DST TIDE and CSRI scheme in AI applications. Some of his professional awards include: Iconic Teacher in Research Award at Symbiosis University of Applied Sciences, Indore, Best Patent Award from IEEE Madras Section for the year 2024, Certificate of Award with cash prize $250 for 1st place in the International Poster Challenger by Peeref, Kalpa Acharya Award (Best researcher Award) Bharath Education Excellence Awards (BEEA) 2021-22 organized by BrainOVision, IEEE MAS Best Researcher Award - 2022 (Age 40 and Below 50) by IEEE Madras Section, AICTE Lilavati Award 2021-22 winner with 1 Lakh Cash Prize, Best Performer in the Poster Display at IIC Regional Meet held at Sathyabama Institute of Science and Technology Chennai on 21st July 2022, Best Model/Technology Presentation Award by IEEE-Nanotechnology Council Student Chapter IIT Indore, Yuva Mentor as a Changemaker Award, Faculty with Maximum Publishing in CSI Communications 2017-2019, International Data Science Writer of the Year 2019 by Data Science Foundation UK with cash prize €900, MTC Global Outstanding Researcher Award, Inspiring Authors of India, Deloitte Innovation Award Deloitte for Smart India Hackathon 2018, Patent Published Award, and Impactful Author of the Year 2017-18. He acted as a Mentor, Evaluator cum Jury Panel Member, Grand finale of SIH 2022 and MANTHAN, Mentor and Jury member in ASEAN-India Hackathon 2021, Primary SPOC and Evaluator for Toycathon 2021. He has received an appreciation certificate for Developing SIH Alumni Portal and SIH 2022 Portal for Ministry of Education's Innovation Cell by Ministry of Human Resource Development, Government of India and MHRD’s Innovation Cell 25th May 2022. He has delivered 110+ guest lectures/seminars in National & International levels, delivered 30+ keynote speech/invited speech and chaired 350+ sessions for various National and International Conferences. He is serving as a Reviewer and Editorial Board Member of many reputed Journals and acted as Technical Program Committee member of National conferences and International Conferences at Vietnam, China, America and Bangkok. His research interests are Artificial Intelligence, Cloud Computing and IoT. He has delivered various guest lecture under AI applications in power grid applications. Dr.Balakrishnan has acted as mentor in prestigious IndiaAI Fellowship under the IndiaAI Mission with a fellowship grant of ₹1,00,000. And he has acted as Mentor in Kavach 2023 Hackathon Title Winner with 1 Lakh Cash Prize, Mentor in Smart India Hackathon (SIH) 2020 Title Winner with 1 Lakh Cash Prize. He has 14 Granted International Patents, 45 Indian Patents on IoT Applications, 22 Design Patent Grants and 3 granted Copyrights. Dr. Balakrishnan has been appreciated under India Book of Records 2021 for filing 18 patents over a period of 15 months. He is acting as an Author at IEEE Teaching Excellence Hub, IEEE EduMentor Connect Program mentor, IEEE YESISI’12 2023 Publicity Ambassador, IEEE.TV Region 10 Global Ambassador, IEEE Brand Ambassador, IEEE Publicity Ambassador, IEEE Senior Member, T4 Ambassador and Bentham Science Publisher Brand Ambassador.

Abstract

The efforts are focused to develop  physicochemical and spectroscopic methods & technologies  to characterize the in-situ chemical speciation of the inorganic contaminants for remediation of water & environmental pollution by catalytic oxidants to save marine life. Also, to discuss strategies to control Water &  Environmental pollution resulting due to toxin, toxic gases, GHG (Green House Gases), by making use of Catalytic oxides of first row transition metal oxides. 

The oxidation process  would be employed to treat Groundwater contaminants by making use of  the chemical oxidantsviz. hydrogen peroxide, persulfate, permanganate & ozone . These oxidants have been able to cause the rapid and complete chemical destruction of many toxic organic chemicals; other organics are amenable to partial degradation as an aid to subsequent bioremediation. Its presumed that Cobalt oxide should optimize the process of subsurface remediation and above-ground water treatment systems depending on a variety of site-specific conditions e.g. reaction rate kinetics.

Also, to correlate Physico-chemical properties of these  catalytic oxidants  involving chemical oxidation be applied  in subsurface systems and in above ground water treatment systems involving chemical oxidation regeneration of Granular Activated Carbon (GAC).

Water gets polluted due to toxin & toxic gases through four types of toxic entities; chemical, biological, physical and radiation . Aim is to develop innovative methods to entrap toxins , Chemical toxicants ,inorganic substances( lead, mercury, hydrofluoric acid, chlorine gas), organic compounds ( methyl alcohol),  by developing High AffinityToxin Receptors (HART).

Next, to  evaluate correlation of  chemical oxidants with chemical species associated with soil and aquifer materials, and with target and non-target contaminants during water treatment processes.Finally,to developModel of Chemical Reaction Kinetics(MCRK) in order to investigate process fundamentals & assess contaminant transformation.

Biography

Dr. Virendra Kumar Goswami, Ph.D. IndianInstitute of Technology, Kharagpur, MS from the University of Wisconsin, USA. Post Doctorate Fellow at the University of Illinois, Chicago, USA. ‘Visiting Scientist’ to United Nations Industrial Development Organization (UNIDO), ICTP, Italy. Expert Panelist International Civil Aviation Organization (ICAO), Canada & Association of Indian Universities. Founder President ’Environment & Peace Foundation & Ex. Wing Commander, IAF. Dr. VirendraGoswami worked at Space Science Engineering Centre, NASA /NOAA, University of Wisconsin,USA. Former Vice Chancellor: Sangam& Sunrise Universities. DirectorGeneral/Director of Management/Engineering Institutes. Prof. Emeritus& Advocate: Supreme Court of India. Ph .D & M. Tech Examiner at Centre of Energy Studies at IIT Delhi . More than 44 years of teaching, research and administrative experience at Home and Abroad. Presented Papers in the field of Chemical Technology, Atmospheric Sciences, Space Sciences, Satellite Application, Climate Variability, Control of Global Warming & Quality Higher Education at International/National Conferences held in India, USA,UK Latin America, South Africa, Canada and Europe(more than 31 countries of all the Continents). Besides, headed various delegations at National & International Levels. Special Invitee by the World Meteorological Organization(WMO), Geneva in 2001& NPW:NCAR USA inApr’15. Invited Speaker to the Coupled Data Assimilation Workshop, sponsored byWMO, Météo-France, Toulouse, October 2016 , IV Family Child Conference ,Nigeria in Nov’16& Lomonosov Moscow State University during Sep17&Univ. of California, Berkley in Apr’18.Lately,Chaired the session & Guest Speaker at International Conf. on Defense & Space Application ,AKT Univ, Aug’19.

Abstract

• Teaching beyond the classroom is essential in applied science, engineering, and technology education to meet modern professional demands. This presentation examines learning approaches that extend beyond traditional classrooms through experiential learning, digital platforms, industry collaboration, and project-based activities. Such approaches bridge theory and practice, enhance critical thinking, innovation, and student engagement, and improve employability. The role of educators shifts from content delivery to facilitation and mentorship. The study concludes that teaching beyond the classroom is a necessary evolution for developing skilled, adaptable, and future-ready graduates.

Biography

Dr. Adel Esayed, brings over three decades of leadership, academic expertise, and industry-focused innovation to the conversation. He currently serves as the Dean of the Faculty of Applied Science, Construction, and Engineering Technology at George Brown Polytechnic , where he has spent the past 10 years shaping programs that respond to the rapidly evolving needs of the construction and engineering sectors. Dr. Esayed’s career includes impactful leadership roles such as Associate Dean at Niagara College, as well as Academic Chair at St. Clair College, leading 75 faculty while advancing student success, accreditation, and program quality. Before moving into senior leadership, Dr. Esayed spent seven years as Program Coordinator and Faculty at George Brown Polytechnic, strengthening industry partnerships, guiding curriculum development, and mentoring new faculty. His academic foundation includes research, instruction, and a post-doctoral fellowship in Materials Science and Engineering at the University of Toronto.