Prof. Antonio Alarcón-Paredes
National Polytechnic Institute, Mexico

Bio: Dr. Antonio Alarcón-Paredes is a professor at the Intelligent Computing Laboratory of the Computer Research Center at the National Polytechnic Institute, where he also earned his Ph.D. in Computer Science. With over a decade of experience in the field, he has authored multiple articles in high-reputed journals and international conferences. He holds one granted patent and three others pending. Since 2020, he has been recognized as a Level 1 National Researcher by the Ministry of Humanities, Science, and Technology of the Mexican government and is also a member of the Mexican Society for Artificial Intelligence. His research interests include the development of algorithms and applications in areas such as image analysis, computer vision, machine learning, deep learning, intelligent computing applications, and biomedical applications.

Prof. Abril Uriarte Arcia
CIDETEC - IPN, Mexico

Bio: Dr. Uriarte is a teacher/researcher at the Center for Innovation and Development in Computing Technology (CIDETEC) of the Instituto Politécnico Nacional (IPN), México, since 2016. His areas of work include topics related to machine learning, pattern classification, neural networks, deep learning, associative memories, time series prediction, and data stream classification. She has participated in the development of projects where intelligent computing methods are applied to problems of social impact such as pre-diagnosis of diseases and environmental monitoring.
Dr. Uriarte earned a BSc in Computer Engineering from the National University of Engineering (UNI) in Managua, Nicaragua. She received her MSc and PhD in Computer Science from The Computing Research Center, IPN.
She is a professor in Artificial Intelligence Engineering and Master's in Computing Technology programs at the IPN, in Bioinspired Algorithms and Machine Learning topics. She has participated in the creation of academic programs such as the Artificial Intelligence Engineering program and the graduate program (master's and doctorate) in Artificial Intelligence Science and Technology and Data Science. Member of the IPN research networks in Computing and Artificial Intelligence and Data Science.

Asst. Prof. Isaac Kofi Nti
University of Cincinnati, USA

Bio: Dr. Isaac Kofi Nti is an Assistant Professor and Co-lead of the Information Technology Analytics Center (ITAC) at the School of Information Technology, University of Cincinnati, Ohio, USA. He holds a Ph.D. in Computer Science from the University of Energy and Natural Resources (UENR) and brings over 16 years of experience in higher education. Dr. Nti has published over 60 research papers in highly peer-reviewed journals, garnering more than 2,400 citations worldwide. Building on his extensive experience, Dr. Nti's research interests include applied machine learning in cybersecurity, education, health informatics, energy systems, agriculture, finance, and data privacy. As a seasoned academician and researcher, Dr. Nti is dedicated to advancing the field of applied machine learning.

Assoc. Prof. Jiaxin Cai
Xiamen University of Technology, China

Bio: Jiaxin Cai received his Ph.D. degree in Information and Computation Science from Sun Yat-Sen University in 2014. He also received his M.S. degree and B.Sc. degree in Bio-medical Engineering from Southern Medical University in 2011 and 2008 respectively. Currently, he is an associate professor in the School of Mathematics and Statistics at Xiamen University of Technology. He has authored over 40 peer-reviewed papers at academic journals and conferences. His current research interests include machine learning, computer vision and bio-medical engineering.

Dr. Vishnu S. Pendyala
San Jose State University, USA

Bio: Vishnu S. Pendyala, PhD is a faculty member in Applied Data Science and an Academic Senator with San Jose State University, current chair of the IEEE Computer Society Santa Clara Valley Chapter, and IEEE Computer Society Distinguished Contributor. During his recent 3-year term as an ACM Distinguished Speaker and before that as a researcher and industry expert, he gave numerous (80+) talks in various reputed forums. Some of these talks are available on YouTube and IEEE.tv. He is a senior member of the IEEE and ACM and has over two decades of experience in the software industry in the Silicon Valley, USA. His book, “Veracity of Big Data,” is available in several libraries, including those of MIT, Stanford, CMU, the US Congress and internationally. In 2023, Dr. Pendyala served on the US government's National Science Foundation (NSF) proposal review panel.