Committee Members

I am a technology leader specializing in AI and big data, bringing extensive experience in application development and architecture to my work. My career has been dedicated to exploring innovative approaches that address complex challenges, enabling organizations to leverage technology effectively. I take pride in my ability to identify creative and pragmatic solutions tailored to the unique needs of my clients, ensuring that their goals are not only met but exceeded.

In addition to my technical expertise, I have a strong passion for motivating others. I believe that fostering an environment of collaboration and encouragement is essential for driving success within teams. I actively seek to inspire my colleagues to strive for excellence, helping them recognize their potential and achieve their best work.

As a regular speaker at conferences and meetups, I enjoy sharing my insights and knowledge with the tech community. These engagements allow me to connect with like-minded professionals and contribute to the broader dialogue on advancements in technology. Through my presentations, I aim to spark curiosity and inspire others to explore new ideas and solutions.

Recently, I had the privilege of co-authoring two books: The Artificial Intelligence Infrastructure Workshop (Packt) and 97 Things Every Data Engineer Should Know (O’Reilly). These publications reflect my commitment to knowledge sharing and professional development in the field of data engineering and artificial intelligence. By contributing to these works, I hope to empower others in their careers and enhance the collective understanding of best practices and emerging trends in our industry.

In all my endeavors, I remain dedicated to bridging the gap between complex technology and real-world applications, driving innovation, and helping organizations navigate their digital transformation journeys. I believe that through collaboration, continuous learning, and a shared vision, we can achieve remarkable outcomes and shape the future of technology together.

Linjuan Rita Men, Ph.D., APR, is a Professor of Public Relations and Director of Internal Communication Research in the College of Journalism and Communications at the University of Florida. She founded and directs the Internal Communication Research Hub, a virtual space dedicated to fostering innovative research, education, and best practices in internal communication. With a background in corporate communication research and consulting, Men’s research interests include internal communication, leadership communication, emerging technologies including social media, metaverse, and artificial intelligence, and entrepreneurial communications.

Men has published more than 100 articles in refereed journals and as book chapters. She is the (co-) author/editor of five books. Men’s contributions to the field have been widely recognized through numerous top paper/research awards and recognitions from national and international communication associations and conferences, including the 2022 Hillier Krieghbaum Under-40 Award from the Association for Education in Journalism and Mass Communication (AEJMC). Men serves as an associate editor for Journal of Communication Management and is a member of the Arthur W. Page Society. Men has worked internationally with Alibaba Group, Inc., Ketchum, Inc., and provided management communication consulting for various multinational corporations, startups, and non-profit organizations.

Mohsen Ahmadi is a Machine Learning and Computer Vision Research Scientist in the Department of Electrical and Computer Science at Florida Atlantic University. His research involved collaborations on several papers related to machine learning. He has been actively involved in image processing and optimization, particularly in Machine Learning with the application of Evolutionary algorithms. He also published a paper on Healthcare Analytics in the Nature Journal, focusing on AI and mathematical programming. He not only advanced past the Top 2% of scientists in 2022 to reach the Top 1% in 2023 but was also ranked among the top 1000 Artificial intelligence and environmental scientists out of roughly 200,000 scientists. He also is one of the top 1% of best reviewers in Computer Science and Cross-Field on the Web of Science. Also, in 2022, he received the Best Researcher award at the 13th International Advanced Computing Conference (IACC, IEEE). His extensive research portfolio covers diverse areas such as video and image processing, optimization, and machine learning, with a specific focus on computer vision applications.

“I am a PhD Candidate at the College of Information Science & Technology, University of Nebraska at Omaha, specializing in NLP, Data Science, AI, Deep Learning, and Statistics. My research focuses on textual data analysis and prediction using deep learning, natural language processing (NLP), and statistical methods, primarily with social media data. I currently concentrate on public health issues related to depression and anxiety, aiming to better understand the severity of these mental health conditions. Additionally, I have extended my work on text generation and text summarization for cyberbullying detection on online platforms. My future research endeavors will involve expanding these methods to image analysis, particularly in the field of neuroscience to investigate the cognitive aspects of mental health.”

Rujun Gao, senior Ph.D. student at Texas A&M University, specializes in natural language processing, large language models, and generative AI, especially the innovative application of AI in educational contexts and platform development. Her research interests include language model agents, retrieval augmented generation, auto coding, auto assessment, etc.

Zhuowen (Kevin) Zou is a 3rd-year Ph.D. Candidate in the Bio-Inspired Architecture and Systems Lab (BIASLab) at the University of California, Irvine, advised by Dr. Mohsen Imani. His research revolves around Vector Symbolic Architecture (VSA), where he develops and analyzes cognitively inspired learning algorithms with VSA for efficient and explainable neuro-symbolic AI. He has published more than 25 papers, including at top journals and conferences in Machine Learning and Electronic Design Automation, including CVPR, Frontiers in Artificial Intelligence, DAC, DATE, ICCAD, Scientific Reports, and ISCA.

Kathy MinHye Kim, Ph.D. Dr. Kim is a Clinical Assistant Professor of TESOL & Applied Linguistics, an affiliated faculty of Boston University’s AI and Education Initiative, and the Director of the Second Language Acquisition Lab at BU. Her work focuses on understanding the cognitive mechanisms behind adult second language (L2) processing and acquisition and the cognitive and biographical factors that impact L2 processing and representation. Dr. Kim has received grants (e.g., NSF DDIG, APA Division 15 Early Career grant) in exploring the development of L2 of adult learners.

Alain R. Puente Santiago received his Ph.D. degree in Physical-Chemistry with distinction (July 2017) from the University of Cordoba, Spain. He has worked as a Research Fellow in Prof. Goodenough’s group (Nobel Prize in Chemistry 2019) at the University of Texas at Austin in the development of nanocluster-based electrocatalytic materials. Currently, he is working as a Postdoctoral Associate in the Department of Chemistry at Florida International University. He has published 71 articles in very prestigious journals such as Journal of the American Chemical Society (7), ACS Sustainable Chemistry and Engineering (5), Journal of Materials Chemistry A (5), Angewandte Chemie (3), Nanoscale (3), ACS Applied Materials and Interfaces (2), Green Chemistry (2), Chemical Society Reviews (2), Advanced Energy Materials (1), Chem (1) and Journal of Catalysis (1). Dr. Santiago’s articles have reached 3000 citations and an H index of 29 in the last 5 years. His research interests tackle the development of low-dimensional heterostructures for electrocatalytic, sensing, and energy storage applications as well as the use of machine learning strategies to design the next generation of catalytic nanosystems.

Yazeed Alkhrijah  received the B.S. degree in electrical engineering (communication and electronics) from King Saud University, Riyadh, Saudi Arabia. He obtained the M.S. degree in electrical and computer engineering from The University of Tennessee, Knoxville, TN, USA, and the Ph.D. degree in electrical and computer engineering from Southern Methodist University, Dallas, TX, USA. In 2022, he served as the director of the Engineering Sciences Research Center at Imam Muhammad Ibn Saud Islamic University (IMSIU). Currently, he is the vice dean of scientific research for the affairs of research centers and chairs at IMSIU. His research interests include wireless communication, Machine learning, AI, UAV, network, and digital signal processing.

Mumtaz Karatas holds a BSc in Industrial Engineering from the Turkish Naval Academy and an MSc in Industrial & Operations Engineering from the University of Michigan. He has six years of experience as an operations research analyst for the navy and obtained his PhD in Industrial Engineering from Kocaeli University. Following his time as a researcher at the Naval Postgraduate School for two years, he served as a faculty member at the Turkish Naval Academy for 10 years.

His primary research focuses on the application of operations research techniques, optimization, machine learning, and data analytics to tackle supply chain design and logistics problems, as well as defense planning problems. He specializes in areas such as facility location and sizing, vehicle/inventory routing, sensor network design, and transportation planning. His recent research includes robust optimization in the context of disaster planning, healthcare resource management, and UAV mission planning.

Dr. Jingran Sun is a post-doctoral fellow at the Center for Transportation Research at The University of Texas at Austin. He earned a PhD in Transportation Engineering from the University of Texas at Austin, as well as two MSc degrees—one in Construction Engineering and Project Management and the other in Statistics. Jingran’s expertise lies in infrastructure system resilience, agent-based simulation, artificial intelligence, and complex network analysis. His research, which has been presented at both national and international conferences and published in various peer-reviewed journals, such as Transportation Research Part D: Transport and Environment and Journal of Infrastructure Systems, and recognized with multiple awards. He is dedicated to finding solutions that promote long-term sustainability of infrastructure systems. Jingran’s contributions extend beyond academia through his active involvement in professional organizations and technical committees, reflecting his commitment to advancing the field of transportation engineering and infrastructure management.

Hussein Alkhazraji  is currently pursuing a Ph.D. in computer science at the University of Northampton. His research is at the intersection of machine learning and GPS data, focusing on innovative solutions for road traffic management. By analyzing and interpreting GPS data with advanced machine learning algorithms, Hussein Alkhazraji aims to revolutionize how drivers receive route suggestions.

Hussein Alkhazraji goal is to enhance the travel experience for drivers by providing intelligent and optimized route suggestions. This not only improves individual travel times but also contributes to more efficient traffic flow on a larger scale.

Prior to his Ph.D. studies, Hussein Alkhazraji completed a Master’s degree in Computer Science, where he developed a keen interest in the practical applications of machine learning. His academic journey has been marked by a strong commitment to leveraging technology for real-world problem-solving.

In addition to his research, Hussein Alkhazraji has presented his findings at various conferences, receiving accolades for his innovative approach to traffic management. He has also published several papers in esteemed journals, establishing himself as a thought leader in his field.

Beyond academia, Hussein Alkhazraji is passionate about sharing his knowledge and inspiring the next generation of computer scientists. He volunteers as a mentor for undergraduate students and participates in community outreach programs that promote STEM education.

His dedication to his research and his desire to make a tangible impact on society drive his work every day. Hussein Alkhazraji envisions a future where intelligent traffic systems are seamlessly integrated into everyday life, leading to safer and more efficient transportation networks worldwide.

Dr. Seunghee Lee is a Research Professor at the KonYang MEdical data ReseArch group, Konyang University Hospital, Daejeon, Republic of Korea.

She is conducting various research projects to bridge theoretical mathematics and practical applications through exploring the theory of stability in dynamical systems and its applications.

Her research interests include dynamical systems, mathematical data analytics, and medical AI.

Currently, she is the principal investigator on a project developing a clinical decision support system (CDSS) using data from the intensive care unit (ICU) and is involved in building and utilizing medical AI-related data from hospital sources.

Ahmadreza Mohebbi has a Ph.D. in Education with a focus on language, culture, and society from the University of Auckland. His research interests include Cultural Linguistics, Linguistic Landscape, Teaching English as an International Language (TEIL), Materials and Curriculum Development for English Language Teaching and Learning, and Mixed Methods Studies. He has served as a reviewer for journals such as Cogent Arts & Humanities, Scientometrics, and Ampersand. Additionally, he has published several papers in international journals, including the International Journal of Multilingualism, The Reading Matrix, TESL-EJ, and Ampersand. He currently works as an EAP lecturer at Bridge International College, one of the schools of ICL Education Group in Auckland.

Miguel Quemada, Professor at the Universidad Politécnica de Madrid (Spain), is an agronomist interested in combining new monitoring technologies (i.e., remote sensing) and artificial intelligence to enhance the sustainability of cropping systems. His field of expertise is nitrogen and water management, researching strategies that increase productivity and minimize environmental impact. He is a member of the European Expert Nitrogen Panel and acts as an External Expert for the European Commission on assessing RTD projects. He has published more than 80 papers in reputed journals and served as an associated editor of Agronomy for Sustainable Development and European Journal of Agronomy.

Wu Jianghong, Doctor of Engineering, professor, doctoral supervisor, responsible person of energy and power engineering. She graduated from School of Energy and Power Engineering, Xi ‘an Jiaotong University in 1987, 1990 and 1996 respectively with bachelor’s degree, master’s degree and doctor’s degree. Her tutors were professors Zhiyou Zhang, Changqing Chen and Yezheng Wu. From 1996 to 1998, she worked as a postdoctoral researcher in Key Laboratory of Heat Transfer Enhancement and Process Energy Conservation of Ministry of Education, South China University of Technology. His research topic was hydrate cold storage technology, and his co-supervisor was Professor Wang Shiping. In 2008, she worked for one year in the Department of Materials and Mechanical Engineering, Queen Mary University of London, with Professor John Rose and Dr. Huasheng Wang as her co-supervisors.

she is mainly engaged in the basic research and technology development of environmental protection, process enhancement and clean/Renewable Energy utilization application with enhancement heat transfer and artificial intelligence as the core. In recent years, she has been published in Renewable and Sustainable Energy Reviews (TOP journal, Impact Factor 12.11), Expert Systems With Applications (authoritative journal of artificial Intelligence, IF 8.665), Applied Energy, Adsorption Science & Technology, International Journal of Refrigeration, International Journal of Refrigeration Energy and other important international journals have published 31 SCI papers, published 35 EI retrieval papers, and obtained 15 invention patents and 20 utility model patents. As a technical expert and main drafter, she participated in the drafting and revision of 5 China national standards for refrigeration and air conditioning industry.

Main Achievement

Main academic contributions: (1) Invention of micro-regenerative solid-state room temperature magnetic refrigeration cycle and system; (2) Invented and studied the air source heat pump system combined with micro-channel heat exchanger and phase-change heat storage material; (3) Successfully developed the electric vehicle heat pump air conditioning system, researched and established the dynamic load calculation method of automobile air conditioning, and obtained an international leading appraisal result; (4) The application of artificial intelligence to R290 room air conditioner active safety research, the development of refrigerant leak identification and early warning air conditioner prototype; (5) To carry out research on air conditioning energy consumption mode, research on refrigeration and heating occurrence time curve and should be used in the national standard of energy efficiency of rotational speed controllable air conditioner.

Cheng Fanyong received his Ph. D. degree in the College of Electrical and Information Engineering, Hunan University, Changsha, China, in 2017. He continued to research as research fellow at the School of Electrical and Electronic Engineering, Nanyang Technological University from 2019 to 2021.
He is currently an Associate Professor at the School of Electrical Engineering, Anhui Polytechnic University, Wuhu, China. He served as the reviewer for some famous journals, such as Applied Energy, IEEE Transactions on Industrial Electronics, IEEE Transactions on Industrial Informatics and so on.
His research interests include: Data-driven Fault detection and diagnosis, anomaly detection and location for surface image, and intelligent air balancing. In related subjects, he has published nearly more than 20 SCI journal papers.

Yaowen Shan is a Professor in the UTS Business School at the University of Technology Sydney. His research focuses on the intersection of accounting and financial economics. In particularly, he examines the role of accounting and non-accounting information in capital market regulation, corporate governance, financial reporting and executive compensation. His work has been accepted for publication at The Accounting Review, Review of Accounting Studies, Contemporary Accounting Research, Journal of Corporate Finance, Journal of Banking and Finance, Abacus, Accounting and Finance, Pacific-Basin Finance Journal, Australian Journal of Management, and Australian Accounting Review. He also serves as the joint editor-in-chief of Australian Accounting Review, and Associate Editor of Accounting and Finance and Australian Journal of Management. Yaowen has won two Best Paper Awards at leading international accounting and finance conferences. He has also received many research grants totaling over 1.6 million dollars. These include three ARC Discovery Grants, and several national competitive grants such as CIFR and AFAANZ research grants.

Denis Borenstein is an esteemed associate professor in the Management School at the Federal University of Rio Grande do Sul, Brazil. He has dedicated his academic career to the application of operations research and artificial intelligence methods to address complex problems in various fields. Borenstein’s expertise spans logistics, real-time transportation design, scientometrics, and finance, where he has made significant contributions through his innovative research.

He has an impressive publication record, with his work appearing in prestigious journals such as the European Journal of Operational Research, Expert Systems with Applications, Engineering Applications of Artificial Intelligence, and Decision Support Systems. His scholarly contributions have garnered recognition and respect within the academic community.

In addition to his research endeavors, Borenstein serves as an associate editor for the journal Expert Systems with Applications, where he plays a pivotal role in shaping the direction of research in the field. His editorial work reflects his commitment to advancing knowledge and fostering innovation in operations research and AI applications.

Throughout his career, Borenstein has demonstrated a passion for solving practical problems through rigorous academic research. His work not only contributes to the theoretical foundations of his fields of interest but also offers valuable insights and solutions to real-world challenges. As an educator and researcher, Denis Borenstein continues to inspire and influence both his students and his peers in the academic community.

Professor Chris Aldrich holds a Chair in Process Systems Engineering in the Western Australian School of Mines at Curtin University. In addition, he is an Extraordinary Professor at Stellenbosch University in South Africa and an Honorary Professor at the University of Queensland. His core expertise is in process automation in the mining and metallurgical process industries, with a strong focus on data analytics and machine learning.

Earlier in his career, he was a recipient of among other the British Association (S₂A₃) Silver Medal and President’s Award of the Foundation of Research and Development (FRD) in South Africa for international recognition of his research.

Prior to emigrating to Australia, he was the Founding Director of the Anglo Platinum Centre of Excellence in Process Monitoring at Stellenbosch University. At present, he is a Chief Investigator in the ARC Centre of Excellence for Enabling Eco-Efficient Beneficiation of Minerals, the ARC Industrial Transformation & Training Centre for Green Chemistry in Manufacturing, as well as the ARC Training Centre for Transforming Maintenance through Data Science. He is Fellow of the South African Academy of Engineering (FSAAE) and the Australasian Institute of Mining and Metallurgy (FAusIMM), as well as Technical Committee (TC 6.2) Chair of the International Federation of Automatic Control in Mining, Minerals and Metal Processing.

Dr. Hui Zhao is an accomplished scholar with a strong academic foundation and diverse research interests. She began her academic journey at Beijing Jiaotong University, where she pursued a Master’s degree in Transportation Management and Planning. Her time at Beijing Jiaotong University laid the groundwork for her deep understanding of transportation systems and planning strategies, which would become a central theme in her later research.

Motivated by a desire to delve deeper into the intersection of technology and transportation, Dr. Zhao pursued a Ph.D. in Computer Science at the Belfort-Montbéliard University of Technology in France. She completed her doctoral studies in July 2020, focusing on the development of advanced computational models and systems. Her Ph.D. research was marked by a commitment to integrating cutting-edge technology with practical applications, particularly in the realm of transportation and urban planning.

After earning her doctorate, Dr. Zhao accepted a Postdoctoral position at the Shanghai Research Institute for Intelligent Autonomous Systems, a prestigious institution affiliated with the School of Electronic and Information Engineering at Tongji University. In this role, she has been involved in pioneering research on intelligent systems, contributing to the development of technologies that enhance urban living and transportation efficiency.

Dr. Zhao’s research interests are broad and interdisciplinary, encompassing multi-agent systems, decision-making models, smart cities, intelligent transportation, and image processing. Her work is characterized by a focus on creating innovative solutions that address real-world challenges, particularly in the context of rapidly urbanizing environments.

Throughout her career, Dr. Zhao has demonstrated a strong commitment to advancing knowledge in her field and contributing to the development of technologies that improve the quality of life in modern cities. Her interdisciplinary approach, combining expertise in computer science with a deep understanding of transportation systems, positions her as a leading figure in the fields of intelligent transportation and smart city development.

Assoc. Prof. A.Y.M. Atiquil Islam is the Director of the International Graduate Program in Educational Technology at the Department of Education Information Technology of the East China Normal University. He is also a Guest Professor at the School of Teacher Education of Jiangsu University. He obtained a multidimensional PhD degree by combining two faculties, namely, Education and Computer Science & Information Technology at the Institute of Graduate Studies, University of Malaya. In his field of specialization, he developed and validated three models, namely, the Technology Adoption and Gratification (TAG) Model, the Technology Satisfaction Model (TSM) and the Online Database Adoption and Satisfaction (ODAS) Model.

Dr. Islam has had almost 21 years of experience in academia, industry and business. Furthermore, Dr. Islam has presented many papers at international conferences (Japan, Singapore, China, Indonesia and Malaysia) and published journal articles, books and chapters. One of his articles was listed as a “Highly Cited Paper” in Essential Science Indicators (ESI) in 2022 & 2023. He has also delivered keynote addresses, speeches, and guest lectures many times in the past five years. Dr. Islam has published in the British Journal of Educational Technology, Instructional Science, Educational Technology Research and Development, Journal of Information Science, Educational Psychology, Interactive Learning Environments, Journal of Research in Science Teaching, Online Information Review, and International Journal of Technology and Human Interaction. He serves as the Principal Investigator and Co-Investigator of local and international research grants totaling over a million yuan.

Dr. Islam has international collaboration with the United States of America, the United Kingdom, Germany, Australia, Malaysia, the Philippines, Pakistan, Indonesia, Saudi Arabia, Algeria, Bangladesh and Nigeria. Dr. Islam is an Editorial Board Member of the British Journal of Educational Technology (Q1, SSCI, 2022 IF=6.6), Executive Editor of the International Journal of Smart Technology and Learning, Editor of Cogent Education (ESCI & Scopus), and Article Editor of SAGE Open (Q2, SSCI, 2021 IF=2.032). His research interests are in the arena of Assessment of Educational Technology, ICT in Higher Education, Quantitative Modeling, Artificial Intelligence, STEM Education, Human Computer Interaction, Information Science, Digital Library Sciences, Metaverse and Virtual Reality.

Professor Alfred Ngowi is the Deputy Vice Chancellor – Research, Innovation and Engagement at the Central University of Technology (CUT), Free State. Before this position he held the positions of the Dean of the Faculty of Engineering and Information Technology, at CUT.

 He holds a Bachelor of Science (Civil Engineering) from the University of Dar es Salaam, Tanzania; a Master of Civil Engineering (Construction Engineering and Management) from Chalmers University of Technology, Sweden; a PhD in Civil Engineering from the University of the Witwatersrand, South Africa; and Advanced Machine Learning from Massachusetts Institute of Technology (MIT).

Professor Ngowi’s research interests are multi-disciplinary, and they include among others engineering, the built environment, human capital, the role of universities in the emerging technologies, future of work, sustainable development, application of Artificial Intelligence and circular economy. He has an extensive record in human capacity development having produced technicians and degree graduates as well as supervising 35 master’s and PhD students. Some of these students proceeded with their doctoral and postdoctoral studies at leading universities such as MIT and Princeton in the USA and Cambridge in the UK. He has published over 150 papers in journals, proceedings, and book chapters. He is a co-Chief Editor of the Journal of Construction in Developing Countries (JCDC); and Deputy Editor of the Journal of Built Environment and Asset Management (BEPAM).

He is a rated scientist by the National Research Foundation (NRF) of South Africa, registered professional construction project manager (Pr.CPM), member of Botswana Institute of Engineers (BIE); Member of the Chartered Institute of Building (MCIOB); and member of the International Association of Housing Sciences (IAHS).

Hugo Terashima-Marín holds a BSc in Computational Systems from Tecnológico de Monterrey, Campus Monterrey in 1982; MSc in Computer Science from University of Oklahoma in 1987; MSc in Information Technology and Knowledge-based Systems from University of Edinburgh in 1994; and PhD in Informatics from Tecnológico de Monterrey, Campus Monterrey in 1998.

Dr. Terashima-Marin is a Full Professor at the School of Engineering and Sciences and the Member of the Research Group in Advanced Artificial Intelligence. He is a member of the National System of Researchers (Rank II), the Mexican Academy of Sciences, and the Mexican Academy of Computing.  He is a Senior Member of the IEEE. His research areas are computational intelligence, heuristics, metaheuristics and hyper-heuristics for combinatorial optimization, automated generation of algorithms and applications of artificial Intelligence and machine learning. He has been principal investigator of various projects for industry and CONACyT.  Dr. Terashima-Marin has current collaboration with research groups in the University of Nottingham, University of Stirling, University of Edinburgh-Napier, University of Texas-San Antonio, the University of Houston, the University Andrés Bello in Santiago de Chile, and the Chinese Academy of Sciences.  He has published more than 130 research articles in international journals and conferences. He has supervised 7 PhD dissertations and 38 Master Thesis. In the past, he has been Director of the Graduate Program in Computer Science, the MSc in Intelligent Systems, the PhD in Artificial Intelligence, the PhD in Information Technology and Communications, the PhD Programs, and Graduate Programs at Tecnológico de Monterrey, Campus Monterrey, and the Leader of the Research Group in Intelligent Systems.

Dr. Shih-Cheng Lee is a distinguished Professor in Digital Finance at Yuan Ze University, where he also serves as the director of the Institute of Digital Finance. His academic leadership extends to his role as a Node Leader in the InSPiR2eS Centre for Responsible Science (IC4RS), reflecting his commitment to advancing responsible and impactful scientific research. Dr. Lee is globally recognized as a Pitching Research Ambassador within the Pitching Research Ambassador Global Network, underscoring his dedication to fostering innovative research practices and collaborations.

His scholarly pursuits are deeply rooted in the realms of Financial Engineering and Financial Risk Management, where he has made significant contributions through his research. Dr. Lee’s expertise encompasses RegTech, a field that integrates regulatory processes with technology to enhance compliance and efficiency in financial services. He is also well-versed in Intelligent Investment, employing advanced algorithms and data analytics to optimize investment strategies.

Dr. Lee’s academic interests further extend to the Basel Accord, a set of international banking regulations developed by the Basel Committee on Banking Supervision, and Accounting-Based Valuation, a method of evaluating the financial health and performance of firms through their accounting data. His multifaceted research endeavors have established him as a prominent figure in the field of digital finance, driving innovation and thought leadership.

Zheng Han is currently the Professor in School of Civil Engineering, Central South University. He serves as the Secretary-General of the Committee on the Practical Application of Artificial Intelligence Technology of the Chinese Society for Rock Mechanics and Engineering, the member of the Mountain Committee of the Chinese Geographical Society, the member of the Landslides and Engineering Committee of the Chinese Society for Rock Mechanics and Engineering, the member of the Ground Rock Engineering Committee of the Chinese Society for Rock Mechanics and Engineering, the executive committee member of the Youth Science and Technology Association of Central South University. He also serves as the associate editor of the journal of Intelligent Geoengineering, an editorial board member of Frontiers in Earth Science, SCIREA Journal of Geosciences, Advances in Geological and Geotechnical Engineering Research, and Journal of Central South University, an editorial board member of the Journal of Geological Hazards and Prevention. He is a visiting scholar at the University of Canterbury in New Zealand, , a member of the Japanese Geotechnical Society (JGS) and the Japan Society of Civil Engineers (JSCE), a member of the Asia Oceania Geosciences Society (AOGS), a member of the International Society for Environmental Geotechnology (ISEG), an expert reviewer for projects of the National Natural Science Foundation of China, the Swiss National Science Foundation, and a committee member of international academic conferences such as ICADD11, IFHR2017, ISEV2018, ICADD16, and ICNGN2023. Currently, Prof. Zheng Han is leading 15 projects funded by the National Natural Science Foundation, the National Key R&D Program, the Hunan Provincial Natural Science Foundation, etc. He has published 106 papers. His research achievements include 14 patents and core contributions to three national standards. He received the Sichuan Provincial Science and Technology Progress Award First Prize in 2024, the Kyushu University Research Award and the Japan Society of Geotechnical Engineering Excellent Research Award in 2015.

Meaad Alqahtany is a Research Assistant at King Saud Bin Abdulaziz University for Health Sciences. She holds a Master of Science from the University of Arkansas. Her primary research area focuses on Health Science Higher Education, where she is dedicated to identifying barriers and challenges within the field. Meaad works to translate these findings into practical solutions that support both faculty and students in the educational process.

She has made significant contributions to the field, including a recent publication titled “Faculty and Students Perspectives Towards Game-Based Learning in Health Sciences Higher Education.” Meaad’s work is instrumental in advancing innovative educational strategies and improving the overall quality of health sciences education.

Looking ahead, Meaad aims to continue conducting and publishing high-impact research that aligns with the goals set under Saudi Vision 2030. Her future research endeavors are directed toward transforming the Kingdom’s research landscape into a knowledge-based society and setting clear directions for enhancing the quality of health sciences education.

Li Qing, associate professor, master’s supervisor, postdoctoral fellow at the University of Alberta, Canada, and joint doctoral student at Donghua University and Georgia Institute of Technology. In May 2021, he was introduced to Anhui Agricultural University as a high-level talent, mainly engaged in research on intelligent monitoring and control of mechanical equipment, mechanical vibration testing, signal processing, etc.
He serves as a member of the Editorial Committee of the China Agricultural Machinery Society, a director of the Anhui Engineering Graphics Society, a returned overseas talent in Anhui Province, a high-level talent in Hefei (municipal leading talent – Category D), a peer reviewer of the National Natural Science Foundation, and an expert in the Anhui Intellectual Property Protection Training Faculty Pool.
He presided over 10 projects, including the National Natural Science Foundation of China, the Natural Science Foundation of Anhui Province, the National Key Laboratory Open Fund, the Basic Scientific Research Projects of Central Universities, the Anhui Provincial Key Laboratory Fund, and the High-level Talent Introduction Project. He published 55 papers (42 as the first author) in journals such as ESWA, MSSP, IEEE TMECH, TIM, SJ, SHM, and FMS, including 47 SCI/EI papers (38 as the first author), and applied for 26 invention patents (12 authorized).
He serves as the deputy editor-in-chief of  ” IEEE Sensors Journal ” (SCI journal)  , editorial board member of ” Measurement Science Review ” (SCI journal ) , guest editor-in-chief of “Frontiers in Physics” (SCI journal ), guest editorial board member of “Machines” (SCI journal ), guest editor-in-chief of “Sock and Vibration” (SCI journal ), chairman of the IEEE ICSIP 2022 International Conference on Signal and Image Processing, member of the program committees of more than 20 international conferences, reviewer of 43 SCI journals including IEEE TIE, TII, MSSP (reviewing more than 100 SCI papers annually and has been awarded outstanding reviewer awards many times), has been invited to be an invited speaker at international conferences many times, and won the IEEE ICSIP 2022 Best Presentation Award, etc.
The research team currently has 25 master’s students. Students majoring in mechanics, electrical engineering, automation, computer science and mathematics are welcome to join the research team. Outstanding graduate students can be recommended to study for a doctorate in well-known overseas universities and domestic 985 universities, or work in well-known companies in Hefei.

JULIANA KEIKO SAGAWA is currently an Associate Professor at the Department of Production Engineering of the Federal University of São Carlos, São Carlos, Brazil. In 2016, she was a visiting professor at the University of Bremen, Germany. Her primary research area concerns the application of Dynamic Modeling and Control Theory to production systems and supply chain. More broadly, her interests encompass intelligent production systems, production planning and control systems, simulation, project management, strategy, organizational integration, and varied topics in operations management, using both quantitative and qualitative methods. She received the B.S. degree in production engineering in 2006, the M.S. degree in mechanical engineering in 2008, and the Ph.D. degree in production engineering in 2013, all from the University of São Paulo, Brazil.

Tao Liu received the B.S. degree (Mathematics and Applied Mathematics) and M.S. degree (Applied Mathematics) from Harbin Engineering University, Harbin, China, in 2007 and 2009, respectively, and the Ph.D. degree (Mathematics) from Harbin Institute of Technology, Harbin, China, 2014. From 2022 to 2023‚ he was a Post-Doctoral Research Fellow at the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. He is currently an Associate Professor at the School of Mathematics and Statistics, Northeastern University at Qinhuangdao, China. He served as the reviewer for Mathematical Reviews of American Mathematical Society, Topical Advisory Panel Member and guest editor of Mathematics (indexed by SCI, JCR-Q1, IF: 2.4), guest editor of Axioms (indexed by SCI, JCR-Q2, IF: 2.0), editor of Journal of Advances in Applied & Computational Mathematics, editor of Journal of Nuclear Science and Technology Updates, external examiner for postgraduate thesis of PSG College of Arts & Science, guest editor of ICTA 2023, International Technical Committee Member of AMMAI 2025, AMMCS 2024, AMMCS 2023, AMMCS 2022, IWEP 2024, IWEP 2023, ICANCT 2024, ICANCT 2022, ICCEAD 2024, ICAIC 2024, ICARCE 2023, ICARCE 2022, AMICS 2023, AMICS 2022, AMDS 2023, AMDS 2022, ICAMCS 2023, ICAMP 2023, ACSE 2023, CMME 2023, SMMA 2023, ICTA 2023, CMBDA 2022, CPRA 2022, and reviewer for many journals indexed by SCI (such as AIMS Mathematics, Applied Mathematics and Computation, Axioms, Chaos, Solitons and Fractals, Communications in Nonlinear Science and Numerical Simulation, Computer Modeling in Engineering and Sciences, Electronic Research Archive, Electronics, Energies, Engineering Computations, Engineering with Computers, Foundations, Fractal and Fractional, International Journal of Mechanical Sciences, International Journal of Non-Linear Mechanics, Inverse Problems in Science and Engineering, Journal of Applied Analysis, Journal of Applied Analysis and Computation, Journal of Mathematics, Journal of Petroleum Science and Engineering, Mathematical Biosciences and Engineering, Mathematical Methods in the Applied Sciences, Mathematics, Optimization, Sensors, Sustainability, Symmetry). His research interests include: Deep Learning; Reinforcement Learning; Multiscale Methods (Multigrid and Wavelet); Homotopy Method; Inverse and Ill-posed Problems; Parameter Reconstruction. In related subjects, he has published nearly 40 SCI journal papers, including 8 top SCI journal papers, and nearly 40 EI conference papers. He has been awarded as the leader of the Outstanding Project of Nature Science Foundation of Hebei Province of China in 2019.

Dr. Yining Chen is a professor at the School of Integrated Circuits, Zhejiang University, and heads the Yield Enhancement and Product Development Department at the Zhejiang Province CMOS Integrated Circuit Process and Design Technology Innovation Center, China. He graduated with a Bachelor’s degree in Electronic Information Engineering from Zhejiang University, a Master’s in Microelectronic Materials from Katholieke Universiteit Leuven, Belgium, and a Ph.D. in Microelectronics from Nanyang Technological University, Singapore. He has worked at IMEC in Belgium and IMRE, A*STAR in Singapore as an R&D engineer and scientist. In the industry, he held senior roles at GlobalFoundries and NXP Semiconductors, and co-founded Smart Analysis Pte. Ltd. in Singapore.

Dr. Chen’s research focuses on leveraging AI and machine learning for IC manufacturing, significantly improving yield enhancement and process optimization. His work has been published in prestigious journals such as Electron Device Letters, Computer and Industry Engineering, and IEEE Transactions on Electron Devices. He pioneered the development of AI-driven yield enhancement solutions and big data analytics for comprehensive chip yield improvement. His contributions include the successful integration of AI algorithms in developing 65/55nm and 45/40nm CMOS low-power logic process platforms and the 28nm FD-SOI ultra-low-power MCU process platform. At Zhejiang University, he continues to drive advancements in AI and machine learning applications for semiconductor manufacturing, achieving industry-leading yield ramp-up efficiency.

Chung Kwan Lo is an Assistant Professor in the Department of Mathematics and Information Technology at the Education University of Hong Kong, Hong Kong. His main research interests are mathematics education, technology-enhanced learning (e.g., flipped learning, gamification, AI-support learning), student engagement, and teacher professional development.

Dr. Chung Kwan Lo is an Assistant Professor in the Department of Mathematics and Information Technology at the Education University of Hong Kong. With a strong focus on advancing educational methodologies, Dr. Lo’s primary research interests lie in mathematics education and technology-enhanced learning. His work encompasses innovative approaches such as flipped learning, gamification, and AI-supported learning, aiming to enhance student engagement and improve educational outcomes.

Dr. Lo is also dedicated to the professional development of teachers, helping them integrate new technologies and methodologies into their teaching practices. His contributions to the field are reflected in his extensive research and active involvement in educational advancements. Through his work, Dr. Lo seeks to foster a more interactive and effective learning environment for both students and educators.

Chuan Qin received his B.S. degree in electronic engineering and the M.S. degree in signal and information processing from Hefei University of Technology, Anhui, China, in 2002 and 2005, respectively, and the Ph.D. degree in signal and information processing from Shanghai University, Shanghai, China, in 2008. Since Dec. 2008, he has been with the faculty of University of Shanghai for Science and Technology, where he is currently a Professor. He was with Feng Chia University at Taiwan as a Postdoctoral Researcher and Adjunct Assistant Professor from July 2010 to July 2012. His research interests include multimedia intelligent computing, AI security, data hiding and image processing in encrypted domain. He has published over 200 peer-reviewed papers in journals and conferences including IEEE TIP, IEEE TIFS, IEEE TMM, IEEE TCSVT, IEEE TDSC, IEEE TETCI, IEEE TIM, IEEE TAI and ACM MM. He has also published one book and held six authorized patents. He was selected as the Highly Cited Chinese Researchers by Elsevier in 2020 and the World’s Top 2% Scientists in 2019-2022. He won the Excellent Paper Awards of CIHW 2016 and ChinaMFS 2023, and the Candidate of Excellent Paper Award of IEEE IIHMSP 2014. He has served as the Associate Editor for ACM TOMM, Signal Processing (Elsevier) and Information Fusion (Elsevier).

“Rodrigo is a Ph.D. candidate in Industrial Engineering specializing in Operations Research with an emphasis on Machine Learning at the Polytechnic School of the Federal University of Bahia. He holds a Master’s degree in Industrial Engineering from the same institution (2023) and a Bachelor’s degree in Statistics from the Institute of Mathematics and Statistics at the University of São Paulo (2021). His main areas of expertise include Operations Research, Machine Learning, Reinforcement Learning, Data Mining, Time Series, and Anomaly Detection.

Recently, he has been working with machine learning algorithms for fault detection in industrial processes. Rodrigo has proposed new approaches for training machine learning algorithms combined with optimization techniques to improve performance. Additionally, he has developed approaches based on explainable artificial intelligence as diagnostic and prognostic tools for monitoring manufacturing processes.

His thesis focuses on developing a new reinforcement learning approach for anomaly detection. This methodology will be applied using real sensor data to detect anomalies in oil and gas wells.”

Dr. Rajeswari Sengupta is an Associate Professor of Economics at the Indira Gandhi Institute of Development Research (IGIDR) in Mumbai, India. In the past she has held research positions at the Institute for Financial Management and Research (IFMR) in Chennai, the Reserve Bank of India, and the International Monetary Fund (IMF) and the World Bank in Washington D.C. She was a member of the research secretariat for the Bankruptcy Law Reforms Committee (BLRC) that recommended the Insolvency and Bankruptcy Code for India. Her research focuses on policy-relevant, macro-financial issues of emerging market economies in general and India in particular in the fields of international finance, monetary policy, banking, financial markets, and national accounts measurement. She has published in reputed international journals and has also written chapters in various books published by the Asian Development Bank, G20, the Centre for International Governance Innovation (CIGI), among others.

Dr. Sengupta completed her M.A. and Ph.D. in Economics from the University of California, Santa Cruz (UCSC). She holds two previous degrees in Economics from India, a Bachelors degree from Presidency College, Calcutta and a Masters from Delhi School of Economics.

She is an Assistant Professor at the Department of Computer Engineering, Modeling, Electronics, and Systems (DIMES) at University of Calabria. She is a working group member of the European Cooperation in Science \& Technology in the domain of Optimal Security approaches and their impact on the user, as well as an Artificial Intelligence/Machine Learning Working Group member of IEEE Future Networks. Prior to this, she was an Assistant Professor in the Department of Computer Science at Banasthali University, Rajasthan, for 15 years. She also worked as a Technical Support Engineer in TechMahindra, India, and Project Trainee at the Centre for Development of Advance Computing (C-DAC), India. She received her Ph.D. from West Bengal University of Technology, Kolkata, India. Her primary research interests are in the domain of Federated learning, Smart healthcare using Machine Learning, specifically Performance Evaluation of and Human Activity Recognition Systems. She is the author of many scholarly research papers, including reputed journal papers, in the above-mentioned areas. In the last few years, she has been exploring different aspects of federated learning. Currently, she is working on the Italian National project related to Green-Aware AI. She is the regular TCP member of some international flagship conferences such as ACM SIGKDD, IEEE Bigdata  and also reviewer of some reputed journals such as IEEE transactions on industrial informatics, IEEE internet of things and so on.

Chinedu Wilfred Okonkwo holds a PhD in Computer Science from North-West University, Potchefstroom Campus, South Africa, currently holds the position of Academic Programme Manager in the Information Technology faculty at Eduvos. With extensive experience in both industry and academia, he possesses strong innovative skills, particularly in developing educational tools aligned with the Fourth Industrial Revolution (4IR). His research focuses on Artificial Intelligence (AI) in Education, Computer Science Education, and Technology Adoption. Chinedu actively collaborates across interdisciplinary domains in AI research, contributing to numerous scholarly publications including journals, conferences, and book chapters as both author and reviewer. He also serves on the editorial board of an international conference and has been recognised with several prestigious awards throughout his career.

Syed Muhammad Abrar Akber received his MS computer science degree from the Virtual University of Pakistan in 2015. He received his PhD Engineering (Specializing in Computer Application Technology) from Huazhong University of Science and Technology, Wuhan, China. He is currently affiliated with the Silesian University of Technology, Gliwice, Poland. He has published many research articles in top level international peer reviewed journals and have presented his work at several prestigious international conferences. His research interests include artificial intelligence, smart cities, and big data processing.

Waishan Qiu is an Assistant Professor at the Department of Urban Planning and Design, the University of Hong Kong (HKU). His research utilizes big data and AI to improve mobility, shareability, and sustainability. He has been involved with various data-driven research and smart city projects worldwide in places like Saudi Arabia, the United Arab Emirates, the U.S., and China. Before joining HKU, he was an Associate at McKinsey & Company. He obtained a Ph.D. in Regional Science’22 from Cornell University, an M.C.P.’17 from MIT, an M.Arch.’14 with distinction from UCL, and a B.E.’ 13 from Tongji University. Waishan actively participates in many publications, lectures, and exhibitions. He co-instructed design workshops for digital conferences including the CAADRIA 2021-2023 and the Digital Futures 2020. He co-authored papers and was a reviewer for top-ranking journals like Landscape and Urban Planning, Sustainable Cities and Society and Cities. His exhibitions included ‘3RD VISION’ for the 2019 Shenzhen-Hong Kong Bi-City Biennale of Urbanism\Architecture (UABB), Housing+ Biennale (2017) at MIT, and ‘the Big Data, Visualization, and Society’ (2016). He also spoke on smart cities and big data for universities and institutions. Waishan was also an entrepreneur and honoree of Forbes China 30U30 (2019). He had co-founded three startups with a shared focus on urban entrepreneurship, looking at design thinking education, AI-enhanced driving safety systems, and urban development strategies respectively.

Dr. Yanti Idaya Aspura is the Deputy Dean for Undergraduate Studies at the Faculty of Arts and Social Sciences and an Associate Professor in the Department of Library and Information Science, Universiti Malaya. She began her career as a lecturer at the University of Malaya in 2016. Before her tenure at the University of Malaya, she served as a Senior Librarian at the International Islamic University Malaysia Library for over 13 years. She obtained her Bachelor of Human Sciences (Political Science) in 2000 and MLIS (Library and Information Science) in 2001 from the International Islamic University Malaysia. Subsequently, Dr. Yanti Idaya earned her PhD in System Science and Management from the National University of Malaysia in 2014. Her areas of expertise include Information Science, Information Retrieval, Digital Repository, Research Data Management and Open Science, and Bibliometrics. She is also an editorial board member of the Malaysian Journal of Library & Information Science (MJLIS) and a Certified Data Steward (511650). Additionally, she is a member of the Awareness and Capacity Working Group, Malaysia Open Science Alliance. She is involved in developing and teaching modules for the Training of Trainers on Data Stewardship for Open Science program. Currently, Dr. Yanti is also a member of the Universiti Malaya Open Science (UMOS), focusing on the development of UMOS policy, data governance, and Research Data Management (RDM) and also a member of the Research Data Alliance (RDA).

Victor Hugo C. de Albuquerque (Senior Member of IEEE) is currently a Professor and Senior Researcher at the Department of Teleinformatics Engineering (DETI)/Graduate Program in Teleinformatics Engineering (PPGETI) at the Federal University of Ceará (UFC), Brazil. He earned a Ph.D in Mechanical Engineering from the Federal University of Paraíba (UFPB, 2010), a MSc in Teleinformatics Engineering from the PPGETI/UFC (UFC, 2007). He completed a BSE in Mechatronics Engineering at the Federal Center of Technological Education of Ceará (CEFETCE, 2006). He has experience in Biomedical Science and Engineering, mainly in the research fields of: Applied Computing, Intelligent Systems, Visualization and Interaction, with specific interest in Pattern Recognition, Artificial Intelligence, Image Processing and Analysis, as well as Automation with respect to biological signal/image processing, biomedical circuits and human/brain-machine interaction, including Augmented and Virtual Reality Simulation Modeling for animals and humans. Prof. Victor is a Full Member of the Brazilian Society of Biomedical Engineering (SBEB). He is Editor-in-Chief of the Journal of Biomedical and Biological Sciences, and, also, of the Journal of Artificial Intelligence and Systems, and Journal of Biological Sciences, as well as Associate Editor of the IEEE Journal of Biomedical and Health Informatics; Computers in Biology and Medicine; Frontiers in Cardiovascular Medicine; Computational Physiology and Medicine; Applied Soft Computing; IEEE Access, Frontiers in Communications and Networks, Computational Intelligence and Neuroscience, Measurement, IET Quantum Communication, and he has been Lead Guest Editor of several high-reputed journals, and TPC member of many international conferences. 

João Manuel R. S. Tavares graduated in Mechanical Engineering at the Universidade do Porto, Portugal in 1992. He also earned his M.Sc. degree and Ph.D. degree in Electrical and Computer Engineering from the Universidade do Porto in 1995 and 2001, and attained his Habilitation in Mechanical Engineering in 2015 from the same University. He is a senior researcher at the Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial (INEGI) and a Full Professor at the Department of Mechanical Engineering (DEMec) of the Faculdade de Engenharia da Universidade do Porto (FEUP). He has been the Head of DEMec since June 2023.

João Tavares is co-editor of more than 80 books, co-author of more than 50 book chapters, 650 articles in international and national journals and conferences, and 3 international and 3 national patents. He has been a committee member of several international and national journals and conferences, is co-founder and co-editor of the book series “Lecture Notes in Computational Vision and Biomechanics” published by Springer, founder and Editor-in-Chief of the journal “Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization” published by Taylor & Francis, Editor-in-Chief of the journal “Computer Methods in Biomechanics and Biomedical Engineering” published by Taylor & Francis, and co-founder and co-chair of the international conference series: International Symposium on Computational Modeling of Objects Presented in Images, ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing, International Conference on Computational and Experimental Biomedical Sciences and International Conference on Biodental Engineering. Additionally, he has been (co-)supervisor of several MSc and PhD theses and supervisor of several post-doc projects and has participated in many scientific projects both as a researcher and as scientific coordinator.

His main research areas include computational vision, medical imaging, biomechanics, biomedical engineering, and new product development.

Dr. Irina Illina received the Diploma in Computer Engineering in Russia in 1988 and Ph.D. degrees in Computer Science in France in 1997. After one year as a post-doctoral researcher in Carnegie Mellon University, Pittsburgh, USA, she became an Assistant Professor at the University of Lorraine, France. She received a habilitation degree from the University of Lorraine in 2005. Her research interests include deep learning for large vocabulary speech recognition, robust speech recognition, language model contextualization, and hate speech detection. She has authored or co-authored more than 100 papers in international and national journals and conferences. She participated in European projects, national projects, evaluation campaigns, and several industry contracts.

Marta Campos Ferreira is an Invited Assistant Professor at the Faculty of Engineering of University of Porto (FEUP) and Researcher at the Institute for Systems and Computer Engineering, Technology and Science (INESC TEC). She holds a PhD in Transport Systems from FEUP (MIT Portugal Program), a M.Sc. in Service Engineering and Management from FEUP and a Lic. in Economics from the Faculty of Economics of University of Porto.

She is the Co-Founder & Co-Editor of the Topical Collection “Research and Entrepreneurship: Making the Leap from Research to Business” with SN Applied Sciences, Associate Editor of the Expert Systems With Applications Journal and Associate Editor of the International Journal of Management and Decision Making.

She has been involved in R&D projects in areas such as technology enabled services, intelligent transport systems and mobility. Her main research interests include service design, human computer interaction, data science and knowledge extraction.

Xiao He received the B.Eng. degree in information technology from the Beijing Institute of Technology, Beijing, China, in 2004, and the Ph.D. degree in control science and engineering from the Tsinghua University, Beijing, China, in 2010.

He is currently a Tenured Professor with the Department of Automation, Tsinghua University. He is also the head of Research Center of Safety Control, Tsinghua University. He has authored more than 200 papers in refereed international journals. His research interests include fault diagnosis and fault-tolerant control of dynamic systems, networked systems, cyber-physical systems, as well as their applications.

Dr. He is a Full Member of Sigma Xi, the Scientific Research Society, and a Senior Member of the Chinese Association of Automation. He is an Associate Editor of {\it IEEE Transactions on Neural Networks and Learning Systems} and {\it Control Engineering Practice}.

Member, IEEE) (S’16–M’18) received the Ph.D. degree from Howard University, Washington,
DC, USA, in 2020 under the supervision of Prof. Danda B. Rawat. His Master degree from Howard
University, Washington, DC, USA and his bachelor degree from Tennessee State University,
Nashville, USA. He is currently working as an Assistant Professor with the Department of
Electrical Engineering and Computer Science, University of Hafr Albatin, Hafr Albatin, Saudi
Arabia. He has delivered Keynotes and invited speeches at international conferences and
workshops. He is engaged in research and teaching in the areas of cybersecurity, machine learning,
big data analytics, and wireless networking for emerging networked systems, including cyber–
physical systems, Internet of Things, smart cities, Edge computing, cognitive city, mobile
computing, network security, and Artificial Intelligence.
Dr. Alshammari is the recipient of the SACM Award in 2012,2013,2014,2015, and 2016. He has
been serving as a reviewer for over 5 international journals, including MDPI – (Sustainability
Journal) and Spring Nature (The Journal of Supercomputing). He has been in organizing
committees for several conferences. He served as a researcher on Cybersecurity and Wireless
Networking Innovations (CWiNs) Lab @ Howard University from 2016 to 2020. He was a
graduate research in the Howard University Data Science & Cybersecurity Center (DSC2) during
his PhD study. Formerly, he led Cybersecurity Innovation, Research, and Development at NEOM
and NEOM AUTHORITY. In addition, he served as Assistant Professor of Cybersecurity and
Artificial Intelligence on the Royal Commission for Jubail and Yanbu.

Dr. Ahmad Faiz Minai is a distinguished scholar and researcher in the field of Electrical Engineering,
with an illustrious career marked by significant contributions to academia and practical initiatives.
Currently he is a researcher at the Faculty of Electrical Engineering, Universiti Teknologi Malaysia
(UTM).
Prior to his current engagement, Dr. Minai amassed substantial teaching and research experience. He is
with Integral University (Currently on leave) and spent more than six years as an Associate Professor
in the Department of Electrical Engineering at Integral University, Lucknow, India, from January 2018
to April 2024. Preceding this tenure, he served for four years and three months in the Electrical and
Electronics Engineering Department at Integral University, Lucknow, India, from July 2009 to October
2013.
Dr. Minai’s academic journey is further adorned with remarkable achievements, including securing the
Graduate Aptitude Test in Engineering (GATE-2007) scholarship from the Ministry of Human Resource
Development, Government of India, with an impressive percentile of 91.71 and All India Rank (AIR)
of 1392.
Furthermore, Dr. Minai has demonstrated his expertise through numerous international publications,
including 64 published papers and 18 in communication, reflecting his profound impact in the academic
community with an h-index of 14 as of May 2024.
His prolific research output encompasses contributions to international journals, conferences, and book
chapters, showcasing his versatility and depth of knowledge in the field of Renewable Energy
Integration, Artificial Intelligence, Machine Learning, Data Analytics, Power Electronic Converters,
Internet of Things etc. Additionally, Dr. Minai holds five patents, including four Indian published
patents and one UK Design Granted patent, underscoring his innovative prowess.
Notably, Dr. Minai has undertaken the role of guest editor for two special issues, demonstrating his
leadership in scholarly endeavors. He is also actively engaged in a significant project focusing on Health
Monitoring, Performance Optimization, and Cost-Evaluation Framework for the 91 kW Rooftop GridConnected Solar Photovoltaic System at Integral University, Lucknow, India.
Dr. Ahmad Faiz Minai’s multifaceted contributions to academia and research epitomize his dedication
to advancing knowledge and fostering innovation in the field of Electrical Engineering.

Shaymaa Ezz ElArab Mohamed Sorour is an accomplished Associate Professor of Computer Science at King Faisal University in Saudi Arabia, specializing in Artificial Intelligence and Machine Learning Algorithms. She holds a PhD in Computer Science from Kyushu University, Japan. Shaymaa’s research contributions are widely recognized, with publications in prestigious journals and presentations at international conferences. She is actively engaged in professional networks, with a strong presence on platforms like Google Scholar, ResearchGate, and Scopus. Beyond academia, Shaymaa is passionate about philanthropy and community empowerment. Her journey exemplifies a relentless pursuit of excellence and a dedication to pushing the boundaries of knowledge in her field. Shaymaa finds inspiration in family, cultural exploration, and literature, embodying a holistic approach to life and scholarship.

Shantian Yang is currently a lecturer at School of Computing and Artificial Intelligence, Southwestern University
of Finance and Economics, Chengdu, China. He received the B.Eng. degree in computer science and
engineering from the Chengdu college of University of Electronic Science and Technology of China (Chengdu),
China, in 2009; and the M.S. and Ph.D degrees from Computer Science and Engineering, University of Electronic
Science and Technology of China, China, in 2018 and 2022. His current research interests include reinforcement
learning, multi-agent learning, graph representation learning, explanation machine learning-xAI
and their applications to quantitative trading, portfolio management and traffic signal control,.

Rizwan Qureshi Senior Member IEEE received the Ph.D. degree from the City University of Hong Kong, Hong Kong, in 2021. He joined the Fast National University of Computer and Emerging Sciences, Karachi, Pakistan, as an Assistant Professor. He is currently with the College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar. He published his findings and methods in IEEE Transactions on Computational Biology and Bioinformatics, IEEE Journal of Biomedical and Health Informatics, Pattern Recognition, and IEEE BIBM conference. His research interests include AI applications in life sciences, cancer data sciences, computer vision, and machine learning. His Ph.D. thesis focused on lung cancer drug resistance analysis using molecular dynamics simulation and machine learning.

Xinheng Wang received the B.E. and M.Sc. degrees in electrical engineering from Xian Jiaotong University, Xi’an, China, in 1991 and 1994, respectively, and the Ph.D. degree in electrical engineering from Brunel University, Uxbridge, U.K., in 2001. He was the founding Head of Department of Mechatronics and Robotics, Xi’an Jiaotong-Liverpool University (XJTLU), Suzhou 215123, China. Prior to joining XJTLU, he was a professor with different universities in the UK.

He has been an Investigator or Co-Investigator of 30+ research projects sponsored from EU, UK EPSRC, Innovate UK, China NSFC, and industry. Total received funding is over 50 million CNY. He has authored or coauthored 230+ referred papers. He holds 26 granted patents, including 1 US, 1 Japan, 4 South Korea and 20 Chinese patents. He was one of the key developers of the world’s first smart trolley to provide intelligent services to passengers at airports. He is currently leading the XJTLU-uGo Robotics Research Centre with multi-million Yuan sponsorship from industry to develop airport robots. His current research interests include intelligent and connected systems, including robotics and healthcare systems, indoor acoustic localization, acoustic posture detection and recognition, and robotic SLAM and navigation.

I am currently an assistant professor with the College of Electrical Engineering at Zhejiang University, leading a research section specializing in Artificial Intelligence for Power and Energy Systems (AI4PES). Prior to this role, I served as a senior researcher at Zhejiang Lab, overseeing a research section focused on Scientific Artificial Intelligence. I completed the doctoral training at Zhejiang University and Argonne National Laboratory.

Yifan Liu graduated with a Bachelor of Engineering degree in Computer Science and Technology in 2022. He is currently pursuing a Master of Engineering degree in Electronic Information at Tsinghua University, China, where he focuses on the intersection of technology and bioinformatics. His research interests span gait analysis, big data analysis techniques, and computer simulations relevant to bioinformatics.

My name is Xiaohe Li, currently working as an assistant researcher in the Aerospace Information Innovation Research Institute of the Chinese Academy of Sciences. I mainly study the data mining of aerospace information and currently participate in several key projects.

Yonggang Lu is now working as a professor in the School of Information Science and Engineering, Lanzhou University, Lanzhou, China. He is a member of IEEE and Chinese Computer Federation. He received both the B.S. and M.S. Degrees in Physics from Lanzhou University, Lanzhou, China in 1996 and 1999 respectively. Later he received the M.S. and Ph.D. Degrees in Computer Science from New Mexico State University, Las Cruces, NM, USA in 2004 and 2007 respectively. He finished some of the Ph.D. work at Los Alamos National Lab, NM, USA. His main research interests include artificial Intelligence, machine learning, computer vision and bioinformatics. He has published over 80 research papers. And has presided over a Chinese Nation Science Foundation project and other projects. More information about his research work can be found at https://www.researchgate.net/profile/Yonggang-Lu/.

Paolo Pagnottoni is an assistant professor of Statistics at the University of Insubria, Varese, Italy. He holds a PhD in Applied Economics and Management with a focus on Statistics from the University of Bergamo, two MSc degrees in Finance and Econometrics, and a Bachelor’s Degree in Economics and Statistics. He has been a visiting scholar at various institutions such as the University of Minnesota, the National University of Singapore, University College London, and De Nederlandsche Bank, among others. He is an Associate Editor of the journal Measurement. He has published in several international peer-reviewed journals, and his main research interests include Multivariate Time Series, Financial Data Science, Computational Statistics, Machine Learning, Machine Learning for Time Series, Network Econometrics, Financial Technologies, Cryptocurrency Markets, Financial Risk Management, Artificial Intelligence, and its applications to Economics and Finance.

Dr. Tao Ruan earned his PhD from the University of Colorado Boulder. Prior to his doctoral studies, he received a Master’s degree from Rutgers University and a Bachelor’s degree from the University of Science and Technology of China. Dr. Ruan’s research spans several cutting-edge areas including crisis informatics, computational social science, social computing, and electrified transportation. Throughout his career, he has collaborated extensively with renowned institutions such as the USGS, UC Berkeley Seismology Lab, and Livermore National Laboratory, contributing to a series of impactful publications.

An active member of the academic community, Dr. Ruan has served as a peer reviewer for over 30 instances across prestigious journals and conferences including AAAI ISWSM, Technological Forecasting and Social Change, Computers in Human Behavior, Scientific Reports, etc. He has also been invited to serve on the committees of numerous international conferences

Dr. Murtadha Ahmed is an accomplished NLP researcher with a Ph.D. in Computer Science from Northwestern Polytechnical University. His expertise lies in the domain of deep learning for NLP tasks, with a focus on enhancing the context capacity of Large Language Models (LLMs), in-context learning, and reducing reliance on labeled data.

Throughout his career, Dr. Ahmed has made significant contributions to the field of NLP, publishing extensively in top-tier venues such as ACL, NAACL, TACL, and KBS. He is renowned for his groundbreaking work on Rotary Positional Embeddings (RoPE), RNT, and LNPL, which have garnered widespread recognition and acclaim within the research community.

Moein Qaisari Hasan Abadi is an accomplished Industrial Engineering professional, currently engaged as a Doctor of Philosophy student specializing in Operation Research and Management at ESSEC Business School in Cergy, France. With a Master of Science in Industrial Engineering from Toosi University of Technology in Tehran, Iran, where he excelled with a GPA of 3.84/4.00, Moein has solidified his expertise in systems optimization.

Moein’s rigorous academic pursuits are matched by his robust practical experience. He has contributed as a Continuous Improvement Expert at Rizsazgan Takin Company in Tehran from March 2021 to March 2023 and previously as a Quality Control Associate at Sepid-Morgh Company in Isfahan. His early career also included a role as a business plan associate at Ideh Pardazan Parto Company.

A prolific researcher, Moein has authored several high-impact publications focusing on sustainability, supply chain resilience, and robust computational methods. His works include studies on dynamic energy pricing models using blockchain and machine learning, and strategic approaches to COVID-19 patient care through hybrid algorithms.

Moein is proficient in a range of technical software and has engaged in substantial academic training, with multiple online courses from FaraDars Institute in areas like data mining and machine learning. He is multilingual, fluent in Persian, English, and French, and has professional proficiency in Zoroastrian, underlined by impressive TOEFL and GRE scores.

His intellectual contributions extend beyond his research; Moein has facilitated workshops on robust optimization and meta-heuristic algorithms and has consistently participated in international conferences, showcasing his commitment to the advancement of industrial engineering and operations research.

Dr Xianbo Zhao is an Associate Professor of built environment at Central Queensland university, Australia. He has led or participated in research projects relating to AI enabled construction risk management and smart construction management.

Yue Zhang is an Assistant Professor at Drexel University’s Computer Science department. His research primarily focuses on system security, specifically in the areas of IoT Security and mobile security. He has published more than 40 papers in security conferences (e.g., USENIX Security, ACM CCS, and NDSS) and journals (e.g., TDSC, TPDS). He received a Best Paper Honorable Mention Award at ACM CCS 2022, and the Best Paper Award at 2019 IEEE International Conference on Industrial Internet. He has also served on the organization committees of the conferences (e.g., general chair of EAI ICECI, track chair for IEEE MSN and IEEE MASS) and technical program committee of the conferences (e.g., USENIX Security, NDSS, ACM CCS, RAID). He serves as an Associate Editor for IEEE T-IFS, HCC and Editor Member of the Blockchain Journal, Electronics Journal, and CMC. His research had led to the discovery of many vendor-acknowledged vulnerabilities, such as by Bluetooth SIG, Apple, Google, and Texas Instruments, and had attracted intense media attention such as Hacker News, and Mirage News.

“Dr. Van-Ha Luong is an academic researcher at the IESEG School of Management in France and also serves as a visiting professor at the Industrial University of Ho Chi Minh City in Vietnam. His research is centered on sustainable tourism and examining consumer behavior in virtual environments, such as video games and the metaverse.. Dr. Luong is noted for his extensive use of advanced analytical techniques, particularly text mining and machine learning, in his research methodology.”

Danilo Cavaliere received both the master degree cum laude in computer science and the Ph.D. degree with judgement excellent from the University of Salerno (Italy) in 2014 and 2020, respectively. He works now as a researcher for the same institution and he is involved in Security and Rights In the Cyberspace (SERICS) research project, that is funded by European Community. Dr. Cavaliere is in the editorial board of Neurocomputing journal and was in Program Committees of international conferences, such as IEEE Symposium Series on Computational Intelligence (SSCI) and World Conference on explainable Artificial Intelligence (XAI). His research interests include artificial and computational intelligence, knowledge-based systems, soft computing, intelligent agents, data mining and knowledge discovery, on which he has published many papers.

Sean Lam leads the data science pillar in the SingHealth Health Service Research Centre. He is also an Adjunct Associate Professor with the Duke-NUS Health Service and Systems Research Signature Program and the SingHealth Duke-NUS Global Health Institute. He is also an adjunct faculty with the Singapore Management University. His research passion lies in the application of data science and advanced quantitative methodologies to solve complex health system problems. His interdisciplinary research focus aims to advance academic knowledge and influence healthcare policy and practice, promoting a data-driven, evidence-based, and patient-centric approach towards the effective delivery of health services.