Dr. Jaime Lloret Mauri
Polytechnic University of Valencia, Spain
Prof. Jaime Lloret is a Full Professor at the Universitat Politècnica de València (UPV), where he is affiliated with the Instituto de Investigación para la Gestión Integrada de Zonas Costeras (IGIC). He is widely recognized for his pioneering contributions to telecommunication networks, wireless sensor systems, and applied information technologies.
He received his M.Sc. in Physics (1997) and later an M.Sc. in Electronic Engineering (2003) from the University of Valencia, followed by a Ph.D. in Telecommunication Engineering from UPV in 2006. He also completed a postgraduate Master in Corporate Networks and Systems Integration (1999). Alongside his studies, he gained professional experience as a network designer and administrator (1997–2001) while teaching more than 2,400 hours of training courses.
At UPV, he founded the Communications and Networks Research Group in 2007 and has served as Director of IGIC since 2017. He also leads the Innovation Group on collaborative learning (EITACURTE) and has directed several academic programs, including the Diploma in Computer Networks and Communications. Internationally, he has held leadership positions within the IEEE Communications Society and Internet Society, notably as Chair of the Internet Technical Committee (2013–2015) and Chair of the IEEE 1907.1 Standard Working Group (2013–2018).
Prof. Lloret has published over 900 papers, including around 600 in JCR-indexed journals, contributed to more than 45 book chapters, authored 12 teaching books, and co-authored 15 patents. His work has earned over 29,000 citations (h-index 84, Google Scholar). Since 2016, he has been ranked as the top Spanish researcher in the Telecommunications journal list by Clarivate Analytics and has consistently appeared in Stanford University's "World's Top 2% Scientists" list.
He serves as Editor-in-Chief of Network Protocols and Algorithms and Ad Hoc & Sensor Wireless Networks, and sits on the editorial boards of over 40 international journals. He has chaired or co-chaired more than 85 international conferences and delivered more than 40 keynote and plenary talks.
His research spans network protocols, wireless sensor networks, multimedia communications, and security, with practical applications in precision agriculture, marine monitoring, emergency management, and healthcare. He is an IEEE Senior Member, ACM Senior Member, IARIA Fellow, and EAI Fellow.
Dr. Sobhan Babu
Indian Institute of Technology, Hyderabad, India
Dr. Sobhan Babu is an Associate Professor at IIT Hyderabad with a passion for exploring the intricate world of data analytics. He had a Ph.D. from IIT Bombay, where his research delved into the fascinating realm of Applied Graph Theory and Algorithms. His thesis, "Degree Conditions for Subgraphs," marked a significant milestone in his academic pursuits with the best Ph.D. award from IBM.
With over a decade of experience, his journey through academia has been enriched by roles that have shaped his expertise. His professional journey extends beyond academia. He worked in the industry as a Senior Software Engineer at both Softjin Technologies and Tessera Systems, where he gained practical insights that continue to enrich his teaching and research.
Beyond the classroom and industry, his passion for data analytics finds expression in diverse projects. He leads the GST Analytics project of several states as Principal Investigator. Additionally, he serves as an IT adviser for the Business Analytics Project at the Insurance Regulatory and Development Authority of India. His commitment to the nation's well-being is evident through his support for the Ayushman Bharat Digital Mission and consultancy work for the Data Analytics Projects at the National Payments Corporation of India. He continues to contribute to the academic and professional spheres, driving innovation and knowledge dissemination.
Dr. Siva Balan N
Data Integration Specialist, NTT DATA, Bengaluru, India
His expertise spans Python programming, SQL, machine learning, data science, cloud computing, and API integration. Dr. Balan has published 18 research papers in Scopus, UGC, and SCI-indexed journals, and has filed three patents.
Previously, he served as a faculty member and led the IBM Center of Excellence at New Horizon College of Engineering, guiding numerous machine learning projects and industry collaborations. His career also includes roles at Subex, Mindtree, and Wipro, where he contributed extensively to software engineering and quality assurance.
Dr. Watchara Ruangsang
School of Architecture and Design,King Mongkut's University of Technology Thonburi, Thailand
Dr. Watchara Ruangsang is a Lecturer in Media Technology at the School of Architecture and Design, King Mongkut's University of Technology Thonburi (KMUTT), Bangkok, Thailand. He earned his Doctor of Philosophy in Electrical Engineering from Chulalongkorn University in 2024, where his dissertation focused on real-time image super-resolution reconstruction for system-on-chip FPGA. His doctoral research, supervised by Assoc. Prof. Dr. Supavadee Aramvith, built upon his earlier work in super-resolution techniques completed during his Master of Engineering studies at Chulalongkorn University in 2015. Dr. Ruangsang began his academic journey with a Bachelor of Engineering in Electrical Engineering from King Mongkut's University of Technology North Bangkok in 2011.
Dr. Ruangsang’s research expertise spans digital image and video processing, computer vision for surveillance applications, and compute-intensive solutions on FPGA and embedded systems. He has contributed to multiple high-impact research projects funded by leading Thai agencies, with a cumulative budget exceeding 9 million Baht. His projects include the development of image and video super-resolution algorithms, FPGA-based hardware prototypes, and applications of artificial intelligence in medical imaging.
An active contributor to the academic community, Dr. Ruangsang has published extensively in IEEE conferences and journals, achieving an h-index of 4 with more than 65 citations. His notable works include papers presented at TENCON, ISCIT, APSIPA ASC, ISCAS, and JCSSE, as well as publications in IEEE Access. Beyond publications, he has also filed multiple patents in Thailand related to image super-resolution, FPGA hardware prototypes, face recognition, and medical devices for breast cancer-related edema detection.
Dr. Ruangsang has been recognized with several prestigious awards, including the Gold Medal Award at Innovation Week Africa (2020), the Silver and Gold Medals at the International Exhibition of Inventions Geneva (2021, 2023), and the Outstanding Student Award from Chulalongkorn University in 2022.
In addition to his academic and research roles, Dr. Ruangsang has actively engaged as a guest lecturer and invited speaker. He has delivered professional workshops on FPGA-based edge AI and accelerator applications in collaboration with organizations such as TESA, AMD, and the National Innovation Agency (NIA). Since February 2025, he has also served as Chair of the IEEE Thailand Section Young Professionals, furthering his commitment to fostering innovation and professional development in the engineering community.
Dr. Ruangsang continues to advance research in image processing and embedded AI systems, with a vision of bridging cutting-edge technology with real-world applications in healthcare, surveillance, and digital media.
Dr Manuel Chaves Maza
Professor and Researcher, Universidad Pablo de Olavide, Spain
Prof. Manuel Chaves Maza is a distinguished academic and researcher specializing in artificial intelligence, statistics, and entrepreneurship support systems. He is currently a Professor at the Universidad Pablo de Olavide (UPO), Spain, where he has been actively contributing since 2007. Accredited as a Contracted Doctor, Prof. Chaves Maza has over 17 years of teaching experience across five academic institutions and more than 18 years of professional consulting expertise in training, development, and innovation.
He earned his Doctorate in Artificial Intelligence applied to Business Administration from UPO in 2020, where his thesis, An Intelligent Support System for Entrepreneurs (SIAPE), received unanimous Cum Laude honors, the Extraordinary University Award, and the Best Andalusian Doctoral Thesis Award. His academic foundation also includes degrees in Business Administration and Management, Agricultural Technical Engineering, and Computer Engineering, reflecting his interdisciplinary expertise.
Prof. Chaves Maza has authored more than 15 publications in high-impact journals, including the Journal of Innovation and Entrepreneurship, Social Science (MDPI), and Journal of Research in Marketing and Entrepreneurship. His research focuses on applying artificial intelligence and multivariate statistical techniques—such as neural networks, decision trees, SEM, and fsQCA—to entrepreneurship, business development, and education. He has participated in national and international R&D projects exceeding 200 initiatives, addressing topics such as augmented reality for lean manufacturing in the aeronautical sector, quality verification through expert systems, and socio-productive system characterization in large-scale engineering projects.
In academia, Prof. Chaves Maza has taught courses in statistics, advanced statistics, financial mathematics, and statistical inference applied to finance, across degrees in Finance, Business Administration, Tourism, and Law. His teaching innovation has also been recognized through projects such as Your Learning Way, an interactive application for enhancing classroom engagement, which earned him the Spin-Off Entrepreneur Award and selection by CITIC as a pioneering project.
Beyond teaching and research, he has served as a reviewer for journals including Equity and Development and Measuring Business Excellence, and is a member of the research group SEJ332, Quantitative Methods in Business and Economics. He has presented his work at numerous international conferences and has been involved in major research collaborations across Europe and Latin America.
Prof. Chaves Maza continues to bridge the gap between academia and industry, advancing the role of artificial intelligence and quantitative methods in fostering entrepreneurship, business innovation, and educational excellence.
