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. Chinthaka Premachandra
Shibaura Institute of Technology, Japan

Bio: Chinthaka Premachandra (Senior Member, IEEE) was born in Sri Lanka. He received his B.Sc. and M.Sc. degrees from Mie University, Tsu, Japan, in 2006 and 2008, respectively, and his Ph.D. degree from Nagoya University, Nagoya, Japan, in 2011. He is a Professor in the Department of Advanced Electronic Engineering, School of Engineering and Graduate School of Engineering, Shibaura Institute of Technology, Tokyo, Japan, where he currently serves as the Director of the Image Processing and Robotics Laboratory. His research interests include AI, UAVs, image processing, audio processing, intelligent transport systems (ITS), and mobile robotics. He has authored or co-authored over 200 publications in reputed journals and conferences related to these fields.
He is currently an Associate Editor for IEEE Robotics and Automation Letters (R-AL) and IEICE Transactions on Information and Systems. He is a member of IEEE, IEICE (Japan), SICE (Japan), RSJ (Japan), and SOFT (Japan). He has received numerous awards, including the IEEE SENSORS LETTERS Best Paper Award from the IEEE Sensors Council in 2022 and the IEEE Japan Medal from the IEEE Tokyo Section in 2022.He is also the Founding Chair of the International Conference on Image Processing and Robotics (ICIPRoB), which is technically co-sponsored by IEEE.

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. Sook Shin
Virginia Tech, USA

Bio: Dr. Sook Shin is a Collegiate Assistant Professor in the Department of Electrical and Computer Engineering at Virginia Tech. Her primary area of expertise is bioinformatics, particularly in the analysis of gene and disease data. Through her research, she applies advanced computational methods to better understand complex biological systems and their implications for human health. In addition to her work in bioinformatics, Dr. Sook Shin has recently expanded her research into the area of precision livestock management, using Artificial Intelligence (AI) to improve the monitoring and management of livestock. This work focuses on automated behavior analysis and predictive modeling, with the goal of optimizing livestock health and productivity. By predicting factors such as weight and body condition, her research aims to provide farmers with better tools for managing livestock efficiently while ensuring animal well-being. Dr. Sook Shin earned her Ph.D. from Virginia Tech in 2012, which laid the foundation for her current research in both bioinformatics and AI. Her interdisciplinary approach to combining computational methods with agriculture and health has opened up new possibilities for both fields, contributing valuable insights to the growing intersection of technology, biology, and farming.

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.